WorldWideScience

Sample records for grossly normal recognition

  1. Combining Illumination Normalization Methods for Better Face Recognition

    NARCIS (Netherlands)

    Boom, B.J.; Tao, Q.; Spreeuwers, L.J.; Veldhuis, R.N.J.

    2009-01-01

    Face Recognition under uncontrolled illumination conditions is partly an unsolved problem. There are two categories of illumination normalization methods. The first category performs a local preprocessing, where they correct a pixel value based on a local neighborhood in the images. The second categ

  2. Channel normalization technique for speech recognition in mismatched conditions

    CSIR Research Space (South Africa)

    Kleynhans, N

    2008-11-01

    Full Text Available , where one wishes to use any available training data for a variety of purposes. Research into a new channel normalization (CN) technique for channel mismatched speech recognition is presented. A process of inverse linear filtering is used in order...

  3. Does cognitive function predict frequency compressed speech recognition in listeners with normal hearing and normal cognition?

    Science.gov (United States)

    Ellis, Rachel J; Munro, Kevin J

    2013-01-01

    The aim was to investigate the relationship between cognitive ability and frequency compressed speech recognition in listeners with normal hearing and normal cognition. Speech-in-noise recognition was measured using Institute of Electrical and Electronic Engineers sentences presented over earphones at 65 dB SPL and a range of signal-to-noise ratios. There were three conditions: unprocessed, and at frequency compression ratios of 2:1 and 3:1 (cut-off frequency, 1.6 kHz). Working memory and cognitive ability were measured using the reading span test and the trail making test, respectively. Participants were 15 young normally-hearing adults with normal cognition. There was a statistically significant reduction in mean speech recognition from around 80% when unprocessed to 40% for 2:1 compression and 30% for 3:1 compression. There was a statistically significant relationship between speech recognition and cognition for the unprocessed condition but not for the frequency-compressed conditions. The relationship between cognitive functioning and recognition of frequency compressed speech-in-noise was not statistically significant. The findings may have been different if the participants had been provided with training and/or time to 'acclimatize' to the frequency-compressed conditions.

  4. Iterative closest normal point for 3D face recognition.

    Science.gov (United States)

    Mohammadzade, Hoda; Hatzinakos, Dimitrios

    2013-02-01

    The common approach for 3D face recognition is to register a probe face to each of the gallery faces and then calculate the sum of the distances between their points. This approach is computationally expensive and sensitive to facial expression variation. In this paper, we introduce the iterative closest normal point method for finding the corresponding points between a generic reference face and every input face. The proposed correspondence finding method samples a set of points for each face, denoted as the closest normal points. These points are effectively aligned across all faces, enabling effective application of discriminant analysis methods for 3D face recognition. As a result, the expression variation problem is addressed by minimizing the within-class variability of the face samples while maximizing the between-class variability. As an important conclusion, we show that the surface normal vectors of the face at the sampled points contain more discriminatory information than the coordinates of the points. We have performed comprehensive experiments on the Face Recognition Grand Challenge database, which is presently the largest available 3D face database. We have achieved verification rates of 99.6 and 99.2 percent at a false acceptance rate of 0.1 percent for the all versus all and ROC III experiments, respectively, which, to the best of our knowledge, have seven and four times less error rates, respectively, compared to the best existing methods on this database.

  5. Super Normal Vector for Human Activity Recognition with Depth Cameras.

    Science.gov (United States)

    Yang, Xiaodong; Tian, YingLi

    2017-05-01

    The advent of cost-effectiveness and easy-operation depth cameras has facilitated a variety of visual recognition tasks including human activity recognition. This paper presents a novel framework for recognizing human activities from video sequences captured by depth cameras. We extend the surface normal to polynormal by assembling local neighboring hypersurface normals from a depth sequence to jointly characterize local motion and shape information. We then propose a general scheme of super normal vector (SNV) to aggregate the low-level polynormals into a discriminative representation, which can be viewed as a simplified version of the Fisher kernel representation. In order to globally capture the spatial layout and temporal order, an adaptive spatio-temporal pyramid is introduced to subdivide a depth video into a set of space-time cells. In the extensive experiments, the proposed approach achieves superior performance to the state-of-the-art methods on the four public benchmark datasets, i.e., MSRAction3D, MSRDailyActivity3D, MSRGesture3D, and MSRActionPairs3D.

  6. Digital image pattern recognition system using normalized Fourier transform and normalized analytical Fourier-Mellin transform

    Science.gov (United States)

    Vélez-Rábago, Rodrigo; Solorza-Calderón, Selene; Jordan-Aramburo, Adina

    2016-12-01

    This work presents an image pattern recognition system invariant to translation, scale and rotation. The system uses the Fourier transform to achieve the invariance to translation and the analytical Forier-Mellin transform for the invariance to scale and rotation. According with the statistical theory of box-plots, the pattern recognition system has a confidence level at least of 95.4%.

  7. Glassfiber post: an alternative for restoring grossly decayed primary incisors.

    Science.gov (United States)

    Mehra, Manjul; Grover, Rashu

    2012-05-01

    Restoration of primary incisors, which have been severely damaged by rampant caries or trauma, is a difficult task for the pediatric dentist. With the introduction of new adhesive systems and restorative materials, alternative approaches for treating these teeth have been proposed. This paper discusses the restoration of carious primary maxillary incisors using composite resin restoration reinforced with fiberglass post. Two case reports are presented here to describe the procedure. Over a 1 year period, the crowns have demonstrated good retention and esthetic results. How to cite this article: Mehra M, Grover R. Glassfiber Post: An Alternative for Restoring Grossly Decayed Primary Incisors. Int J Clin Pediatr Dent 2012;5(2):159-162.

  8. Recognition of "real-world" musical excerpts by cochlear implant recipients and normal-hearing adults.

    Science.gov (United States)

    Gfeller, Kate; Olszewski, Carol; Rychener, Marly; Sena, Kimberly; Knutson, John F; Witt, Shelley; Macpherson, Beth

    2005-06-01

    The purposes of this study were (a) to compare recognition of "real-world" music excerpts by postlingually deafened adults using cochlear implants and normal-hearing adults; (b) to compare the performance of cochlear implant recipients using different devices and processing strategies; and (c) to examine the variability among implant recipients in recognition of musical selections in relation to performance on speech perception tests, performance on cognitive tests, and demographic variables. Seventy-nine cochlear implant users and 30 normal-hearing adults were tested on open-set recognition of systematically selected excerpts from musical recordings heard in real life. The recognition accuracy of the two groups was compared for three musical genre: classical, country, and pop. Recognition accuracy was correlated with speech recognition scores, cognitive measures, and demographic measures, including musical background. Cochlear implant recipients were significantly less accurate in recognition of previously familiar (known before hearing loss) musical excerpts than normal-hearing adults (p performance on selected speech perception tests, and the amount of focused music listening following implantation. Current-day cochlear implants are not effective in transmitting several key structural features (i.e., pitch, harmony, timbral blends) of music essential to open-set recognition of well-known musical selections. Consequently, implant recipients must rely on extracting those musical features most accessible through the implant, such as song lyrics or a characteristic rhythm pattern, to identify the sorts of musical selections heard in everyday life.

  9. New Fuzzy-based Retinex Method for the Illumination Normalization of Face Recognition

    Directory of Open Access Journals (Sweden)

    Gi Pyo Nam

    2012-10-01

    Full Text Available We propose a new illumination normalization for face recognition which robust in relation to the illumination variations on mobile devices. This research is novel in the following five ways when compared to previous works: (i a new fuzzy‐based Retinex method is proposed for illumination normalization; (ii the performance of face recognition is enhanced by determining the optimal parameter of Retinex filtering based on fuzzy logic; (iii the output of the fuzzy membership function is adaptively determined based on the mean and standard deviations of the grey values of the detected face region; (iv through the comparison of various defuzzification methods in terms of the accuracy of face recognition, one optimal method was selected; (v we proved the validations of the proposed method by testing it with various face recognition methods. Experimental results showed that the accuracy of the face recognition with the proposed method was enhanced compared to previous ones.

  10. Categorization and category effects in normal object recognition

    DEFF Research Database (Denmark)

    Gerlach, Christian; Law, I; Gade, A

    2000-01-01

    ). The object decision tasks were associated with activation of areas involved in structural processing (fusiform gyri, right inferior frontal gyrus). In contrast, the categorization tasks were associated with activation of the left inferior temporal gyrus, a structure believed to be involved in semantic......To investigate the neural correlates of the structural and semantic stages of visual object recognition and to see whether any effects of category could be found at these stages, we compared the rCBF associated with two categorization tasks (subjects decided whether pictures represented artefacts...... or natural objects), and two object decision tasks (subjects decided whether pictures represented real objects or nonobjects). The categorization tasks differed from each other in that the items presented in the critical scan window were drawn primarily from the category of artefacts in the one task and from...

  11. Perceptual differentiation and category effects in normal object recognition

    DEFF Research Database (Denmark)

    Gerlach, Christian; Law, I; Gade, A

    1999-01-01

    on artefacts in the difficult object decision tasks. Natural objects also recruited larger parts of the right inferior temporal and anterior fusiform gyri compared with artefacts as task difficulty increased. Differences in the amount of activation in these regions may reflect the greater perceptual......The purpose of the present PET study was (i) to investigate the neural correlates of object recognition, i.e. the matching of visual forms to memory, and (ii) to test the hypothesis that this process is more difficult for natural objects than for artefacts. This was done by using object decision...... tasks where subjects decided whether pictures represented real objects or non-objects. The object decision tasks differed in their difficulty (the degree of perceptual differentiation needed to perform them) and in the category of the real objects used (natural objects versus artefacts). A clear effect...

  12. Syntactic error modeling and scoring normalization in speech recognition: Error modeling and scoring normalization in the speech recognition task for adult literacy training

    Science.gov (United States)

    Olorenshaw, Lex; Trawick, David

    1991-01-01

    The purpose was to develop a speech recognition system to be able to detect speech which is pronounced incorrectly, given that the text of the spoken speech is known to the recognizer. Better mechanisms are provided for using speech recognition in a literacy tutor application. Using a combination of scoring normalization techniques and cheater-mode decoding, a reasonable acceptance/rejection threshold was provided. In continuous speech, the system was tested to be able to provide above 80 pct. correct acceptance of words, while correctly rejecting over 80 pct. of incorrectly pronounced words.

  13. Predicting consonant recognition and confusions in normal-hearing listeners

    DEFF Research Database (Denmark)

    Zaar, Johannes; Dau, Torsten

    2017-01-01

    confusion groups. The large predictive power of the proposed model suggests that adaptive processes in the auditory preprocessing in combination with a cross-correlation based template-matching back end can account for some of the processes underlying consonant perception in normal-hearing listeners...

  14. Perturbation and Pitch Normalization as Enhancements to Speaker Recognition

    Science.gov (United States)

    2009-04-01

    Representation", Proc. ICASSP 2003, vol. I, pp.256-259, 2003. [4] Marrero, V. et al. "Identifying speaker-dependent acoustic parameters in Spanish vowels ...Meeting of the Acoustical Society of America, June 4-8, 2007 [8] Reynolds, D. A. “ Comparison of Background Normalization Methods for Text...improvements across disparate conditions. This paper demonstrates that acoustic perturbation, in this case analysis, distortion, and resynthesis of

  15. The study on normalization algorithm applied to the character recognition system

    Science.gov (United States)

    Wang, Jingzhong; Xu, Xiaoqing; Hu, Beibei

    2013-03-01

    In this paper, it's research hard on the normalization algorithm of image preprocessing. It proposes that normalize the size of a single character at first, and then thin this character, make an amendment to the framework image at last. Experimental results indicate that this method is validate and lays a solid foundation for consequence processing of the Chinese character recognition.

  16. IMPROVEMENT IN HANDWRITTEN NUMERAL STRING RECOGNITION BY SLANT NORMALIZATION AND CONTEXTUAL INFORMATION

    NARCIS (Netherlands)

    Britto jr., A. de S.; Sabourin, R.; Lethelier, E.; Bortolozzi, F.; Suen, C.Y.

    2004-01-01

    This work describes a way of enhancing handwritten numeral string recognition by considering slant normalization and contextual information to train an implicit segmentation­based system. A word slant normalization method is modified in order to improve the results for handwritten numeral strings.

  17. Glassfiber Post: An Alternative for Restoring Grossly Decayed Primary Incisors

    Science.gov (United States)

    Grover, Rashu

    2012-01-01

    ABSTRACT Restoration of primary incisors, which have been severely damaged by rampant caries or trauma, is a difficult task for the pediatric dentist. With the introduction of new adhesive systems and restorative materials, alternative approaches for treating these teeth have been proposed. This paper discusses the restoration of carious primary maxillary incisors using composite resin restoration reinforced with fiberglass post. Two case reports are presented here to describe the procedure. Over a 1 year period, the crowns have demonstrated good retention and esthetic results. How to cite this article: Mehra M, Grover R. Glassfiber Post: An Alternative for Restoring Grossly Decayed Primary Incisors. Int J Clin Pediatr Dent 2012;5(2):159-162. PMID:25206160

  18. Normal and abnormal category-effects in visual object recognition

    DEFF Research Database (Denmark)

    Gerlach, Christian

    2017-01-01

    Are all categories of objects recognized in the same manner visually? Evidence from neuropsychology suggests they are not, as some brain injured patients are more impaired in recognizing natural objects than artefacts while others show the opposite impairment. In an attempt to explain category......-specific deficits for natural objects Glyn Humphreys and colleagues suggested that natural objects are harder to perceptually differentiate than artefacts because natural objects are more structurally similar than artefacts. This explanation was proposed in the context of the Cascade model of visual object naming....... While this model has been successful in accounting for a number of observations concerning category-specificity in both patients with brain injury and normal subjects, it has also become clear that there are many important aspects of category-specificity that the model cannot accommodate...

  19. Mexican sign language recognition using normalized moments and artificial neural networks

    Science.gov (United States)

    Solís-V., J.-Francisco; Toxqui-Quitl, Carina; Martínez-Martínez, David; H.-G., Margarita

    2014-09-01

    This work presents a framework designed for the Mexican Sign Language (MSL) recognition. A data set was recorded with 24 static signs from the MSL using 5 different versions, this MSL dataset was captured using a digital camera in incoherent light conditions. Digital Image Processing was used to segment hand gestures, a uniform background was selected to avoid using gloved hands or some special markers. Feature extraction was performed by calculating normalized geometric moments of gray scaled signs, then an Artificial Neural Network performs the recognition using a 10-fold cross validation tested in weka, the best result achieved 95.83% of recognition rate.

  20. Automatic Mexican sign language and digits recognition using normalized central moments

    Science.gov (United States)

    Solís, Francisco; Martínez, David; Espinosa, Oscar; Toxqui, Carina

    2016-09-01

    This work presents a framework for automatic Mexican sign language and digits recognition based on computer vision system using normalized central moments and artificial neural networks. Images are captured by digital IP camera, four LED reflectors and a green background in order to reduce computational costs and prevent the use of special gloves. 42 normalized central moments are computed per frame and used in a Multi-Layer Perceptron to recognize each database. Four versions per sign and digit were used in training phase. 93% and 95% of recognition rates were achieved for Mexican sign language and digits respectively.

  1. Category Specificity in Normal Episodic Learning: Applications to Object Recognition and Category-Specific Agnosia

    Science.gov (United States)

    Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen

    2004-01-01

    Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…

  2. Audibility-based predictions of speech recognition for children and adults with normal hearing.

    Science.gov (United States)

    McCreery, Ryan W; Stelmachowicz, Patricia G

    2011-12-01

    This study investigated the relationship between audibility and predictions of speech recognition for children and adults with normal hearing. The Speech Intelligibility Index (SII) is used to quantify the audibility of speech signals and can be applied to transfer functions to predict speech recognition scores. Although the SII is used clinically with children, relatively few studies have evaluated SII predictions of children's speech recognition directly. Children have required more audibility than adults to reach maximum levels of speech understanding in previous studies. Furthermore, children may require greater bandwidth than adults for optimal speech understanding, which could influence frequency-importance functions used to calculate the SII. Speech recognition was measured for 116 children and 19 adults with normal hearing. Stimulus bandwidth and background noise level were varied systematically in order to evaluate speech recognition as predicted by the SII and derive frequency-importance functions for children and adults. Results suggested that children required greater audibility to reach the same level of speech understanding as adults. However, differences in performance between adults and children did not vary across frequency bands.

  3. Towards an Intelligent Acoustic Front End for Automatic Speech Recognition: Built-in Speaker Normalization

    Directory of Open Access Journals (Sweden)

    Umit H. Yapanel

    2008-08-01

    Full Text Available A proven method for achieving effective automatic speech recognition (ASR due to speaker differences is to perform acoustic feature speaker normalization. More effective speaker normalization methods are needed which require limited computing resources for real-time performance. The most popular speaker normalization technique is vocal-tract length normalization (VTLN, despite the fact that it is computationally expensive. In this study, we propose a novel online VTLN algorithm entitled built-in speaker normalization (BISN, where normalization is performed on-the-fly within a newly proposed PMVDR acoustic front end. The novel algorithm aspect is that in conventional frontend processing with PMVDR and VTLN, two separating warping phases are needed; while in the proposed BISN method only one single speaker dependent warp is used to achieve both the PMVDR perceptual warp and VTLN warp simultaneously. This improved integration unifies the nonlinear warping performed in the front end and reduces simultaneously. This improved integration unifies the nonlinear warping performed in the front end and reduces computational requirements, thereby offering advantages for real-time ASR systems. Evaluations are performed for (i an in-car extended digit recognition task, where an on-the-fly BISN implementation reduces the relative word error rate (WER by 24%, and (ii for a diverse noisy speech task (SPINE 2, where the relative WER improvement was 9%, both relative to the baseline speaker normalization method.

  4. Towards an Intelligent Acoustic Front End for Automatic Speech Recognition: Built-in Speaker Normalization

    Directory of Open Access Journals (Sweden)

    Yapanel UmitH

    2008-01-01

    Full Text Available A proven method for achieving effective automatic speech recognition (ASR due to speaker differences is to perform acoustic feature speaker normalization. More effective speaker normalization methods are needed which require limited computing resources for real-time performance. The most popular speaker normalization technique is vocal-tract length normalization (VTLN, despite the fact that it is computationally expensive. In this study, we propose a novel online VTLN algorithm entitled built-in speaker normalization (BISN, where normalization is performed on-the-fly within a newly proposed PMVDR acoustic front end. The novel algorithm aspect is that in conventional frontend processing with PMVDR and VTLN, two separating warping phases are needed; while in the proposed BISN method only one single speaker dependent warp is used to achieve both the PMVDR perceptual warp and VTLN warp simultaneously. This improved integration unifies the nonlinear warping performed in the front end and reduces simultaneously. This improved integration unifies the nonlinear warping performed in the front end and reduces computational requirements, thereby offering advantages for real-time ASR systems. Evaluations are performed for (i an in-car extended digit recognition task, where an on-the-fly BISN implementation reduces the relative word error rate (WER by 24%, and (ii for a diverse noisy speech task (SPINE 2, where the relative WER improvement was 9%, both relative to the baseline speaker normalization method.

  5. Intensity Variation Normalization for Finger Vein Recognition Using Guided Filter Based Singe Scale Retinex.

    Science.gov (United States)

    Xie, Shan Juan; Lu, Yu; Yoon, Sook; Yang, Jucheng; Park, Dong Sun

    2015-07-14

    Finger vein recognition has been considered one of the most promising biometrics for personal authentication. However, the capacities and percentages of finger tissues (e.g., bone, muscle, ligament, water, fat, etc.) vary person by person. This usually causes poor quality of finger vein images, therefore degrading the performance of finger vein recognition systems (FVRSs). In this paper, the intrinsic factors of finger tissue causing poor quality of finger vein images are analyzed, and an intensity variation (IV) normalization method using guided filter based single scale retinex (GFSSR) is proposed for finger vein image enhancement. The experimental results on two public datasets demonstrate the effectiveness of the proposed method in enhancing the image quality and finger vein recognition accuracy.

  6. Intensity Variation Normalization for Finger Vein Recognition Using Guided Filter Based Singe Scale Retinex

    Directory of Open Access Journals (Sweden)

    Shan Juan Xie

    2015-07-01

    Full Text Available Finger vein recognition has been considered one of the most promising biometrics for personal authentication. However, the capacities and percentages of finger tissues (e.g., bone, muscle, ligament, water, fat, etc. vary person by person. This usually causes poor quality of finger vein images, therefore degrading the performance of finger vein recognition systems (FVRSs. In this paper, the intrinsic factors of finger tissue causing poor quality of finger vein images are analyzed, and an intensity variation (IV normalization method using guided filter based single scale retinex (GFSSR is proposed for finger vein image enhancement. The experimental results on two public datasets demonstrate the effectiveness of the proposed method in enhancing the image quality and finger vein recognition accuracy.

  7. Trade off between variable and fixed size normalization in orthogonal polynomials based iris recognition system.

    Science.gov (United States)

    Krishnamoorthi, R; Anna Poorani, G

    2016-01-01

    Iris normalization is an important stage in any iris biometric, as it has a propensity to trim down the consequences of iris distortion. To indemnify the variation in size of the iris owing to the action of stretching or enlarging the pupil in iris acquisition process and camera to eyeball distance, two normalization schemes has been proposed in this work. In the first method, the iris region of interest is normalized by converting the iris into the variable size rectangular model in order to avoid the under samples near the limbus border. In the second method, the iris region of interest is normalized by converting the iris region into a fixed size rectangular model in order to avoid the dimensional discrepancies between the eye images. The performance of the proposed normalization methods is evaluated with orthogonal polynomials based iris recognition in terms of FAR, FRR, GAR, CRR and EER.

  8. Microscopic prediction of speech recognition for listeners with normal hearing in noise using an auditory model.

    Science.gov (United States)

    Jürgens, Tim; Brand, Thomas

    2009-11-01

    This study compares the phoneme recognition performance in speech-shaped noise of a microscopic model for speech recognition with the performance of normal-hearing listeners. "Microscopic" is defined in terms of this model twofold. First, the speech recognition rate is predicted on a phoneme-by-phoneme basis. Second, microscopic modeling means that the signal waveforms to be recognized are processed by mimicking elementary parts of human's auditory processing. The model is based on an approach by Holube and Kollmeier [J. Acoust. Soc. Am. 100, 1703-1716 (1996)] and consists of a psychoacoustically and physiologically motivated preprocessing and a simple dynamic-time-warp speech recognizer. The model is evaluated while presenting nonsense speech in a closed-set paradigm. Averaged phoneme recognition rates, specific phoneme recognition rates, and phoneme confusions are analyzed. The influence of different perceptual distance measures and of the model's a-priori knowledge is investigated. The results show that human performance can be predicted by this model using an optimal detector, i.e., identical speech waveforms for both training of the recognizer and testing. The best model performance is yielded by distance measures which focus mainly on small perceptual distances and neglect outliers.

  9. Recognition of Speech of Normal-hearing Individuals with Tinnitus and Hyperacusis

    Directory of Open Access Journals (Sweden)

    Hennig, Tais Regina

    2011-01-01

    Full Text Available Introduction: Tinnitus and hyperacusis are increasingly frequent audiological symptoms that may occur in the absence of the hearing involvement, but it does not offer a lower impact or bothering to the affected individuals. The Medial Olivocochlear System helps in the speech recognition in noise and may be connected to the presence of tinnitus and hyperacusis. Objective: To evaluate the speech recognition of normal-hearing individual with and without complaints of tinnitus and hyperacusis, and to compare their results. Method: Descriptive, prospective and cross-study in which 19 normal-hearing individuals were evaluated with complaint of tinnitus and hyperacusis of the Study Group (SG, and 23 normal-hearing individuals without audiological complaints of the Control Group (CG. The individuals of both groups were submitted to the test List of Sentences in Portuguese, prepared by Costa (1998 to determine the Sentences Recognition Threshold in Silence (LRSS and the signal to noise ratio (S/N. The SG also answered the Tinnitus Handicap Inventory for tinnitus analysis, and to characterize hyperacusis the discomfort thresholds were set. Results: The CG and SG presented with average LRSS and S/N ratio of 7.34 dB NA and -6.77 dB, and of 7.20 dB NA and -4.89 dB, respectively. Conclusion: The normal-hearing individuals with or without audiological complaints of tinnitus and hyperacusis had a similar performance in the speech recognition in silence, which was not the case when evaluated in the presence of competitive noise, since the SG had a lower performance in this communication scenario, with a statistically significant difference.

  10. [The effects of normal aging on face naming and recognition of famous people: battery 75].

    Science.gov (United States)

    Pluchon, C; Simonnet, E; Toullat, G; Gil, R

    2002-07-01

    The difficulty to recall proper nouns is often something elderly people complain about. Thus, we tried to build and standardize a tool that could allow a quantified estimation of the naming and recognition abilities about famous people faces, specifying the part of gender, age and cultural level for each kind of test. The performances of 542 subjects divided in 3 age brackets and 3 academic knowledge levels were analysed. To carry out the test material, the artistic team of the Grevin Museum (Paris) was called upon. Their work offers a homogeneous way to shape famous people faces. One same person thus photographed 75 characters from different social categories with the same conditions of light, during only one day. The results of the study show that men perform better than women as concerns naming task, but that there's no difference between genders as concerns recognition task. Recognition performances are significantly better whatever the age, the gender and the cultural level may be. Generally, performances are all the more better since subjects are younger and have a higher cultural level. Our study then confirms the fact that normal aging goes hand in hand with rising difficulties to name faces. Moreover, results tend to show that recognition of faces remains better preserved and that the greater disability to recall a name is linked to difficulties in lexical accessing.

  11. Lexical effects on spoken-word recognition in children with normal hearing.

    Science.gov (United States)

    Krull, Vidya; Choi, Sangsook; Kirk, Karen Iler; Prusick, Lindsay; French, Brian

    2010-02-01

    This study is the first in a series designed to develop and norm new theoretically motivated sentence tests for children. The purpose was to examine the independent contributions of word frequency (i.e., how often words occur in language) and lexical density (the number of similar sounding words or "neighbors" to a target word) to the perception of key words in the new sentence set. Twenty-four children with normal hearing aged 5 to 12 yrs served as participants; they were divided into four equal age-matched groups. The stimuli consisted of 100 semantically neutral sentences that were 5 to 7 words in length. Each sentence contained 3 key words that were controlled for word frequency and lexical density. Words with few neighbors come from sparse neighborhoods, whereas words with many neighbors come from dense neighborhoods. The key words within a sentence belonged to one of the four lexical categories: (1) high-frequency sparse, (2) low-frequency dense, (3) high-frequency dense, and (4) low-frequency sparse. Participants were administered the sentence list and the 300 key words in isolation at 65 dB SPL. Each participant group was tested in spectrally matched noise at one of the four signal-to-noise ratios (SNRs -2, 0, 2, and 4 dB). The percent of words correctly identified was calculated as a function of SNR, key word context (sentences vs. words), and key word lexical category. SNR had a significant effect on the recognition of key words in sentences and in isolation; performance improved at higher SNRs. There were significant main effects of word frequency and lexical density as well as a significant interaction between the two lexical factors. In isolation, high-frequency words were recognized more accurately than low-frequency words. In both word and sentence contexts, sparse words yielded greater accuracy than dense words, irrespective of word frequency. There was a modest but significant negative correlation between lexical density and the recognition of

  12. Voice emotion recognition by cochlear-implanted children and their normally-hearing peers.

    Science.gov (United States)

    Chatterjee, Monita; Zion, Danielle J; Deroche, Mickael L; Burianek, Brooke A; Limb, Charles J; Goren, Alison P; Kulkarni, Aditya M; Christensen, Julie A

    2015-04-01

    Despite their remarkable success in bringing spoken language to hearing impaired listeners, the signal transmitted through cochlear implants (CIs) remains impoverished in spectro-temporal fine structure. As a consequence, pitch-dominant information such as voice emotion, is diminished. For young children, the ability to correctly identify the mood/intent of the speaker (which may not always be visible in their facial expression) is an important aspect of social and linguistic development. Previous work in the field has shown that children with cochlear implants (cCI) have significant deficits in voice emotion recognition relative to their normally hearing peers (cNH). Here, we report on voice emotion recognition by a cohort of 36 school-aged cCI. Additionally, we provide for the first time, a comparison of their performance to that of cNH and NH adults (aNH) listening to CI simulations of the same stimuli. We also provide comparisons to the performance of adult listeners with CIs (aCI), most of whom learned language primarily through normal acoustic hearing. Results indicate that, despite strong variability, on average, cCI perform similarly to their adult counterparts; that both groups' mean performance is similar to aNHs' performance with 8-channel noise-vocoded speech; that cNH achieve excellent scores in voice emotion recognition with full-spectrum speech, but on average, show significantly poorer scores than aNH with 8-channel noise-vocoded speech. A strong developmental effect was observed in the cNH with noise-vocoded speech in this task. These results point to the considerable benefit obtained by cochlear-implanted children from their devices, but also underscore the need for further research and development in this important and neglected area. This article is part of a Special Issue entitled .

  13. Influence of tinnitus percentage index of speech recognition in patients with normal hearing

    Directory of Open Access Journals (Sweden)

    Urnau, Daila

    2010-12-01

    Full Text Available Introduction: The understanding of speech is one of the most important measurable aspects of human auditory function. Tinnitus affects the quality of life, impairing communication. Objective: To investigate possible changes in the Percentage Index of Speech Recognition (SDT in individuals with tinnitus have normal hearing and examining the relationship between tinnitus, gender and age. Methods:A retrospective study by analyzing the records of 82 individuals of both genders, aged 21-70 years, totaling 128 ears with normal hearing. The ears were analyzed separately, and divided into control group, no complaints of tinnitus and group study, with complaints of tinnitus. The variables gender and age groups and examined the influence of tinnitus in the SDT. It was considered normal, the percentage of 100% correct and changed, and the value between 88-96%. These criteria were adopted, since the percentage below 88% correct is found in individuals with sensorineural hearing loss. Results:There was no statistically significant difference between the variables age and tinnitus, and tinnitus SDT, only gender and tinnitus. The prevalence of tinnitus in females (56%, higher incidence of tinnitus in the age group 31-40 years (41.67% and fewer from 41 to 50 years (18.75% and on the SDT there was a greater percentage change in individuals with tinnitus (61.11%. Conclusion: The buzz does not interfere with SDT and there is no relationship between tinnitus and age, only between tinnitus and gender.

  14. When family looks strange and strangers look normal: a case of impaired face perception and recognition after stroke.

    Science.gov (United States)

    Heutink, Joost; Brouwer, Wiebo H; Kums, Evelien; Young, Andy; Bouma, Anke

    2012-02-01

    We describe a patient (JS) with impaired recognition and distorted visual perception of faces after an ischemic stroke. Strikingly, JS reports that the faces of family members look distorted, while faces of other people look normal. After neurological and neuropsychological examination, we assessed response accuracy, response times, and skin conductance responses on a face recognition task in which photographs of close family members, celebrities and unfamiliar people were presented. JS' performance was compared to the performance of three healthy control participants. Results indicate that three aspects of face perception appear to be impaired in JS. First, she has impaired recognition of basic emotional expressions. Second, JS has poor recognition of familiar faces in general, but recognition of close family members is disproportionally impaired compared to faces of celebrities. Third, JS perceives faces of family members as distorted. In this paper we consider whether these impairments can be interpreted in terms of previously described disorders of face perception and recent models for face perception.

  15. Comparing Facial Emotional Recognition in Patients with Borderline Personality Disorder and Patients with Schizotypal Personality Disorder with a Normal Group

    Directory of Open Access Journals (Sweden)

    Aida Farsham

    2017-04-01

    Full Text Available Objective: No research has been conducted on facial emotional recognition on patients with borderline personality disorder (BPD and schizotypal personality disorder (SPD. The present study aimed at comparing facial emotion recognition in these patients with the general population. The neurocognitive processing of emotions can show the pathologic style of these 2 disorders. Method:  Twenty BPD patients, 16 SPD patients, and 20 healthy individuals were selected by available sampling method. Structural Clinical Interview for Axis II, Millon Personality Inventory, Beck Depression Inventory and Facial Emotional Recognition Test was were conducted for all participants.Discussion: The results of one way ANOVA and Scheffe’s post hoc test analysis revealed significant differences in neuropsychology assessment of  facial emotional recognition between BPD and  SPD patients with normal group (p = 0/001. A significant difference was found in emotion recognition of fear between the 2 groups of BPD and normal population (p = 0/008. A significant difference was observed between SPD patients and control group in emotion recognition of wonder (p = 0/04(.The obtained results indicated a deficit in negative emotion recognition, especially disgust emotion, thus, it can be concluded that these patients have the same neurocognitive profile in the emotion domain.

  16. Prediction of consonant recognition in quiet for listeners with normal and impaired hearing using an auditory model.

    Science.gov (United States)

    Jürgens, Tim; Ewert, Stephan D; Kollmeier, Birger; Brand, Thomas

    2014-03-01

    Consonant recognition was assessed in normal-hearing (NH) and hearing-impaired (HI) listeners in quiet as a function of speech level using a nonsense logatome test. Average recognition scores were analyzed and compared to recognition scores of a speech recognition model. In contrast to commonly used spectral speech recognition models operating on long-term spectra, a "microscopic" model operating in the time domain was used. Variations of the model (accounting for hearing impairment) and different model parameters (reflecting cochlear compression) were tested. Using these model variations this study examined whether speech recognition performance in quiet is affected by changes in cochlear compression, namely, a linearization, which is often observed in HI listeners. Consonant recognition scores for HI listeners were poorer than for NH listeners. The model accurately predicted the speech reception thresholds of the NH and most HI listeners. A partial linearization of the cochlear compression in the auditory model, while keeping audibility constant, produced higher recognition scores and improved the prediction accuracy. However, including listener-specific information about the exact form of the cochlear compression did not improve the prediction further.

  17. Learning weighted sparse representation of encoded facial normal information for expression-robust 3D face recognition

    KAUST Repository

    Li, Huibin

    2011-10-01

    This paper proposes a novel approach for 3D face recognition by learning weighted sparse representation of encoded facial normal information. To comprehensively describe 3D facial surface, three components, in X, Y, and Z-plane respectively, of normal vector are encoded locally to their corresponding normal pattern histograms. They are finally fed to a sparse representation classifier enhanced by learning based spatial weights. Experimental results achieved on the FRGC v2.0 database prove that the proposed encoded normal information is much more discriminative than original normal information. Moreover, the patch based weights learned using the FRGC v1.0 and Bosphorus datasets also demonstrate the importance of each facial physical component for 3D face recognition. © 2011 IEEE.

  18. Speech intonation and melodic contour recognition in children with cochlear implants and with normal hearing.

    Science.gov (United States)

    See, Rachel L; Driscoll, Virginia D; Gfeller, Kate; Kliethermes, Stephanie; Oleson, Jacob

    2013-04-01

    Cochlear implant (CI) users have difficulty perceiving some intonation cues in speech and melodic contours because of poor frequency selectivity in the cochlear implant signal. To assess perceptual accuracy of normal hearing (NH) children and pediatric CI users on speech intonation (prosody), melodic contour, and pitch ranking, and to determine potential predictors of outcomes. Does perceptual accuracy for speech intonation or melodic contour differ as a function of auditory status (NH, CI), perceptual category (falling versus rising intonation/contour), pitch perception, or individual differences (e.g., age, hearing history)? NH and CI groups were tested on recognition of falling intonation/contour versus rising intonation/contour presented in both spoken and melodic (sung) conditions. Pitch ranking was also tested. Outcomes were correlated with variables of age, hearing history, HINT, and CNC scores. The CI group was significantly less accurate than the NH group in spoken (CI, M = 63.1%; NH, M = 82.1%) and melodic (CI, M = 61.6%; NH, M = 84.2%) conditions. The CI group was more accurate in recognizing rising contour in the melodic condition compared with rising intonation in the spoken condition. Pitch ranking was a significant predictor of outcome for both groups in falling intonation and rising melodic contour; age at testing and hearing history variables were not predictive of outcomes. Children with CIs were less accurate than NH children in perception of speech intonation, melodic contour, and pitch ranking. However, the larger pitch excursions of the melodic condition may assist in recognition of the rising inflection associated with the interrogative form.

  19. A LITERATURE SURVEY ON VARIOUS ILLUMINATION NORMALIZATION TECHNIQUES FOR FACE RECOGNITION WITH FUZZY K NEAREST NEIGHBOUR CLASSIFIER

    Directory of Open Access Journals (Sweden)

    A. Thamizharasi

    2015-05-01

    Full Text Available The face recognition is popular in video surveillance, social networks and criminal identifications nowadays. The performance of face recognition would be affected by variations in illumination, pose, aging and partial occlusion of face by Wearing Hats, scarves and glasses etc. The illumination variations are still the challenging problem in face recognition. The aim is to compare the various illumination normalization techniques. The illumination normalization techniques include: Log transformations, Power Law transformations, Histogram equalization, Adaptive histogram equalization, Contrast stretching, Retinex, Multi scale Retinex, Difference of Gaussian, DCT, DCT Normalization, DWT, Gradient face, Self Quotient, Multi scale Self Quotient and Homomorphic filter. The proposed work consists of three steps. First step is to preprocess the face image with the above illumination normalization techniques; second step is to create the train and test database from the preprocessed face images and third step is to recognize the face images using Fuzzy K nearest neighbor classifier. The face recognition accuracy of all preprocessing techniques is compared using the AR face database of color images.

  20. When family looks strange and strangers look normal : A case of impaired face perception and recognition after stroke

    NARCIS (Netherlands)

    Heutink, Joost; Brouwer, Wiebo H.; Kums, Evelien; Young, Andy; Bouma, Anke

    2012-01-01

    We describe a patient (JS) with impaired recognition and distorted visual perception of faces after an ischemic stroke. Strikingly, JS reports that the faces of family members look distorted, while faces of other people look normal. After neurological and neuropsychological examination, we assessed

  1. When family looks strange and strangers look normal : A case of impaired face perception and recognition after stroke

    NARCIS (Netherlands)

    Heutink, Joost; Brouwer, Wiebo H.; Kums, Evelien; Young, Andy; Bouma, Anke

    2012-01-01

    We describe a patient (JS) with impaired recognition and distorted visual perception of faces after an ischemic stroke. Strikingly, JS reports that the faces of family members look distorted, while faces of other people look normal. After neurological and neuropsychological examination, we assessed

  2. The Effects of Inter-Letter Spacing in Visual-Word Recognition: Evidence with Young Normal Readers and Developmental Dyslexics

    Science.gov (United States)

    Perea, Manuel; Panadero, Victoria; Moret-Tatay, Carmen; Gomez, Pablo

    2012-01-01

    Recent research has demonstrated that slight increases of inter-letter spacing have a positive impact on skilled readers' recognition of visually presented words. In the present study, we examined whether this effect generalises to young normal readers and readers with developmental dyslexia, and whether increased inter-letter spacing affects the…

  3. Pattern-recognition system, designed on GPU, for discriminating between injured normal and pathological knee cartilage.

    Science.gov (United States)

    Kostopoulos, Spiros; Sidiropoulos, Konstantinos; Glotsos, Dimitris; Athanasiadis, Emmanouil; Boutsikou, Konstantina; Lavdas, Eleftherios; Oikonomou, Georgia; Fezoulidis, Ioannis V; Vlychou, Marianna; Hantes, Michael; Cavouras, Dionisis

    2013-06-01

    The aim was to design a pattern-recognition (PR) system for discriminating between normal and pathological knee articular cartilage of the medial femoral (MFC) and tibial condyles (MTC). The data set comprised segmented regions of interest (ROIs) from coronal and sagittal 3-T magnetic resonance images of the MFC and MTC cartilage of young patients, 28 with abnormality-free knee and 16 with pathological findings. The PR system was designed employing the probabilistic neural network classifier, textural features from the segmented ROIs and the leave-one-out evaluation method, while the PR system's precision to "unseen" data was assessed by employing the external cross-validation method. Optimal system design was accomplished on a consumer graphics processing unit (GPU) using Compute Unified Device Architecture parallel programming. PR system design on the GPU required about 3.5 min against 15 h on a CPU-based system. Highest classification accuracies for the MFC and MTC cartilages were 93.2% and 95.5%, and accuracies to "unseen" data were 89% and 86%, respectively. The proposed PR system is housed in a PC, equipped with a consumer GPU, and it may be easily retrained when new verified data are incorporated in its repository and may be of value as a second-opinion tool in a clinical environment.

  4. NCBI disease corpus: a resource for disease name recognition and concept normalization.

    Science.gov (United States)

    Doğan, Rezarta Islamaj; Leaman, Robert; Lu, Zhiyong

    2014-02-01

    knowledge-based disease normalization methods with a best performance in F-measure of 63.7%. These results show that the NCBI disease corpus has the potential to significantly improve the state-of-the-art in disease name recognition and normalization research, by providing a high-quality gold standard thus enabling the development of machine-learning based approaches for such tasks. The NCBI disease corpus, guidelines and other associated resources are available at: http://www.ncbi.nlm.nih.gov/CBBresearch/Dogan/DISEASE/.

  5. Local Illumination Normalization and Facial Feature Point Selection for Robust Face Recognition

    Directory of Open Access Journals (Sweden)

    Song HAN

    2013-03-01

    Full Text Available Face recognition systems must be robust to the variation of various factors such as facial expression, illumination, head pose and aging. Especially, the robustness against illumination variation is one of the most important problems to be solved for the practical use of face recognition systems. Gabor wavelet is widely used in face detection and recognition because it gives the possibility to simulate the function of human visual system. In this paper, we propose a method for extracting Gabor wavelet features which is stable under the variation of local illumination and show experiment results demonstrating its effectiveness.

  6. Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearinga)

    Science.gov (United States)

    Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

    2015-01-01

    Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes. PMID:26233047

  7. Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearing.

    Science.gov (United States)

    Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

    2015-07-01

    Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes.

  8. NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition

    Directory of Open Access Journals (Sweden)

    Hung Hsieh-Chuan

    2006-12-01

    Full Text Available Abstract Background Biomedical named entity recognition (Bio-NER is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized and at least one class tag (e.g., B-protein, the beginning of a protein name. However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., "2" in the biomedical term IL2 cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target word's closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words. We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing. Results To develop our ML

  9. Intensity Variation Normalization for Finger Vein Recognition Using Guided Filter Based Singe Scale Retinex

    OpenAIRE

    Shan Juan Xie; Yu Lu; Sook Yoon; Jucheng Yang; Dong Sun Park

    2015-01-01

    Finger vein recognition has been considered one of the most promising biometrics for personal authentication. However, the capacities and percentages of finger tissues (e.g., bone, muscle, ligament, water, fat, etc.) vary person by person. This usually causes poor quality of finger vein images, therefore degrading the performance of finger vein recognition systems (FVRSs). In this paper, the intrinsic factors of finger tissue causing poor quality of finger vein images are analyzed, and an int...

  10. Wavelet-based automatic cry recognition system for detecting infants with hearing-loss from normal infants

    Directory of Open Access Journals (Sweden)

    Mahmoud Mansouri Jam

    2013-11-01

    Full Text Available Infant cry is a multimodal and dynamic behaviour that it contains a lot of information. Goal of this investigation is recognition of two groups of infants by new acoustic feature that has not used in infant cry classification. The cry of deaf infants and normal hearing infants is studied. ‘Mel filter-bank discrete wavelet coefficients (MFDWCs’ have been extracted as feature vector. Infant cry classification is a pattern recognition problem such as ‘automatic speech recognition’, which in signal processing stage the authors performed some pre-processing included silence elimination, filtering, pre-emphasising and, segmentation. After applying the discrete wavelet transform on the Mel scaled log filter bank energies of a cry signal frames, MFDWCs feature vector was extracted. The feature vector, MFDWCs, of each cry sample has large length, so they used principle components analysis to reduce in feature space dimension, after training of neural network as classifier, they achieved to 93.2% correction rate in cry recognition of test data set. This result shows better efficiency in comparison with previous familiarised approaches.

  11. A New IRIS Normalization Process For Recognition System With Cryptographic Techniques

    CERN Document Server

    Nithyanandam, S; Priyadarshini, P L K

    2011-01-01

    Biometric technologies are the foundation of personal identification systems. It provides an identification based on a unique feature possessed by the individual. This paper provides a walkthrough for image acquisition, segmentation, normalization, feature extraction and matching based on the Human Iris imaging. A Canny Edge Detection scheme and a Circular Hough Transform, is used to detect the iris boundaries in the eye's digital image. The extracted IRIS region was normalized by using Image Registration technique. A phase correlation base method is used for this iris image registration purpose. The features of the iris region is encoded by convolving the normalized iris region with 2D Gabor filter. Hamming distance measurement is used to compare the quantized vectors and authenticate the users. To improve the security, Reed-Solomon technique is employed directly to encrypt and decrypt the data. Experimental results show that our system is quite effective and provides encouraging performance. Keywords: Biome...

  12. A New IRIS Normalization Process For Recognition System With Cryptographic Techniques

    Directory of Open Access Journals (Sweden)

    S Nithyanandam

    2011-07-01

    Full Text Available Biometric technologies are the foundation of personal identification systems. It provides an identification based on a unique feature possessed by the individual. This paper provides a walkthrough for image acquisition, segmentation, normalization, feature extraction and matching based on the Human Iris imaging. A Canny Edge Detection scheme and a Circular Hough Transform, is used to detect the iris boundaries in the eye's digital image. The extracted IRIS region was normalized by using Image Registration technique. A phase correlation base method is used for this iris image registration purpose. The features of the iris region is encoded by convolving the normalized iris region with 2D Gabor filter. Hamming distance measurement is used to compare the quantized vectors and authenticate the users. To improve the security, Reed-Solomon technique is employed directly to encrypt and decrypt the data. Experimental results show that our system is quite effective and provides encouraging performance.

  13. Speech recognition with dynamic range reduction: (1) deaf and normal subjects in laboratory conditions.

    Science.gov (United States)

    Drysdale, A E; Gregory, R L

    1978-08-01

    Processing to reduce the dynamic range of speech should increase intelligibility and protect the impaired ear from overloading. There are theoretical and practical objections to using AGC devices to reduce dynamic range. These are overcome by using recently available signal processing employing high frequency carrier clipping. An increase in intelligibility of speech with this HFCC has been demonstrated, for normal subjects with simulated deafness, and for most partially hearing patients. Intelligibility is not improved for some patients; possibly due to their having learned to extract features which are lost. These patients may also benefit after training.

  14. Intermodal timing relations and audio-visual speech recognition by normal-hearing adults.

    Science.gov (United States)

    McGrath, M; Summerfield, Q

    1985-02-01

    Audio-visual identification of sentences was measured as a function of audio delay in untrained observers with normal hearing; the soundtrack was replaced by rectangular pulses originally synchronized to the closing of the talker's vocal folds and then subjected to delay. When the soundtrack was delayed by 160 ms, identification scores were no better than when no acoustical information at all was provided. Delays of up to 80 ms had little effect on group-mean performance, but a separate analysis of a subgroup of better lipreaders showed a significant trend of reduced scores with increased delay in the range from 0-80 ms. A second experiment tested the interpretation that, although the main disruptive effect of the delay occurred on a syllabic time scale, better lipreaders might be attempting to use intermodal timing cues at a phonemic level. Normal-hearing observers determined whether a 120-Hz complex tone started before or after the opening of a pair of liplike Lissajou figures. Group-mean difference limens (70.7% correct DLs) were - 79 ms (sound leading) and + 138 ms (sound lagging), with no significant correlation between DLs and sentence lipreading scores. It was concluded that most observers, whether good lipreaders or not, possess insufficient sensitivity to intermodal timing cues in audio-visual speech for them to be used analogously to voice onset time in auditory speech perception. The results of both experiments imply that delays of up to about 40 ms introduced by signal-processing algorithms in aids to lipreading should not materially affect audio-visual speech understanding.

  15. Effect of Speaking Rate on Recognition of Synthetic and Natural Speech by Normal-Hearing and Cochlear Implant Listeners

    Science.gov (United States)

    Ji, Caili; Galvin, John J.; Xu, Anting; Fu, Qian-Jie

    2012-01-01

    Objective Most studies have evaluated cochlear implant (CI) performance using “clear” speech materials, which are highly intelligible and well-articulated. CI users may encounter much greater variability in speech patterns in the “real-world,” including synthetic speech. In this study, we measured normal-hearing (NH) and CI listeners’ sentence recognition with multiple talkers and speaking rates, and with naturally produced and synthetic speech. Design NH and CI subjects were asked to recognize naturally produced or synthetic sentences, presented at a slow, normal, or fast speaking rate. Natural speech was produced by one male and one female talker; synthetic speech was generated to simulate a male and female talker. For natural speech, the speaking rate was time-scaled while preserving voice pitch and formant frequency information. For synthetic speech, the speaking rate was adjusted within the speech synthesis engine. NH subjects were tested while listening to unprocessed speech or to an 8-channel acoustic CI simulation. CI subjects were tested while listening with their clinical processors and the recommended microphone sensitivity and volume settings. Results The NH group performed significantly better than the CI simulation group, and the CI simulation group performed significantly better than the CI group. For all subject groups, sentence recognition was significantly better with natural than with synthetic speech. The performance deficit with synthetic speech was relatively small for NH subjects listening to unprocessed speech. However, the performance deficit with synthetic speech was much greater for CI subjects and for CI simulation subjects. There was significant effect of talker gender, with slightly better performance with the female talker for CI subjects and slightly better performance with the male talker for the CI simulations. For all subject groups, sentence recognition was significantly poorer only at the fast rate. CI performance was

  16. Spin Dynamics Simulations of Multiple Echo Spacing Pulse Sequences in Grossly Inhomogeneous Fields

    Science.gov (United States)

    Heidler, R.; Bachman, H. N.; Johansen, Y.

    2008-12-01

    Pulse sequences with multiple lengths of echo spacings are used in oilfield NMR logging for diffusion-based NMR applications such as rock and fluid characterization. One specific implementation is the so-called diffusion editing sequence comprising two long echo spacings followed by a standard CPMG at a shorter echo spacing. The echoes in the CPMG portion contain signal from both the direct and stimulated echoes. Modern oilfield NMR logging tools are designed for continuous depth logging of earth formations by projecting both the static (B0) and dynamic (B1) fields into the formation. Both B0 and B1 profiles are grossly inhomogeneous which results in non-steady-state behavior in the early echoes. The spin dynamics effects present a challenge for processing the echo amplitudes to measure porosity (amplitude extrapolated to zero time) and attenuations for fluid or pore size characterization. In this work we describe a calculation of the spin dynamics of the diffusion editing sequence with two long echo spacings. The calculation takes into account full B1 and B0 field maps, and comparisons will be made for sensors and parameters typical of oilfield logging tools and environments.

  17. Revisiting vocal perception in non-human animals: a review of vowel discrimination, speaker voice recognition, and speaker normalization

    Directory of Open Access Journals (Sweden)

    Buddhamas eKriengwatana

    2015-01-01

    Full Text Available The extent to which human speech perception evolved by taking advantage of predispositions and pre-existing features of vertebrate auditory and cognitive systems remains a central question in the evolution of speech. This paper reviews asymmetries in vowel perception, speaker voice recognition, and speaker normalization in non-human animals – topics that have not been thoroughly discussed in relation to the abilities of non-human animals, but are nonetheless important aspects of vocal perception. Throughout this paper we demonstrate that addressing these issues in non-human animals is relevant and worthwhile because many non-human animals must deal with similar issues in their natural environment. That is, they must also discriminate between similar-sounding vocalizations, determine signaler identity from vocalizations, and resolve signaler-dependent variation in vocalizations from conspecifics. Overall, we find that, although plausible, the current evidence is insufficiently strong to conclude that directional asymmetries in vowel perception are specific to humans, or that non-human animals can use voice characteristics to recognize human individuals. However, we do find some indication that non-human animals can normalize speaker differences. Accordingly, we identify avenues for future research that would greatly improve and advance our understanding of these topics.

  18. Seabird bycatch in pelagic longline fisheries is grossly underestimated when using only haul data.

    Directory of Open Access Journals (Sweden)

    Nigel Brothers

    Full Text Available Hundreds of thousands of seabirds are killed each year as bycatch in longline fisheries. Seabirds are predominantly caught during line setting but bycatch is generally recorded during line hauling, many hours after birds are caught. Bird loss during this interval may lead to inaccurate bycatch information. In this 15 year study, seabird bycatch was recorded during both line setting and line hauling from four fishing regions: Indian Ocean, Southern Ocean, Coral Sea and central Pacific Ocean. Over 43,000 albatrosses, petrels and skuas representing over 25 species were counted during line setting of which almost 6,000 seabirds attempted to take the bait. Bait-taking interactions were placed into one of four categories. (i The majority (57% of bait-taking attempts were "unsuccessful" involving seabirds that did not take the bait nor get caught or hooked. (ii One-third of attempts were "successful" with seabirds removing the bait while not getting caught. (iii One-hundred and seventy-six seabirds (3% of attempts were observed being "caught" during line setting, with three albatross species - Laysan (Phoebastria immutabilis, black-footed (P. nigripes and black-browed (Thalassarche melanophrys- dominating this category. However, of these, only 85 (48% seabird carcasses were retrieved during line hauling. Most caught seabirds were hooked through the bill. (iv The remainder of seabird-bait interactions (7% was not clearly observed, but likely involved more "caught" seabirds. Bait taking attempts and percentage outcome (e.g. successful, caught varied between seabird species and was not always related to species abundance around fishing vessels. Using only haul data to calculate seabird bycatch grossly underestimates actual bycatch levels, with the level of seabird bycatch from pelagic longline fishing possibly double what was previously thought.

  19. Seabird bycatch in pelagic longline fisheries is grossly underestimated when using only haul data.

    Science.gov (United States)

    Brothers, Nigel; Duckworth, Alan R; Safina, Carl; Gilman, Eric L

    2010-08-31

    Hundreds of thousands of seabirds are killed each year as bycatch in longline fisheries. Seabirds are predominantly caught during line setting but bycatch is generally recorded during line hauling, many hours after birds are caught. Bird loss during this interval may lead to inaccurate bycatch information. In this 15 year study, seabird bycatch was recorded during both line setting and line hauling from four fishing regions: Indian Ocean, Southern Ocean, Coral Sea and central Pacific Ocean. Over 43,000 albatrosses, petrels and skuas representing over 25 species were counted during line setting of which almost 6,000 seabirds attempted to take the bait. Bait-taking interactions were placed into one of four categories. (i) The majority (57%) of bait-taking attempts were "unsuccessful" involving seabirds that did not take the bait nor get caught or hooked. (ii) One-third of attempts were "successful" with seabirds removing the bait while not getting caught. (iii) One-hundred and seventy-six seabirds (3% of attempts) were observed being "caught" during line setting, with three albatross species - Laysan (Phoebastria immutabilis), black-footed (P. nigripes) and black-browed (Thalassarche melanophrys)- dominating this category. However, of these, only 85 (48%) seabird carcasses were retrieved during line hauling. Most caught seabirds were hooked through the bill. (iv) The remainder of seabird-bait interactions (7%) was not clearly observed, but likely involved more "caught" seabirds. Bait taking attempts and percentage outcome (e.g. successful, caught) varied between seabird species and was not always related to species abundance around fishing vessels. Using only haul data to calculate seabird bycatch grossly underestimates actual bycatch levels, with the level of seabird bycatch from pelagic longline fishing possibly double what was previously thought.

  20. Mice deficient for striatal Vesicular Acetylcholine Transporter (VAChT) display impaired short-term but normal long-term object recognition memory.

    Science.gov (United States)

    Palmer, Daniel; Creighton, Samantha; Prado, Vania F; Prado, Marco A M; Choleris, Elena; Winters, Boyer D

    2016-09-15

    Substantial evidence implicates Acetylcholine (ACh) in the acquisition of object memories. While most research has focused on the role of the cholinergic basal forebrain and its cortical targets, there are additional cholinergic networks that may contribute to object recognition. The striatum contains an independent cholinergic network comprised of interneurons. In the current study, we investigated the role of this cholinergic signalling in object recognition using mice deficient for Vesicular Acetylcholine Transporter (VAChT) within interneurons of the striatum. We tested whether these striatal VAChT(D2-Cre-flox/flox) mice would display normal short-term (5 or 15min retention delay) and long-term (3h retention delay) object recognition memory. In a home cage object recognition task, male and female VAChT(D2-Cre-flox/flox) mice were impaired selectively with a 15min retention delay. When tested on an object location task, VAChT(D2-Cre-flox/flox) mice displayed intact spatial memory. Finally, when object recognition was tested in a Y-shaped apparatus, designed to minimize the influence of spatial and contextual cues, only females displayed impaired recognition with a 5min retention delay, but when males were challenged with a 15min retention delay, they were also impaired; neither males nor females were impaired with the 3h delay. The pattern of results suggests that striatal cholinergic transmission plays a role in the short-term memory for object features, but not spatial location.

  1. Brain catechol-O-methyltransferase (COMT) inhibition by tolcapone counteracts recognition memory deficits in normal and chronic phencyclidine-treated rats and in COMT-Val transgenic mice.

    Science.gov (United States)

    Detrait, Eric R; Carr, Greg V; Weinberger, Daniel R; Lamberty, Yves

    2016-08-01

    The critical involvement of dopamine in cognitive processes has been well established, suggesting that therapies targeting dopamine metabolism may alleviate cognitive dysfunction. Catechol-O-methyl transferase (COMT) is a catecholamine-degrading enzyme, the substrates of which include dopamine, epinephrine, and norepinephrine. The present work illustrates the potential therapeutic efficacy of COMT inhibition in alleviating cognitive impairment. A brain-penetrant COMT inhibitor, tolcapone, was tested in normal and phencyclidine-treated rats and COMT-Val transgenic mice. In a novel object recognition procedure, tolcapone counteracted a 24-h-dependent forgetting of a familiar object as well as phencyclidine-induced recognition deficits in the rats at doses ranging from 7.5 to 30 mg/kg. In contrast, entacapone, a COMT inhibitor that does not readily cross the blood-brain barrier, failed to show efficacy at doses up to 30 mg/kg. Tolcapone at a dose of 30 mg/kg also improved novel object recognition performance in transgenic mice, which showed clear recognition deficits. Complementing earlier studies, our results indicate that central inhibition of COMT positively impacts recognition memory processes and might constitute an appealing treatment for cognitive dysfunction related to neuropsychiatric disorders.

  2. Expression-robust 3D face recognition via weighted sparse representation of multi-scale and multi-component local normal patterns

    KAUST Repository

    Li, Huibin

    2014-06-01

    In the theory of differential geometry, surface normal, as a first order surface differential quantity, determines the orientation of a surface at each point and contains informative local surface shape information. To fully exploit this kind of information for 3D face recognition (FR), this paper proposes a novel highly discriminative facial shape descriptor, namely multi-scale and multi-component local normal patterns (MSMC-LNP). Given a normalized facial range image, three components of normal vectors are first estimated, leading to three normal component images. Then, each normal component image is encoded locally to local normal patterns (LNP) on different scales. To utilize spatial information of facial shape, each normal component image is divided into several patches, and their LNP histograms are computed and concatenated according to the facial configuration. Finally, each original facial surface is represented by a set of LNP histograms including both global and local cues. Moreover, to make the proposed solution robust to the variations of facial expressions, we propose to learn the weight of each local patch on a given encoding scale and normal component image. Based on the learned weights and the weighted LNP histograms, we formulate a weighted sparse representation-based classifier (W-SRC). In contrast to the overwhelming majority of 3D FR approaches which were only benchmarked on the FRGC v2.0 database, we carried out extensive experiments on the FRGC v2.0, Bosphorus, BU-3DFE and 3D-TEC databases, thus including 3D face data captured in different scenarios through various sensors and depicting in particular different challenges with respect to facial expressions. The experimental results show that the proposed approach consistently achieves competitive rank-one recognition rates on these databases despite their heterogeneous nature, and thereby demonstrates its effectiveness and its generalizability. © 2014 Elsevier B.V.

  3. Wire-guided (Seldinger technique intubation through a face mask in urgent, difficult and grossly distorted airways

    Directory of Open Access Journals (Sweden)

    Jake M Heier

    2012-01-01

    Full Text Available We report two cases of successful urgent intubation using a Seldinger technique for airway management through an anesthesia facemask, while maintaining ventilation in patients with difficult airways and grossly distorted airway anatomy. In both cases, conventional airway management techniques were predicted to be difficult or impossible, and a high likelihood for a surgical airway was present. This technique was chosen as it allows tracheal tube placement through the nares during spontaneous ventilation with the airway stented open and oxygen delivery with either continuous positive airway pressure and/or pressure support ventilation. This unhurried technique may allow intubation when other techniques are unsuitable, while maintaining control of the airway.

  4. Wire-guided (Seldinger technique) intubation through a face mask in urgent, difficult and grossly distorted airways.

    Science.gov (United States)

    Heier, Jake M; Schroeder, Kristopher M; Galgon, Richard E; Arndt, George A

    2012-07-01

    We report two cases of successful urgent intubation using a Seldinger technique for airway management through an anesthesia facemask, while maintaining ventilation in patients with difficult airways and grossly distorted airway anatomy. In both cases, conventional airway management techniques were predicted to be difficult or impossible, and a high likelihood for a surgical airway was present. This technique was chosen as it allows tracheal tube placement through the nares during spontaneous ventilation with the airway stented open and oxygen delivery with either continuous positive airway pressure and/or pressure support ventilation. This unhurried technique may allow intubation when other techniques are unsuitable, while maintaining control of the airway.

  5. The Effects of Musical and Linguistic Components in Recognition of Real-World Musical Excerpts by Cochlear Implant Recipients and Normal-Hearing Adults

    Science.gov (United States)

    Gfeller, Kate; Jiang, Dingfeng; Oleson, Jacob; Driscoll, Virginia; Olszewski, Carol; Knutson, John F.; Turner, Christopher; Gantz, Bruce

    2011-01-01

    Background Cochlear implants (CI) are effective in transmitting salient features of speech, especially in quiet, but current CI technology is not well suited in transmission of key musical structures (e.g., melody, timbre). It is possible, however, that sung lyrics, which are commonly heard in real-world music may provide acoustical cues that support better music perception. Objective The purpose of this study was to examine how accurately adults who use CIs (n=87) and those with normal hearing (NH) (n=17) are able to recognize real-world music excerpts based upon musical and linguistic (lyrics) cues. Results CI recipients were significantly less accurate than NH listeners on recognition of real-world music with or, in particular, without lyrics; however, CI recipients whose devices transmitted acoustic plus electric stimulation were more accurate than CI recipients reliant upon electric stimulation alone (particularly items without linguistic cues). Recognition by CI recipients improved as a function of linguistic cues. Methods Participants were tested on melody recognition of complex melodies (pop, country, classical styles). Results were analyzed as a function of: hearing status and history, device type (electric only or acoustic plus electric stimulation), musical style, linguistic and musical cues, speech perception scores, cognitive processing, music background, age, and in relation to self-report on listening acuity and enjoyment. Age at time of testing was negatively correlated with recognition performance. Conclusions These results have practical implications regarding successful participation of CI users in music-based activities that include recognition and accurate perception of real-world songs (e.g., reminiscence, lyric analysis, listening for enjoyment). PMID:22803258

  6. The effects of musical and linguistic components in recognition of real-world musical excerpts by cochlear implant recipients and normal-hearing adults.

    Science.gov (United States)

    Gfeller, Kate; Jiang, Dingfeng; Oleson, Jacob J; Driscoll, Virginia; Olszewski, Carol; Knutson, John F; Turner, Christopher; Gantz, Bruce

    2012-01-01

    Cochlear implants (CI) are effective in transmitting salient features of speech, especially in quiet, but current CI technology is not well suited in transmission of key musical structures (e.g., melody, timbre). It is possible, however, that sung lyrics, which are commonly heard in real-world music may provide acoustical cues that support better music perception. The purpose of this study was to examine how accurately adults who use CIs (n = 87) and those with normal hearing (NH) (n = 17) are able to recognize real-world music excerpts based upon musical and linguistic (lyrics) cues. CI recipients were significantly less accurate than NH listeners on recognition of real-world music with or, in particular, without lyrics; however, CI recipients whose devices transmitted acoustic plus electric stimulation were more accurate than CI recipients reliant upon electric stimulation alone (particularly items without linguistic cues). Recognition by CI recipients improved as a function of linguistic cues. Participants were tested on melody recognition of complex melodies (pop, country, & classical styles). Results were analyzed as a function of: hearing status and history, device type (electric only or acoustic plus electric stimulation), musical style, linguistic and musical cues, speech perception scores, cognitive processing, music background, age, and in relation to self-report on listening acuity and enjoyment. Age at time of testing was negatively correlated with recognition performance. These results have practical implications regarding successful participation of CI users in music-based activities that include recognition and accurate perception of real-world songs (e.g., reminiscence, lyric analysis, & listening for enjoyment).

  7. Empathy and recognition of facial expressions of emotion in sex offenders, non-sex offenders and normal controls.

    Science.gov (United States)

    Gery, Isabelle; Miljkovitch, Raphaële; Berthoz, Sylvie; Soussignan, Robert

    2009-02-28

    Research conducted on empathy and emotional recognition in sex offenders is contradictory. The present study was aimed to clarify this issue by controlling for some affective and social variables (depression, anxiety, and social desirability) that are presumed to influence emotional and empathic measures, using a staged multicomponent model of empathy. Incarcerated sex offenders (child molesters), incarcerated non-sex offenders, and non-offender controls (matched for age, gender, and education level) performed a recognition task of facial expressions of basic emotions that varied in intensity, and completed various self-rating scales designed to assess distinct components of empathy (perspective taking, affective empathy, empathy concern, and personal distress), as well as depression, anxiety, and social desirability. Sex offenders were less accurate than the other participants in recognizing facial expressions of anger, disgust, surprise and fear, with problems in confusing fear with surprise, and disgust with anger. Affective empathy was the only component that discriminated sex offenders from non-sex offenders and was correlated with accuracy recognition of emotional expressions. Although our findings must be replicated with a larger number of participants, they support the view that sex offenders might have impairments in the decoding of some emotional cues conveyed by the conspecifics' face, which could have an impact on affective empathy.

  8. Automated robust registration of grossly misregistered whole-slide images with varying stains

    Science.gov (United States)

    Litjens, G.; Safferling, K.; Grabe, N.

    2016-03-01

    Cancer diagnosis and pharmaceutical research increasingly depend on the accurate quantification of cancer biomarkers. Identification of biomarkers is usually performed through immunohistochemical staining of cancer sections on glass slides. However, combination of multiple biomarkers from a wide variety of immunohistochemically stained slides is a tedious process in traditional histopathology due to the switching of glass slides and re-identification of regions of interest by pathologists. Digital pathology now allows us to apply image registration algorithms to digitized whole-slides to align the differing immunohistochemical stains automatically. However, registration algorithms need to be robust to changes in color due to differing stains and severe changes in tissue content between slides. In this work we developed a robust registration methodology to allow for fast coarse alignment of multiple immunohistochemical stains to the base hematyoxylin and eosin stained image. We applied HSD color model conversion to obtain a less stain color dependent representation of the whole-slide images. Subsequently, optical density thresholding and connected component analysis were used to identify the relevant regions for registration. Template matching using normalized mutual information was applied to provide initial translation and rotation parameters, after which a cost function-driven affine registration was performed. The algorithm was validated using 40 slides from 10 prostate cancer patients, with landmark registration error as a metric. Median landmark registration error was around 180 microns, which indicates performance is adequate for practical application. None of the registrations failed, indicating the robustness of the algorithm.

  9. Deficits in audiovisual speech perception in normal aging emerge at the level of whole-word recognition.

    Science.gov (United States)

    Stevenson, Ryan A; Nelms, Caitlin E; Baum, Sarah H; Zurkovsky, Lilia; Barense, Morgan D; Newhouse, Paul A; Wallace, Mark T

    2015-01-01

    Over the next 2 decades, a dramatic shift in the demographics of society will take place, with a rapid growth in the population of older adults. One of the most common complaints with healthy aging is a decreased ability to successfully perceive speech, particularly in noisy environments. In such noisy environments, the presence of visual speech cues (i.e., lip movements) provide striking benefits for speech perception and comprehension, but previous research suggests that older adults gain less from such audiovisual integration than their younger peers. To determine at what processing level these behavioral differences arise in healthy-aging populations, we administered a speech-in-noise task to younger and older adults. We compared the perceptual benefits of having speech information available in both the auditory and visual modalities and examined both phoneme and whole-word recognition across varying levels of signal-to-noise ratio. For whole-word recognition, older adults relative to younger adults showed greater multisensory gains at intermediate SNRs but reduced benefit at low SNRs. By contrast, at the phoneme level both younger and older adults showed approximately equivalent increases in multisensory gain as signal-to-noise ratio decreased. Collectively, the results provide important insights into both the similarities and differences in how older and younger adults integrate auditory and visual speech cues in noisy environments and help explain some of the conflicting findings in previous studies of multisensory speech perception in healthy aging. These novel findings suggest that audiovisual processing is intact at more elementary levels of speech perception in healthy-aging populations and that deficits begin to emerge only at the more complex word-recognition level of speech signals. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Deficits in audiovisual speech perception in normal aging emerge at the level of whole-word recognition

    Science.gov (United States)

    Stevenson, Ryan A.; Nelms, Caitlin; Baum, Sarah H.; Zurkovsky, Lilia; Barense, Morgan D.; Newhouse, Paul A.; Wallace, Mark T.

    2014-01-01

    Over the next two decades, a dramatic shift in the demographics of society will take place, with a rapid growth in the population of older adults. One of the most common complaints with healthy aging is a decreased ability to successfully perceive speech, particularly in noisy environments. In such noisy environments, the presence of visual speech cues (i.e., lip movements) provide striking benefits for speech perception and comprehension, but previous research suggests that older adults gain less from such audiovisual integration than their younger peers. To determine at what processing level these behavioral differences arise in healthy-aging populations, we administered a speech-in-noise task to younger and older adults. We compared the perceptual benefits of having speech information available in both the auditory and visual modalities and examined both phoneme and whole-word recognition across varying levels of signal-to-noise ratio (SNR). For whole-word recognition, older relative to younger adults showed greater multisensory gains at intermediate SNRs, but reduced benefit at low SNRs. By contrast, at the phoneme level both younger and older adults showed approximately equivalent increases in multisensory gain as SNR decreased. Collectively, the results provide important insights into both the similarities and differences in how older and younger adults integrate auditory and visual speech cues in noisy environments, and help explain some of the conflicting findings in previous studies of multisensory speech perception in healthy aging. These novel findings suggest that audiovisual processing is intact at more elementary levels of speech perception in healthy aging populations, and that deficits begin to emerge only at the more complex, word-recognition level of speech signals. PMID:25282337

  11. Spatial distribution of grossly visible diseases and parasites in flounder ( Platichthys flesus ) from the Baltic Sea : a synoptic survey

    DEFF Research Database (Denmark)

    Lang, T.; Mellergaard, Stig; Wosniok, W.;

    1999-01-01

    for lymphocystis (14.4%) and acute/healing stages of the skin ulcer disease (5.9%). The prevalences of liver neoplasms >2 mm in diameter (0.4%), skeletal deformities (0.6%), and fin rot/erosion (0.5%) were low. The only externally visible parasite recorded was Cryptocotyle concavum (28.2%). The results......Information on prevalences of grossly visible diseases and parasites of flounder (Platichthys flesus) from the Baltic Sea is presented for 11 sampling areas on a transect from the Mecklenburg Eight to the Gulf of Finland. Among the 3008 flounder examined, highest overall prevalences were observed...... of a multivariate statistical analysis reveal that the diseases are influenced by a variety of host-specific (length, age, sex) and area-specific (salinity, temperature) factors as well as their interactions. By calculating the expected prevalence for a standardized fish population for each area and disease...

  12. PWZ-029, an inverse agonist selective for α₅ GABAA receptors, improves object recognition, but not water-maze memory in normal and scopolamine-treated rats.

    Science.gov (United States)

    Milić, Marija; Timić, Tamara; Joksimović, Srđan; Biawat, Poonam; Rallapalli, Sundari; Divljaković, Jovana; Radulović, Tamara; Cook, James M; Savić, Miroslav M

    2013-03-15

    Inverse agonism at the benzodiazepine site of α(5) subunit-containing GABA(A) receptors is an attractive approach for the development of putative cognition-enhancing compounds, which are still far from clinical application. Several ligands with binding and/or functional selectivity for α(5) GABA(A) receptors have been synthesized and tested in a few animal models. PWZ-029 is an α(5) GABA(A) selective inverse agonist whose memory enhancing effects were demonstrated in the passive avoidance task in rats and in Pavlovian fear conditioning in mice. In the present study we investigated the effects of PWZ-029 administration in novel object recognition test and Morris water maze, in normal and scopolamine-treated rats. All the three doses of PWZ-029 (2, 5 and 10 mg/kg) improved object recognition after the 24-h delay period, as shown by significant differences between the exploration times of the novel and old object, and the respective discrimination indices. PWZ-029 (2 mg/kg) also successfully reversed the 0.3 mg/kg scopolamine-induced deficit in recognition memory after the 1-h delay. In the Morris water maze test, PWZ-029 (5, 10 and 15 mg/kg) did not significantly influence swim patterns, either during five acquisition days or during the treatment-free probe trial. PWZ-029 (2, 5 and 10 mg/kg) also proved to be ineffective in the reversal of the 1mg/kg scopolamine-induced memory impairment in the water maze. The present mixed results encourage use of a variety of tests and experimental conditions in order to increase the predictability of preclinical testing of selective α(5) GABA(A) inverse agonists.

  13. Recognition of faux pas by normally developing children and children with Asperger syndrome or high-functioning autism.

    Science.gov (United States)

    Baron-Cohen, S; O'Riordan, M; Stone, V; Jones, R; Plaisted, K

    1999-10-01

    Most theory of mind (ToM) tests are designed for subjects with a mental age of 4-6 years. There are very few ToM tests for subjects who are older or more able than this. We report a new test of ToM, designed for children 7-11 years old. The task involves recognizing faux pas. Study 1 tested 7-9, and 11-year-old normal children. Results showed that the ability to detect faux pas developed with age and that there was a differential developmental profile between the two sexes (female superiority). Study 2 tested children with Asperger syndrome (AS) or high-functioning autism (HFA), selected for being able to pass traditional 4- to 6-year level (first- and second-order) false belief tests. Results showed that whereas normal 9- to 11-year-old children were skilled at detecting faux pas, children with AS or HFA were impaired on this task. Study 3 reports a refinement in the test, employing control stimuli. This replicated the results from Study 2. Some patients with AS or HFA were able to recognize faux pas but still produced them. Future research should assess faux pas production.

  14. Experimental induction of reading difficulties in normal readers provides novel insights into the neurofunctional mechanisms of visual word recognition.

    Science.gov (United States)

    Heim, Stefan; Weidner, Ralph; von Overheidt, Ann-Christin; Tholen, Nicole; Grande, Marion; Amunts, Katrin

    2014-03-01

    Phonological and visual dysfunctions may result in reading deficits like those encountered in developmental dyslexia. Here, we use a novel approach to induce similar reading difficulties in normal readers in an event-related fMRI study, thus systematically investigating which brain regions relate to different pathways relating to orthographic-phonological (e.g. grapheme-to-phoneme conversion, GPC) vs. visual processing. Based upon a previous behavioural study (Tholen et al. 2011), the retrieval of phonemes from graphemes was manipulated by lowering the identifiability of letters in familiar vs. unfamiliar shapes. Visual word and letter processing was impeded by presenting the letters of a word in a moving, non-stationary manner. FMRI revealed that the visual condition activated cytoarchitectonically defined area hOC5 in the magnocellular pathway and area 7A in the right mesial parietal cortex. In contrast, the grapheme manipulation revealed different effects localised predominantly in bilateral inferior frontal gyrus (left cytoarchitectonic area 44; right area 45) and inferior parietal lobule (including areas PF/PFm), regions that have been demonstrated to show abnormal activation in dyslexic as compared to normal readers. This pattern of activation bears close resemblance to recent findings in dyslexic samples both behaviourally and with respect to the neurofunctional activation patterns. The novel paradigm may thus prove useful in future studies to understand reading problems related to distinct pathways, potentially providing a link also to the understanding of real reading impairments in dyslexia.

  15. 频域光照归一化的人脸识别%Face Recognition Based on Illumination Normalization in Frequency-Domain

    Institute of Scientific and Technical Information of China (English)

    琚生根; 周激流; 何坤; 夏欣; 王刚

    2009-01-01

    In order, to reduce the impact environmental requirements and overcome the effects of illumination on face recognition, a novel recognition method is presented based on normalization illumination in frequency-domain, via analyzing the Amplitude-frequency and phase-frequency characteristics of human faces. Collected images under any light conditions are normalized so that the light is exactly the same for the training images, while retaining the distinctive features of human faces. As the different information of faces is usually small, the smallest non-zero eigenvector is chosen as a facial feature. Experimental results show that our method is more robust against light than traditional methods.%为了降低人脸识别对环境条件的要求,克服光照对人脸识别的影响,通过分析人脸图像的幅频特性和相频特性,提出了频域光照归一化的人脸识别,对任何光照条件下采集的图像经过归一化后,光照与训练库中完全相同,同时保留了人脸的可区分性.人脸之间差异的信息量一般较少,运用最小非零特征向量作为人脸特征.实验仿真表明,与传统方法相比,频域光照归一化人脸识别方法对光照变化具有鲁棒性.

  16. 基于光照归一化分块完备LBP特征的人脸识别%Face recognition based on illumination normalization and block-based completed local binary pattern

    Institute of Scientific and Technical Information of China (English)

    周巍; 程勇; 曹雪虹

    2015-01-01

    针对复杂光照条件下的人脸识别,提出了一种基于光照归一化分块完备局部二值模式(B-CLBP)特征的人脸识别算法。该方法对人脸图像进行光照归一化预处理,对处理后的人脸图像进行B-CLBP特征提取,融合成B-CLBP直方图,根据最近邻准则进行分类识别。在Extended Yale B人脸库上的实验结果表明,所提算法可以有效提高复杂光照条件下的人脸识别率。%Aiming at the problem of face recognition under complex illumination, an effective face recognition method based on illumination normalization and block-based completed local binary pattern is proposed. The method performs illumination normalization on face images, then extracts the B-CLBP features from the processed face images in order to form the B-CLBP histogram, applies the nearest neighbor principle for face recognition. The experimental results on Extended Yale B face databases demonstrate that the proposed method can achieve significant recognition rate under com-plex illumination conditions.

  17. Measurements of normal inner ear on computed tomography in children with congenital sensorineural hearing loss.

    Science.gov (United States)

    Lan, Ming-Ying; Shiao, Jiun-Yih; Ho, Ching-Yin; Hung, Hao-Chun

    2009-09-01

    The objective of this study is to use standardized measurements of the inner ear to see whether there are subtle bony malformations in children with congenital sensorineural hearing loss (SNHL) whose temporal bone computed tomography (CT) are grossly normal. The study includes 45 ears with congenital SNHL and grossly normal temporal bone CT scans and 45 ears with normal inner ear structures and normal hearing. Standardized measurements of the inner ear structures were made on axial temporal bone CT scans. Student's t test was performed to compare the measurements of the two groups. There were significant differences in the measurements of the bony island width of the superior semicircular canal, bony island width of the lateral semicircular canal and maximal height of cochlea between two groups (P inner ear on temporal bone CT can identify subtle abnormalities of inner ear in patients with congenital SNHL having grossly normal radiological images.

  18. National survey data for zoonotic schistosomiasis in the Philippines grossly underestimates the true burden of disease within endemic zones: implications for future control.

    Science.gov (United States)

    Olveda, Remigio M; Tallo, Veronica; Olveda, David U; Inobaya, Marianette T; Chau, Thao N; Ross, Allen G

    2016-04-01

    Zoonotic schistosomiasis has a long endemic history in the Philippines. Human mass drug administration has been the cornerstone of schistosomiasis control in the country for the past three decades. Recent publications utilizing retrospective national survey data have indicated that the national human prevalence of the disease is disease is now close to elimination. However, the evidence for such a claim is weak, given that less than a third of the human population is currently being treated annually within endemic zones and only a third of those treated actually swallow the tablets. For those who consume the drug at the single oral dose of 40mg/kg, the estimated cure rate is 52% based on a recent meta-analysis. Thus, approximately 5% of the endemic human population is in reality receiving the appropriate treatment. To compound this public health problem, most of the bovines in the endemic communities are concurrently infected but are not treated under the current national control programme. Given this evidence, it is believed that the human prevalence of schistosomiasis within endemic regions has been grossly underestimated. Inherent flaws in the reporting of national schistosomiasis prevalence data are reported here, and the problems of utilizing national retrospective data in making geographic information system (GIS) risk maps and advising policy makers of the outcomes are highlighted.

  19. National survey data for zoonotic schistosomiasis in the Philippines grossly underestimates the true burden of disease within endemic zones: implications for future control

    Directory of Open Access Journals (Sweden)

    Remigio M. Olveda

    2016-04-01

    Full Text Available Zoonotic schistosomiasis has a long endemic history in the Philippines. Human mass drug administration has been the cornerstone of schistosomiasis control in the country for the past three decades. Recent publications utilizing retrospective national survey data have indicated that the national human prevalence of the disease is <1%, hence the disease is now close to elimination. However, the evidence for such a claim is weak, given that less than a third of the human population is currently being treated annually within endemic zones and only a third of those treated actually swallow the tablets. For those who consume the drug at the single oral dose of 40 mg/kg, the estimated cure rate is 52% based on a recent meta-analysis. Thus, approximately 5% of the endemic human population is in reality receiving the appropriate treatment. To compound this public health problem, most of the bovines in the endemic communities are concurrently infected but are not treated under the current national control programme. Given this evidence, it is believed that the human prevalence of schistosomiasis within endemic regions has been grossly underestimated. Inherent flaws in the reporting of national schistosomiasis prevalence data are reported here, and the problems of utilizing national retrospective data in making geographic information system (GIS risk maps and advising policy makers of the outcomes are highlighted.

  20. The recognition of sine-wave Mandarin Chinese in normal-hearing listeners%听力正常人对正弦波汉语普通话的识别

    Institute of Scientific and Technical Information of China (English)

    冯艳梅; 徐立; 周宁; 杨光; 殷善开

    2012-01-01

    Objective To study the mechanism in recognition of sine-wave Mandarin Chinese tones and sentences in normal-hearing listeners.Method The testing involved recognition of tones and sentences processed with sine-wave replica. A practice session was given to all 45 normal-hearing subjects before formal test. Feedback was provided to the subjects during the practice session (but not during the formal test) to familiarize the subjects with the sine-wave replica. In tone recognition, the subjects were forced to choose from four tone tokens displayed on the screen when he/she heard a sine-wave tone token. The aine-wave tone tokens were presented only once. The correct percent was recorded from each subject. The Mandarin hearing in noise test (MHINT) was adopted for the sentence recognition of sine-wave replica. The subjects could listen to the sine-wave replica as many times as he/she wanted. The correct percent was recorded.Results The mean score for tone recognition of sine-wave replica was 32.6% which was only slighdy higher than the chance level (25%). The scores ranged from 23.5% to 42.3%, with most scores ranging from 25% to 35%. In the tone recognition, tone 1 scored the highest (42.3% correct), followed by tone 3 (34.9% correct). Tone 2 and tone 4 scored 23.5% and 29.6% correct, respectively. The mean score for sentence recognition of sine-wave replica was 92.3%. The scores ranged from 78% to 100% correct, with most scores above 80% correct. Paired t test indicated that the difference between tone and sentence recognition of sine-wave replica was statistically significant (P<0.05). Conclusion The recognition of sine-wave Mandarin Chinese tones was poor but the recognition was nearly perfect for sentences. The top-down processes must play an important role in sine-wave Mandarin sentence recognition.%目的 通过听力正常人对正弦波处理的汉语普通话的音调及句子识别,探讨正弦波汉语普通话的识别机制。方法 测试包括正弦波

  1. Oclusão normal na dentadura mista: reconhecimento das características oclusais por alunos de graduação Normal occlusion during mixed dentition: recognition of occlusal traits by dental students

    Directory of Open Access Journals (Sweden)

    José Augusto Mendes Miguel

    2005-02-01

    Full Text Available O propósito deste artigo foi avaliar o grau de conhecimento sobre o desenvolvimento normal da oclusão durante a fase da dentadura mista. A amostra foi composta de 138 alunos do último período de graduação de dez Faculdades de Odontologia do Estado do Rio de Janeiro, que foram avaliados por meio de questionários com perguntas fechadas. Foram apresentados aos alunos fotografias e modelos de estudo de um paciente Classe I de Angle na fase do " patinho feio" (oclusão normal. Constatou-se que há certa facilidade por parte dos estudantes em diagnosticar a Classe I de Angle (n=120 ou 87,6%, assim como a presença de trespasse horizontal aumentado (n=109 ou 79,6% e a existência de diastemas (n=112 ou 81,7%. Em relação à sobremordida, observou-se que 40 (28,9% alunos identificaram um aumento da mesma, e apenas um número muito reduzido da amostra considerou estas características compatíveis com a fase da dentadura mista. Apenas 10,1% entenderam que não havia necessidade de tratamento ortodôntico, já que a oclusão era totalmente compatível com a fase de desenvolvimento. Os resultados mostraram que uma grande parte dos alunos termina o curso de graduação com dificuldades em identificar as características normais do desenvolvimento, o que pode levar a tratamentos desnecessários ou encaminhamentos tardios.The aim of this study was to evaluate the knowledge degree about normal occlusion development during the mixed dentition phase. The sample was composed of 138 students in their senior year from 10 Dental Schools in the Rio de Janeiro state. After observing photographs and study casts of a Class I patient showing normal occlusion during mixed dentition, students were evaluated through a questionnaire. It was found that was fairly easy for them to diagnose a Class I patient (n=120 or 87.59%, as much as the increased overjet (n=109 or 79.6% and diastemas (n=112 or 81.7%. Considering the overbite, it was observed that 40 students (28

  2. Pattern recognition

    CERN Document Server

    Theodoridis, Sergios

    2003-01-01

    Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10

  3. Recognition of Disorders and Emotional Problems of Deaf Children Using House-Tree-Person and Draw-A-Person Tests in Comparison with Normal Children of Hamadan Province

    Directory of Open Access Journals (Sweden)

    D. Amini

    2013-04-01

    Full Text Available Introduction & Objective: Deaf children have special emotional reactions, Understanding these characteristics and problems can help medical and paramedical professionals, parents and teachers to reach the purpose of behavioral adaptability.The present study was performed in order to recognize disorders, emotional problems and functions of deaf children compared with normal children in emotional components of anxiety, depression, aggression, impulsiv-ity and lack of compromise. Materials & Methods: In order to recognize emotional disorders and problems of deaf children, sample groups of 120 male and female patients (60 deaf children and 60 children with nor-mal hearing with equal number of male and female enrolled in primary schools of Hamadan province were selected by multi stage randomly sampling in this casual_comparative study. House-Tree-Person (HTP and Draw-A-Person tests (DAP were used to determine their emotional problems. Results:Our results indicate that in terms of parameters related to the two tests (distance of three components of each other ,anxiety, aggression, depression and impulsivity and lack of compromise, participants' overall scores in two tests by major scales such as anxiety (?=0.01, P< 0.05; 3.48, 3.13 aggression (?= 0.05 , 0.01, P< 0.05; 6.12 ,3.97 depression (?=0.05 P<0.05 ; 3.75,3.81 , impulsivity (?=0.05, 0.01, P<0.05 ; 3.47, 3.01 and lack of compromise (?=0.05, 0.01, P<0.05; 4.89, 4.95 are significantly different from each other. Conclusion:The deaf children in terms of denotative parameters related to the two tests are sig-nificantly different from normal children; and the overall scores obtained on each of the scales generally show a significant difference with normal children,In the deaf group with regard to gender variable (male and female significant differences in some of the scales such as distance of three components of each other ,anxiety, aggression, depression and lack of compromise iare observed between

  4. Limiares de reconhecimento de sentenças no ruído, em campo livre: valores de referência para adultos normo-ouvintes Speech recognition thresholds in noisy areas: reference values for normal hearing adults

    Directory of Open Access Journals (Sweden)

    Marília Oliveira Henriques

    2008-04-01

    Full Text Available Nas clínicas de audiologia, as queixas de dificuldade de compreensão da fala em ambientes ruidosos são freqüentes, mesmo para indivíduos normo-ouvintes. Assim, o audiologista deve não só identificar uma perda auditiva, mas também analisar a compreensão da fala, em condições de comunicação próximas às encontradas no cotidiano. OBJETIVO: Determinar o valor de referência para os limiares de reconhecimento de sentenças no ruído, em campo livre, para indivíduos adultos normo-ouvintes. MATERIAL E MÉTODO: O experimento foi realizado nos anos de 2005 e 2006. Participaram da pesquisa 150 indivíduos adultos normo-ouvintes, com idade entre 18 e 64 anos, avaliados em cabine acusticamente tratada. Realizou-se a avaliação a partir da aplicação do teste Listas de Sentenças em Português. As listas de sentenças foram apresentadas em campo livre, na presença de um ruído competitivo, na intensidade fixa de 65 dB A. O ângulo de incidência de ambos os estímulos foi de 0º- 0º azimute. RESULTADOS E CONCLUSÃO: Os limiares de reconhecimento de sentenças em campo-livre foram obtidos na relação sinal-ruído de -8,14 dB A, sendo este o valor de referência para indivíduos normo-ouvintes.In audiology clinics, complaints about difficulties in speech recognition in noise environments are frequent, even for normal-hearing individuals. Thus, the audiologist must not only identify a hearing loss, but also analyze speech recognition, under noisy conditions similar to those found in our daily lives. AIM: Determine the reference value for the recognition of phrases under noisy conditions, in the free field, for adult normal hearing patients. MATERIALS AND METHODS: This study was carried out in 2005 and 2006. We had 150 adult normal hearing individuals participating, with ages between 18 and 64 years, assessed in a sound-proof booth. We evaluation was based on lists of phrases in Portuguese. The phrases lists were presented in the free field

  5. Voice Recognition in Face-Blind Patients.

    Science.gov (United States)

    Liu, Ran R; Pancaroglu, Raika; Hills, Charlotte S; Duchaine, Brad; Barton, Jason J S

    2016-04-01

    Right or bilateral anterior temporal damage can impair face recognition, but whether this is an associative variant of prosopagnosia or part of a multimodal disorder of person recognition is an unsettled question, with implications for cognitive and neuroanatomic models of person recognition. We assessed voice perception and short-term recognition of recently heard voices in 10 subjects with impaired face recognition acquired after cerebral lesions. All 4 subjects with apperceptive prosopagnosia due to lesions limited to fusiform cortex had intact voice discrimination and recognition. One subject with bilateral fusiform and anterior temporal lesions had a combined apperceptive prosopagnosia and apperceptive phonagnosia, the first such described case. Deficits indicating a multimodal syndrome of person recognition were found only in 2 subjects with bilateral anterior temporal lesions. All 3 subjects with right anterior temporal lesions had normal voice perception and recognition, 2 of whom performed normally on perceptual discrimination of faces. This confirms that such lesions can cause a modality-specific associative prosopagnosia.

  6. Effects of the cannabinoid 1 receptor peptide ligands hemopressin, (m)RVD-hemopressin(α) and (m)VD-hemopressin(α) on memory in novel object and object location recognition tasks in normal young and Aβ1-42-treated mice.

    Science.gov (United States)

    Zhang, Rui-San; He, Zhen; Jin, Wei-Dong; Wang, Rui

    2016-10-01

    The cannabinoid system plays an important role in memory processes, many studies have indicated that cannabinoid receptor ligands have ability to modulate memory in rodents. A nonapeptide hemopressin (Hp) derived from rat brain, acts as a peptide antagonist or selective inverse peptide agonist of cannabinoid 1 (CB1) receptor. N-terminally extended forms of Hp isolated from mouse brain, (m)RVD-hemopressin(α) (RVD) and (m)VD-hemopressin(α) (VD) also bind CB1 receptor, however, as peptide agonists. Here, we investigated the roles of Hp, RVD, and VD on memory in mice using novel object recognition (NOR) and object location recognition (OLR) tasks. In normal young mice, intracerebroventricular (i.c.v.) infusion of Hp before training not only improved memory formation, but also prolonged memory retention in the tasks, these effects could be inhibited by RVD or VD at the same dose and intraperitoneal (i.p.) injection of a small molecule agonist of CB1 receptor WIN55, 212-2 15min before administration of Hp inhibited the memory-improving effect of Hp. In addition, under the same experimental conditions, i.c.v. RVD or VD displayed memory-impairing effects, which could be prevented by Hp (i.c.v.) or AM251 (i.p.), a small molecule antagonist of CB1 receptor. Infusion of amyloid-β (1-42) (Aβ1-42) 14days before training resulted in impairment of memory in mice which could be used as animal model of Alzheimer's disease (AD). In these mice, RVD or VD (i.c.v.) reversed the memory impairment induced by Aβ1-42, and the effects of RVD and VD could be suppressed by Hp (i.c.v.) or AM251 (2mg/kg, i.p.). Separate administration of Hp had no effect in Aβ1-42-treated mice. The above results suggested that Hp, RVD and VD, as CB1 receptor peptide ligands, may be potential drugs to treatment of the memory deficit-involving disease, just as AD. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Facial Recognition

    National Research Council Canada - National Science Library

    Mihalache Sergiu; Stoica Mihaela-Zoica

    2014-01-01

    .... From birth, faces are important in the individual's social interaction. Face perceptions are very complex as the recognition of facial expressions involves extensive and diverse areas in the brain...

  8. Fingerprint recognition

    OpenAIRE

    Diefenderfer, Graig T.

    2006-01-01

    The use of biometrics is an evolving component in today's society. Fingerprint recognition continues to be one of the most widely used biometric systems. This thesis explores the various steps present in a fingerprint recognition system. The study develops a working algorithm to extract fingerprint minutiae from an input fingerprint image. This stage incorporates a variety of image pre-processing steps necessary for accurate minutiae extraction and includes two different methods of ridge thin...

  9. Pattern Recognition by Combined Invariants

    Institute of Scientific and Technical Information of China (English)

    WANG Xiaohong; ZHAO Rongchun

    2001-01-01

    A feature-based recognition of objectsor patterns independent of their position, size, orien-tation and other variations has been the goal of muchrecent research. The existing approaches to invarianttwo-dimensional pattern recognition are useless whenpattern is blurred. In this paper, we present a novelpattern recognition system which can solve the prob-lem by using combined invariants as image features.The classification technique we choose for our systemis weighted normalized cross correlation. The mean ofthe intraclass standard deviations of the kth featureover the total number of prototypes for each class isused as a weighting factor during the classification pro-cess to improve recognition accuracy. The feasibilityof our pattern recognition system and the invarianceof the combined features with respect to translation,scaling, rotation and blurring are approved by numer-ical experiments on head images.

  10. Prenatal diagnosis of 45,X/46,XY mosaicism with postnatal confirmation in a phenotypically normal male infant.

    Science.gov (United States)

    Hsu, L Y; Kim, H J; Hausknecht, R; Hirschhorn, K

    1976-10-01

    Prenatal detection of chromosome mosaicism has always been a diagnostic dilemma. In 21 reported cases of chromosomal mosaicism in cultured amniotic fluid cells, only two cases had cytogenetic confirmation of the mosaicism. All 21 pregnancies resulted in either phenotypically normal liveborns or grossly normal abortuses. We report a case of XO/XY mosaicism detected prenatally and confirmed postnatally in a grossly normal male infant. The indication for prenatal cytogenetic diagnosis was advanced maternal age (38 years). A diagnosis of XO/XY mosaicism was made from two separate culture flasks of amniotic fluid cells, with 45,X cells predominating (86.4%). The Y chromosome was of normal size but carried no fluorescent band. The parents were counseled and were advised that the phenotype of XO/XY mosaicism can range from relative normality to sexual maldevelopment. They decided to continue this pregnancy. The infant was born at term and was a grossly normal male with normal penis and descended, normal-sized testes. Leukocyte culture from the cord blood and a skin fibroblast culture confirmed the mosaicism of XO/XY. The father's Y chromosome was of identical size and carried a small fluorescent band. It appears that an altered Y chromosome may be predisposed to anaphase lag leading to mosaicism.

  11. Facial Recognition

    Directory of Open Access Journals (Sweden)

    Mihalache Sergiu

    2014-05-01

    Full Text Available During their lifetime, people learn to recognize thousands of faces that they interact with. Face perception refers to an individual's understanding and interpretation of the face, particularly the human face, especially in relation to the associated information processing in the brain. The proportions and expressions of the human face are important to identify origin, emotional tendencies, health qualities, and some social information. From birth, faces are important in the individual's social interaction. Face perceptions are very complex as the recognition of facial expressions involves extensive and diverse areas in the brain. Our main goal is to put emphasis on presenting human faces specialized studies, and also to highlight the importance of attractiviness in their retention. We will see that there are many factors that influence face recognition.

  12. Recognition memory impairments caused by false recognition of novel objects.

    Science.gov (United States)

    Yeung, Lok-Kin; Ryan, Jennifer D; Cowell, Rosemary A; Barense, Morgan D

    2013-11-01

    A fundamental assumption underlying most current theories of amnesia is that memory impairments arise because previously studied information either is lost rapidly or is made inaccessible (i.e., the old information appears to be new). Recent studies in rodents have challenged this view, suggesting instead that under conditions of high interference, recognition memory impairments following medial temporal lobe damage arise because novel information appears as though it has been previously seen. Here, we developed a new object recognition memory paradigm that distinguished whether object recognition memory impairments were driven by previously viewed objects being treated as if they were novel or by novel objects falsely recognized as though they were previously seen. In this indirect, eyetracking-based passive viewing task, older adults at risk for mild cognitive impairment showed false recognition to high-interference novel items (with a significant degree of feature overlap with previously studied items) but normal novelty responses to low-interference novel items (with a lower degree of feature overlap). The indirect nature of the task minimized the effects of response bias and other memory-based decision processes, suggesting that these factors cannot solely account for false recognition. These findings support the counterintuitive notion that recognition memory impairments in this memory-impaired population are not characterized by forgetting but rather are driven by the failure to differentiate perceptually similar objects, leading to the false recognition of novel objects as having been seen before.

  13. Iris Recognition using Orthogonal Transforms

    Directory of Open Access Journals (Sweden)

    M.Mani Roja

    2012-12-01

    Full Text Available Iris Recognition is a biometric recognition technique in which features of the iris are used to uniquely identify individuals. Iris recognition has over the years emerged as one of the most accuratebiometric techniques as opposed to other biometric techniques like face, signature and fingerprint. First, the iris image is pre processed using canny edge detector using a Gaussian filter. The iris edge and the pupil edge are extracted using image morphological operation, image opening. After normalization of red, green and blue components of the colour iris using Euclidean distance method, they are combined to form the localized colour iris. For feature vectors extraction, orthogonal transforms like discrete cosine transform, discrete sine transform and discrete Fourier transform have been considered. The proposed iris recognition system is very time efficient and it takes less than 1 second to grant authentication.

  14. Isolated Speech Recognition Using Artificial Neural Networks

    Science.gov (United States)

    2007-11-02

    In this project Artificial Neural Networks are used as research tool to accomplish Automated Speech Recognition of normal speech. A small size...the first stage of this work are satisfactory and thus the application of artificial neural networks in conjunction with cepstral analysis in isolated word recognition holds promise.

  15. Speaker Recognition

    DEFF Research Database (Denmark)

    Mølgaard, Lasse Lohilahti; Jørgensen, Kasper Winther

    2005-01-01

    Speaker recognition is basically divided into speaker identification and speaker verification. Verification is the task of automatically determining if a person really is the person he or she claims to be. This technology can be used as a biometric feature for verifying the identity of a person...... in applications like banking by telephone and voice mail. The focus of this project is speaker identification, which consists of mapping a speech signal from an unknown speaker to a database of known speakers, i.e. the system has been trained with a number of speakers which the system can recognize....

  16. The recognition of work

    OpenAIRE

    Nierling, Linda

    2007-01-01

    The following article argues that recognition structures in work relations differ significantly in the sphere of paid work in contrast to unpaid work in private spheres. According to the systematic approach on recognition of Axel Honneth three different levels of recognition are identified: the interpersonal recognition, organisational recognition and societal recognition. Based on this framework it can be stated that recognition structures in the sphere of paid work and in private spheres di...

  17. Clarifying Normalization

    Science.gov (United States)

    Carpenter, Donald A.

    2008-01-01

    Confusion exists among database textbooks as to the goal of normalization as well as to which normal form a designer should aspire. This article discusses such discrepancies with the intention of simplifying normalization for both teacher and student. This author's industry and classroom experiences indicate such simplification yields quicker…

  18. Speech recognition with amplitude and frequency modulations

    Science.gov (United States)

    Zeng, Fan-Gang; Nie, Kaibao; Stickney, Ginger S.; Kong, Ying-Yee; Vongphoe, Michael; Bhargave, Ashish; Wei, Chaogang; Cao, Keli

    2005-02-01

    Amplitude modulation (AM) and frequency modulation (FM) are commonly used in communication, but their relative contributions to speech recognition have not been fully explored. To bridge this gap, we derived slowly varying AM and FM from speech sounds and conducted listening tests using stimuli with different modulations in normal-hearing and cochlear-implant subjects. We found that although AM from a limited number of spectral bands may be sufficient for speech recognition in quiet, FM significantly enhances speech recognition in noise, as well as speaker and tone recognition. Additional speech reception threshold measures revealed that FM is particularly critical for speech recognition with a competing voice and is independent of spectral resolution and similarity. These results suggest that AM and FM provide independent yet complementary contributions to support robust speech recognition under realistic listening situations. Encoding FM may improve auditory scene analysis, cochlear-implant, and audiocoding performance. auditory analysis | cochlear implant | neural code | phase | scene analysis

  19. Birkhoff normalization

    NARCIS (Netherlands)

    Broer, H.; Hoveijn, I.; Lunter, G.; Vegter, G.

    2003-01-01

    The Birkhoff normal form procedure is a widely used tool for approximating a Hamiltonian systems by a simpler one. This chapter starts out with an introduction to Hamiltonian mechanics, followed by an explanation of the Birkhoff normal form procedure. Finally we discuss several algorithms for comput

  20. Window Size Impact in Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Oresti Banos

    2014-04-01

    Full Text Available Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact, most designs normally rely on figures used in previous works, but with no strict studies that support them. Intuitively, decreasing the window size allows for a faster activity detection, as well as reduced resources and energy needs. On the contrary, large data windows are normally considered for the recognition of complex activities. In this work, we present an extensive study to fairly characterize the windowing procedure, to determine its impact within the activity recognition process and to help clarify some of the habitual assumptions made during the recognition system design. To that end, some of the most widely used activity recognition procedures are evaluated for a wide range of window sizes and activities. From the evaluation, the interval 1–2 s proves to provide the best trade-off between recognition speed and accuracy. The study, specifically intended for on-body activity recognition systems, further provides designers with a set of guidelines devised to facilitate the system definition and configuration according to the particular application requirements and target activities.

  1. Emotion recognition during cocaine intoxication.

    Science.gov (United States)

    Kuypers, K P C; Steenbergen, L; Theunissen, E L; Toennes, S W; Ramaekers, J G

    2015-11-01

    Chronic or repeated cocaine use has been linked to impairments in social skills. It is not clear whether cocaine is responsible for this impairment or whether other factors, like polydrug use, distort the observed relation. We aimed to investigate this relation by means of a placebo-controlled experimental study. Additionally, associations between stressor-related activity (cortisol, cardiovascular parameters) induced by the biological stressor cocaine, and potential cocaine effects on emotion recognition were studied. Twenty-four healthy recreational cocaine users participated in this placebo-controlled within-subject study. Participants were tested between 1 and 2 h after treatment with oral cocaine (300 mg) or placebo. Emotion recognition of low and high intensity expressions of basic emotions (fear, anger, disgust, sadness, and happiness) was tested. Findings show that cocaine impaired recognition of negative emotions; this was mediated by the intensity of the presented emotions. When high intensity expressions of Anger and Disgust were shown, performance under influence of cocaine 'normalized' to placebo-like levels while it made identification of Sadness more difficult. The normalization of performance was most notable for participants with the largest cortisol responses in the cocaine condition compared to placebo. It was demonstrated that cocaine impairs recognition of negative emotions, depending on the intensity of emotion expression and cortisol response.

  2. Gesture Recognition Summarization

    Institute of Scientific and Technical Information of China (English)

    ZHANG Ting-fang; FENG Zhi-quan; SU Yuan-yuan; JIANG Yan

    2014-01-01

    Gesture recognition is an important research in the field of human-computer interaction. Hand Gestures are strong variable and flexible, so the gesture recognition has always been an important challenge for the researchers. In this paper, we first outlined the development of gestures recognition, and different classification of gestures based on different purposes. Then we respectively introduced common methods used in the process of gesture segmentation, feature extraction and recognition. Finally, the gesture recognition was summarized and the studying prospects were given.

  3. Iris Recognition Technique

    Institute of Scientific and Technical Information of China (English)

    XIE Mei

    2006-01-01

    The demand on security is increasing greatly in these years and biometric recognition gradually becomes a hot field of research. Iris recognition is a new branch of biometric recognition, which is regarded as the most stable, safe and accurate biometric recognition method. In these years, much progress in this field has been made by scholars and experts of different countries. In this paper, some successful iris recognition methods are listed and their performance are compared. Furthermore, the existing problems and challenges are discussed.

  4. The Impact of Variable Speech Rates on Word Recognition Score of People With Normal Hearing and Hearing Impairment%不同语速对听力正常者和听障者言语辨别率的影响

    Institute of Scientific and Technical Information of China (English)

    刘亚南

    2015-01-01

    ObjectiveTo do research on the impact of variable speech rates on word recognition score of people with normal hearing and hearing impairment. Methods30 cases of patients with mild to moderate sensorineural hearing loss were selected as the observation group. 30 cases of patients with normal hearing from the volunteers were randomly selected as the control group. Both groups were tested by the CD of different speech rate,which were recorded by themselves. Changes of variable speech rates and word recognition score of the two groups were compared.Results The normal speed of speech discrimination of the control group was 82.53%,and 1.5 times of the normal speed was 74.66%,2.0 times of the normal speed was 73.22%. In the observation group,the normal speed of speech discrimination was at 74.35%,1.5 times of the normal speed of 66.73%,2.0 times of the normal speed was 50.18%. The compararance of the two groups were significantly different(P<0.05).Conclusion From normal speed to 2.0 times normal speed of patients with hearing impairment,their speech discrimination rate was lower than those with normal hearing. It shows that sensorineural hearing loss and speech rate are related to the rate of speech discrimination.%目的:研究不同语速对听力正常者和听障者言语辨别率的影响。方法选择30例轻到中度感音神经性听力下降者作为观察组,在志愿者中随机抽取30例听力正常者作为对照组。两组均用自行录制的不同语速CD进行测试,比较两组在语速变化情况下言语辨别率的变化。结果正常语速时对照组的言语辨别率为82.53%,1.5倍正常语速时为74.66%,2.0倍正常语速时为73.22%;观察组在正常语速时的言语辨别率为74.35%,1.5倍正常语速时为66.73%,2.0倍正常语速时为50.18%,两组相比差异具有统计学意义(P<0.05)。结论从正常语速到2.0倍正常语速时听障者的言语辨别率较听力正常者低,表明感音神经性

  5. Novel Techniques for Dialectal Arabic Speech Recognition

    CERN Document Server

    Elmahdy, Mohamed; Minker, Wolfgang

    2012-01-01

    Novel Techniques for Dialectal Arabic Speech describes approaches to improve automatic speech recognition for dialectal Arabic. Since speech resources for dialectal Arabic speech recognition are very sparse, the authors describe how existing Modern Standard Arabic (MSA) speech data can be applied to dialectal Arabic speech recognition, while assuming that MSA is always a second language for all Arabic speakers. In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and M...

  6. Fuzzy Logic-Based Audio Pattern Recognition

    Science.gov (United States)

    Malcangi, M.

    2008-11-01

    Audio and audio-pattern recognition is becoming one of the most important technologies to automatically control embedded systems. Fuzzy logic may be the most important enabling methodology due to its ability to rapidly and economically model such application. An audio and audio-pattern recognition engine based on fuzzy logic has been developed for use in very low-cost and deeply embedded systems to automate human-to-machine and machine-to-machine interaction. This engine consists of simple digital signal-processing algorithms for feature extraction and normalization, and a set of pattern-recognition rules manually tuned or automatically tuned by a self-learning process.

  7. SPEECH EMOTION RECOGNITION USING MODIFIED QUADRATIC DISCRIMINATION FUNCTION

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Quadratic Discrimination Function(QDF)is commonly used in speech emotion recognition,which proceeds on the premise that the input data is normal distribution.In this Paper,we propose a transformation to normalize the emotional features,then derivate a Modified QDF(MQDF) to speech emotion recognition.Features based on prosody and voice quality are extracted and Principal Component Analysis Neural Network (PCANN) is used to reduce dimension of the feature vectors.The results show that voice quality features are effective supplement for recognition.and the method in this paper could improve the recognition ratio effectively.

  8. Object reading: text recognition for object recognition

    NARCIS (Netherlands)

    Karaoglu, S.; van Gemert, J.C.; Gevers, T.

    2012-01-01

    We propose to use text recognition to aid in visual object class recognition. To this end we first propose a new algorithm for text detection in natural images. The proposed text detection is based on saliency cues and a context fusion step. The algorithm does not need any parameter tuning and can d

  9. Face Recognition Using Local and Global Features

    Directory of Open Access Journals (Sweden)

    Jian Huang

    2004-04-01

    Full Text Available The combining classifier approach has proved to be a proper way for improving recognition performance in the last two decades. This paper proposes to combine local and global facial features for face recognition. In particular, this paper addresses three issues in combining classifiers, namely, the normalization of the classifier output, selection of classifier(s for recognition, and the weighting of each classifier. For the first issue, as the scales of each classifier's output are different, this paper proposes two methods, namely, linear-exponential normalization method and distribution-weighted Gaussian normalization method, in normalizing the outputs. Second, although combining different classifiers can improve the performance, we found that some classifiers are redundant and may even degrade the recognition performance. Along this direction, we develop a simple but effective algorithm for classifiers selection. Finally, the existing methods assume that each classifier is equally weighted. This paper suggests a weighted combination of classifiers based on Kittler's combining classifier framework. Four popular face recognition methods, namely, eigenface, spectroface, independent component analysis (ICA, and Gabor jet are selected for combination and three popular face databases, namely, Yale database, Olivetti Research Laboratory (ORL database, and the FERET database, are selected for evaluation. The experimental results show that the proposed method has 5–7% accuracy improvement.

  10. Graphical symbol recognition

    OpenAIRE

    K.C., Santosh; Wendling, Laurent

    2015-01-01

    International audience; The chapter focuses on one of the key issues in document image processing i.e., graphical symbol recognition. Graphical symbol recognition is a sub-field of a larger research domain: pattern recognition. The chapter covers several approaches (i.e., statistical, structural and syntactic) and specially designed symbol recognition techniques inspired by real-world industrial problems. It, in general, contains research problems, state-of-the-art methods that convey basic s...

  11. FACE RECOGNITION FROM FRONT-VIEW FACE

    Institute of Scientific and Technical Information of China (English)

    Wu Lifang; Shen Lansun

    2003-01-01

    This letter presents a face normalization algorithm based on 2-D face model to recognize faces with variant postures from front-view face. A 2-D face mesh model can be extracted from faces with rotation to left or right and the corresponding front-view mesh model can be estimated according to the facial symmetry. Then based on the inner relationship between the two mesh models, the normalized front-view face is formed by gray level mapping. Finally, the face recognition will be finished based on Principal Component Analysis (PCA). Experiments show that better face recognition performance is achieved in this way.

  12. Neuroethics beyond Normal.

    Science.gov (United States)

    Shook, John R; Giordano, James

    2016-01-01

    An integrated and principled neuroethics offers ethical guidelines able to transcend conventional and medical reliance on normality standards. Elsewhere we have proposed four principles for wise guidance on human transformations. Principles like these are already urgently needed, as bio- and cyberenhancements are rapidly emerging. Context matters. Neither "treatments" nor "enhancements" are objectively identifiable apart from performance expectations, social contexts, and civic orders. Lessons learned from disability studies about enablement and inclusion suggest a fresh way to categorize modifications to the body and its performance. The term "enhancement" should be broken apart to permit recognition of enablements and augmentations, and kinds of radical augmentation for specialized performance. Augmentations affecting the self, self-worth, and self-identity of persons require heightened ethical scrutiny. Reversibility becomes the core problem, not the easy answer, as augmented persons may not cooperate with either decommissioning or displacement into unaccommodating societies. We conclude by indicating how our four principles of self-creativity, nonobsolescence, empowerment, and citizenship establish a neuroethics beyond normal that is better prepared for a future in which humans and their societies are going so far beyond normal.

  13. Face Recognition in Various Illuminations

    Directory of Open Access Journals (Sweden)

    Saurabh D. Parmar,

    2014-05-01

    Full Text Available Face Recognition (FR under various illuminations is very challenging. Normalization technique is useful for removing the dimness and shadow from the facial image which reduces the effect of illumination variations still retaining the necessary information of the face. The robust local feature extractor which is the gray-scale invariant texture called Local Binary Pattern (LBP is helpful for feature extraction. K-Nearest Neighbor classifier is utilized for the purpose of classification and to match the face images from the database. Experimental results were based on Yale-B database with three different sub categories. The proposed method has been tested to robust face recognition in various illumination conditions. Extensive experiment shows that the proposed system can achieve very encouraging performance in various illumination environments.

  14. Covert Face Recognition without Prosopagnosia

    Directory of Open Access Journals (Sweden)

    H. D. Ellis

    1993-01-01

    Full Text Available An experiment is reported where subjects were presented with familiar or unfamiliar faces for supraliminal durations or for durations individually assessed as being below the threshold for recognition. Their electrodermal responses to each stimulus were measured and the results showed higher peak amplitude skin conductance responses for familiar than for unfamiliar faces, regardless of whether they had been displayed supraliminally or subliminally. A parallel is drawn between elevated skin conductance responses to subliminal stimuli and findings of covert recognition of familiar faces in prosopagnosic patients, some of whom show increased electrodermal activity (EDA to previously familiar faces. The supraliminal presentation data also served to replicate similar work by Tranel et al (1985. The results are considered alongside other data indicating the relation between non-conscious, “automatic” aspects of normal visual information processing and abilities which can be found to be preserved without awareness after brain injury.

  15. Face recognition using Krawtchouk moment

    Indian Academy of Sciences (India)

    J Sheeba Rani; D Devaraj

    2012-08-01

    Feature extraction is one of the important tasks in face recognition. Moments are widely used feature extractor due to their superior discriminatory power and geometrical invariance. Moments generally capture the global features of the image. This paper proposes Krawtchouk moment for feature extraction in face recognition system, which has the ability to extract local features from any region of interest. Krawtchouk moment is used to extract both local features and global features of the face. The extracted features are fused using summed normalized distance strategy. Nearest neighbour classifier is employed to classify the faces. The proposed method is tested using ORL and Yale databases. Experimental results show that the proposed method is able to recognize images correctly, even if the images are corrupted with noise and possess change in facial expression and tilt.

  16. Electrolarynx Voice Recognition Utilizing Pulse Coupled Neural Network

    Directory of Open Access Journals (Sweden)

    Fatchul Arifin

    2010-08-01

    Full Text Available The laryngectomies patient has no ability to speak normally because their vocal chords have been removed. The easiest option for the patient to speak again is by using electrolarynx speech. This tool is placed on the lower chin. Vibration of the neck while speaking is used to produce sound. Meanwhile, the technology of "voice recognition" has been growing very rapidly. It is expected that the technology of "voice recognition" can also be used by laryngectomies patients who use electrolarynx.This paper describes a system for electrolarynx speech recognition. Two main parts of the system are feature extraction and pattern recognition. The Pulse Coupled Neural Network – PCNN is used to extract the feature and characteristic of electrolarynx speech. Varying of β (one of PCNN parameter also was conducted. Multi layer perceptron is used to recognize the sound patterns. There are two kinds of recognition conducted in this paper: speech recognition and speaker recognition. The speech recognition recognizes specific speech from every people. Meanwhile, speaker recognition recognizes specific speech from specific person. The system ran well. The "electrolarynx speech recognition" has been tested by recognizing of “A” and "not A" voice. The results showed that the system had 94.4% validation. Meanwhile, the electrolarynx speaker recognition has been tested by recognizing of “saya” voice from some different speakers. The results showed that the system had 92.2% validation. Meanwhile, the best β parameter of PCNN for electrolarynx recognition is 3.

  17. AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION

    Directory of Open Access Journals (Sweden)

    K. Meena

    2013-11-01

    Full Text Available Automatic face recognition remains an interesting but challenging computer vision open problem. Poor illumination is considered as one of the major issue, since illumination changes cause large variation in the facial features. To resolve this, illumination normalization preprocessing techniques are employed in this paper to enhance the face recognition rate. The methods such as Histogram Equalization (HE, Gamma Intensity Correction (GIC, Normalization chain and Modified Homomorphic Filtering (MHF are used for preprocessing. Owing to great success, the texture features are commonly used for face recognition. But these features are severely affected by lighting changes. Hence texture based models Local Binary Pattern (LBP, Local Derivative Pattern (LDP, Local Texture Pattern (LTP and Local Tetra Patterns (LTrPs are experimented under different lighting conditions. In this paper, illumination invariant face recognition technique is developed based on the fusion of illumination preprocessing with local texture descriptors. The performance has been evaluated using YALE B and CMU-PIE databases containing more than 1500 images. The results demonstrate that MHF based normalization gives significant improvement in recognition rate for the face images with large illumination conditions.

  18. Face Recognition Based on Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Ali Javed

    2013-02-01

    Full Text Available The purpose of the proposed research work is to develop a computer system that can recognize a person by comparing the characteristics of face to those of known individuals. The main focus is on frontal two dimensional images that are taken in a controlled environment i.e. the illumination and the background will be constant. All the other methods of person’s identification and verification like iris scan or finger print scan require high quality and costly equipment’s but in face recognition we only require a normal camera giving us a 2-D frontal image of the person that will be used for the process of the person’s recognition. Principal Component Analysis technique has been used in the proposed system of face recognition. The purpose is to compare the results of the technique under the different conditions and to find the most efficient approach for developing a facial recognition system

  19. A Multi—View Face Recognition System

    Institute of Scientific and Technical Information of China (English)

    张永越; 彭振云; 等

    1997-01-01

    In many automatic face recognition systems,posture constraining is a key factor preventing them from application.In this paper a series of strategies will be described to achieve a system which enables face recognition under varying pose.These approaches include the multi-view face modeling,the threschold image based face feature detection,the affine transformation based face posture normalization and the template matching based face identification.Combining all of these strategies,a face recognition system with the pose invariance is designed successfully,Using a 75MHZ Pentium PC and with a database of 75 individuals,15 images for each person,and 225 test images with various postures,a very good recognition rate of 96.89% is obtained.

  20. Recognition of time-compressed speech does not predict recognition of natural fast-rate speech by older listeners.

    Science.gov (United States)

    Gordon-Salant, Sandra; Zion, Danielle J; Espy-Wilson, Carol

    2014-10-01

    This study investigated whether recognition of time-compressed speech predicts recognition of natural fast-rate speech, and whether this relationship is influenced by listener age. High and low context sentences were presented to younger and older normal-hearing adults at a normal speech rate, naturally fast speech rate, and fast rate implemented by time compressing the normal-rate sentences. Recognition of time-compressed sentences over-estimated recognition of natural fast sentences for both groups, especially for older listeners. The findings suggest that older listeners are at a much greater disadvantage when listening to natural fast speech than would be predicted by recognition performance for time-compressed speech.

  1. Lexicon Optimization for Dutch Speech Recognition in Spoken Document Retrieval

    NARCIS (Netherlands)

    Ordelman, Roeland; Hessen, van Arjan; Jong, de Franciska

    2001-01-01

    In this paper, ongoing work concerning the language modelling and lexicon optimization of a Dutch speech recognition system for Spoken Document Retrieval is described: the collection and normalization of a training data set and the optimization of our recognition lexicon. Effects on lexical coverage

  2. Lexicon optimization for Dutch speech recognition in spoken document retrieval

    NARCIS (Netherlands)

    Ordelman, Roeland; Hessen, van Arjan; Jong, de Franciska

    2001-01-01

    In this paper, ongoing work concerning the language modelling and lexicon optimization of a Dutch speech recognition system for Spoken Document Retrieval is described: the collection and normalization of a training data set and the optimization of our recognition lexicon. Effects on lexical coverage

  3. A REVIEW ON THE DEVELOPMENT OF INDONESIAN SIGN LANGUAGE RECOGNITION SYSTEM

    OpenAIRE

    Sutarman; Mazlina Abdul Majid; Jasni Mohamad Zain

    2013-01-01

    Sign language is mainly employed by hearing-impaired people to communicate with each other. However, communication with normal people is a major handicap for them since normal people do not understand their sign language. Sign language recognition is needed for realizing a human oriented interactive system that can perform an interaction like normal communication. Sign language recognition basically uses two approaches: (1) computer vision-based gesture recognition, in which a camera is used ...

  4. Multimodal eye recognition

    Science.gov (United States)

    Zhou, Zhi; Du, Yingzi; Thomas, N. L.; Delp, Edward J., III

    2010-04-01

    Multimodal biometrics use more than one means of biometric identification to achieve higher recognition accuracy, since sometimes a unimodal biometric is not good enough used to do identification and classification. In this paper, we proposed a multimodal eye recognition system, which can obtain both iris and sclera patterns from one color eye image. Gabor filter and 1-D Log-Gabor filter algorithms have been applied as the iris recognition algorithms. In sclera recognition, we introduced automatic sclera segmentation, sclera pattern enhancement, sclera pattern template generation, and sclera pattern matching. We applied kernelbased matching score fusion to improve the performance of the eye recognition system. The experimental results show that the proposed eye recognition method can achieve better performance compared to unimodal biometric identification, and the accuracy of our proposed kernel-based matching score fusion method is higher than two classic linear matching score fusion methods: Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).

  5. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

  6. Visual recognition of permuted words

    Science.gov (United States)

    Rashid, Sheikh Faisal; Shafait, Faisal; Breuel, Thomas M.

    2010-02-01

    In current study we examine how letter permutation affects in visual recognition of words for two orthographically dissimilar languages, Urdu and German. We present the hypothesis that recognition or reading of permuted and non-permuted words are two distinct mental level processes, and that people use different strategies in handling permuted words as compared to normal words. A comparison between reading behavior of people in these languages is also presented. We present our study in context of dual route theories of reading and it is observed that the dual-route theory is consistent with explanation of our hypothesis of distinction in underlying cognitive behavior for reading permuted and non-permuted words. We conducted three experiments in lexical decision tasks to analyze how reading is degraded or affected by letter permutation. We performed analysis of variance (ANOVA), distribution free rank test, and t-test to determine the significance differences in response time latencies for two classes of data. Results showed that the recognition accuracy for permuted words is decreased 31% in case of Urdu and 11% in case of German language. We also found a considerable difference in reading behavior for cursive and alphabetic languages and it is observed that reading of Urdu is comparatively slower than reading of German due to characteristics of cursive script.

  7. Statistical Pattern Recognition

    CERN Document Server

    Webb, Andrew R

    2011-01-01

    Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.  It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,

  8. Ear Recognition Based on Gabor Features and KFDA

    OpenAIRE

    Li Yuan; Zhichun Mu

    2014-01-01

    We propose an ear recognition system based on 2D ear images which includes three stages: ear enrollment, feature extraction, and ear recognition. Ear enrollment includes ear detection and ear normalization. The ear detection approach based on improved Adaboost algorithm detects the ear part under complex background using two steps: offline cascaded classifier training and online ear detection. Then Active Shape Model is applied to segment the ear part and normalize all the ear images to the s...

  9. Comparison of associative recognition versus source recognition.

    Science.gov (United States)

    Park, Heekyeong; Abellanoza, Cheryl; Schaeffer, James D

    2014-10-03

    The importance of the medial temporal lobe (MTL) for memory of arbitrary associations has been well established. However, the contribution of the MTL in concurrent retrieval of different classes of associations remains unclear. The present fMRI study investigated neural correlates of concurrent retrieval of associative and source memories. Participants studied a list of object pairs with two study tasks and judged the status and context of the pair during test. Associative retrieval was supported by neural activity in bilateral prefrontal cortex and left ventral occipito-temporal cortex, while source recognition was linked to activity in the right caudate. Both the hippocampus and MTL cortex showed retrieval activity for associative and source memory. Importantly, greater brain activity for successful associative recognition accompanied with successful source recognition was evident in left perirhinal and anterior hippocampal regions. These results indicate that the MTL is critical in the retrieval of different classes of associations.

  10. Recognition measured values

    OpenAIRE

    LEITKEP, Zdeněk

    2012-01-01

    This work deals recognition measured values. The main task is to find suitable method for preprocessing images and create interface to software performing recognition. Created application will be used primarily to analyze the photos on site acquisition. Application is developed in Java and properly documented on javadoc level.

  11. Handwritten Digits Recognition

    OpenAIRE

    Grand, Eric

    2000-01-01

    My work of diploma consisted in developing a Windows application for the recognition of the handwritten digits. The source images come from a pen-scanner. The user can also draw the digits directly with the mouse and do the recognition of it. In this software, I integrated the SVM Light reconizer.

  12. Multimodal recognition of emotions

    NARCIS (Netherlands)

    Datcu, D.

    2009-01-01

    This thesis proposes algorithms and techniques to be used for automatic recognition of six prototypic emotion categories by computer programs, based on the recognition of facial expressions and emotion patterns in voice. Considering the applicability in real-life conditions, the research is carried

  13. Applications of Pattern Recognition Algorithms in Agriculture: A Review

    Directory of Open Access Journals (Sweden)

    M. P. Raj

    2015-03-01

    Full Text Available Pattern recognition has its roots in artificial intelligence and is a branch of machine learning that focuses on the recognition of patterns and regularities in data. Data can be in the form of image, text, video or any other format. Under normal scenario, pattern recognition is implemented by first formalizing a problem, explain and at last visualize the pattern. In contrast to pattern matching, pattern recognition algorithms generally provide a fair result for all possible inputs by considering statistical variations. Probabilistic classifiers have supported Agricultural statistical inference for decades. Potential applications of this technique in agriculture are numerous like pattern recognition from satellite imagery, identifying the type of disease from leaf image, weed detection etc. This paper explores employment of pattern recognition in an agricultural domain.

  14. Comparative Analysis of Vehicle Make and Model Recognition Techniques

    Directory of Open Access Journals (Sweden)

    Faiza Ayub Syed

    2014-03-01

    Full Text Available Vehicle Make and Model Recognition (VMMR has emerged as a significant element of vision based systems because of its application in access control systems, traffic control and monitoring systems, security systems and surveillance systems, etc. So far a number of techniques have been developed for vehicle recognition. Each technique follows different methodology and classification approaches. The evaluation results highlight the recognition technique with highest accuracy level. In this paper we have pointed out the working of various vehicle make and model recognition techniques and compare these techniques on the basis of methodology, principles, classification approach, classifier and level of recognition After comparing these factors we concluded that Locally Normalized Harris Corner Strengths (LHNS performs best as compared to other techniques. LHNS uses Bayes and K-NN classification approaches for vehicle classification. It extracts information from frontal view of vehicles for vehicle make and model recognition.

  15. Structure and mechanism for DNA lesion recognition

    Institute of Scientific and Technical Information of China (English)

    Wei Yang

    2008-01-01

    A fundamental question in DNA repair is how a lesion is detected when embedded in millions to billions of normal base pairs. Extensive structural and functional studies reveal atomic details of DNA repair protein and nucleic acid interactions. This review summarizes seemingly diverse structural motifs used in lesion recognition and suggests a general mechanism to recognize DNA lesion by the poor base stacking. After initial recognition of this shared struc-tural feature of lesions, different DNA repair pathways use unique verification mechanisms to ensure correct lesion identification and removal.

  16. FACE RECOGNITION FROM FRONT-VIEW FACE

    Institute of Scientific and Technical Information of China (English)

    WuLifang; ShenLansun

    2003-01-01

    This letter presents a face normalization algorithm based on 2-D face model to rec-ognize faces with variant postures from front-view face.A 2-D face mesh model can be extracted from faces with rotation to left or right and the corresponding front-view mesh model can be estimated according to facial symmetry.Then based on the relationship between the two mesh models,the nrmalized front-view face is formed by gray level mapping.Finally,the face recognition will be finished based on Principal Component Analysis(PCA).Experiments show that better face recognition performance is achieved in this way.

  17. Named entity normalization in user generated content

    NARCIS (Netherlands)

    Jijkoun, V.; Khalid, M.A.; Marx, M.; de Rijke, M.

    2008-01-01

    Named entity recognition is important for semantically oriented retrieval tasks, such as question answering, entity retrieval, biomedical retrieval, trend detection, and event and entity tracking. In many of these tasks it is important to be able to accurately normalize the recognized entities, i.e.

  18. Facial emotion recognition impairments in individuals with HIV.

    Science.gov (United States)

    Clark, Uraina S; Cohen, Ronald A; Westbrook, Michelle L; Devlin, Kathryn N; Tashima, Karen T

    2010-11-01

    Characterized by frontostriatal dysfunction, human immunodeficiency virus (HIV) is associated with cognitive and psychiatric abnormalities. Several studies have noted impaired facial emotion recognition abilities in patient populations that demonstrate frontostriatal dysfunction; however, facial emotion recognition abilities have not been systematically examined in HIV patients. The current study investigated facial emotion recognition in 50 nondemented HIV-seropositive adults and 50 control participants relative to their performance on a nonemotional landscape categorization control task. We examined the relation of HIV-disease factors (nadir and current CD4 levels) to emotion recognition abilities and assessed the psychosocial impact of emotion recognition abnormalities. Compared to control participants, HIV patients performed normally on the control task but demonstrated significant impairments in facial emotion recognition, specifically for fear. HIV patients reported greater psychosocial impairments, which correlated with increased emotion recognition difficulties. Lower current CD4 counts were associated with poorer anger recognition. In summary, our results indicate that chronic HIV infection may contribute to emotion processing problems among HIV patients. We suggest that disruptions of frontostriatal structures and their connections with cortico-limbic networks may contribute to emotion recognition abnormalities in HIV. Our findings also highlight the significant psychosocial impact that emotion recognition abnormalities have on individuals with HIV.

  19. EEG based topography analysis in string recognition task

    Science.gov (United States)

    Ma, Xiaofei; Huang, Xiaolin; Shen, Yuxiaotong; Qin, Zike; Ge, Yun; Chen, Ying; Ning, Xinbao

    2017-03-01

    Vision perception and recognition is a complex process, during which different parts of brain are involved depending on the specific modality of the vision target, e.g. face, character, or word. In this study, brain activities in string recognition task compared with idle control state are analyzed through topographies based on multiple measurements, i.e. sample entropy, symbolic sample entropy and normalized rhythm power, extracted from simultaneously collected scalp EEG. Our analyses show that, for most subjects, both symbolic sample entropy and normalized gamma power in string recognition task are significantly higher than those in idle state, especially at locations of P4, O2, T6 and C4. It implies that these regions are highly involved in string recognition task. Since symbolic sample entropy measures complexity, from the perspective of new information generation, and normalized rhythm power reveals the power distributions in frequency domain, complementary information about the underlying dynamics can be provided through the two types of indices.

  20. Mobile intention recognition

    CERN Document Server

    Kiefer, Peter

    2011-01-01

    Mobile Intention Recognition addresses problems of practical relevance for mobile system engineers: how can we make mobile assistance systems more intelligent? How can we model and recognize patterns of human behavior which span more than a limited spatial context? This text provides an overview on plan and intention recognition, ranging from the late 1970s to very recent approaches. This overview is unique as it discusses approaches with respect to the specificities of mobile intention recognition. This book covers problems from research on mobile assistance systems using methods from artific

  1. PCA facial expression recognition

    Science.gov (United States)

    El-Hori, Inas H.; El-Momen, Zahraa K.; Ganoun, Ali

    2013-12-01

    This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. The comparative study of Facial Expression Recognition (FER) techniques namely Principal Component's analysis (PCA) and PCA with Gabor filters (GF) is done. The objective of this research is to show that PCA with Gabor filters is superior to the first technique in terms of recognition rate. To test and evaluates their performance, experiments are performed using real database by both techniques. The universally accepted five principal emotions to be recognized are: Happy, Sad, Disgust and Angry along with Neutral. The recognition rates are obtained on all the facial expressions.

  2. Handbook of Face Recognition

    CERN Document Server

    Li, Stan Z

    2011-01-01

    This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational face recognition systems. After a thorough introductory chapter, each of the following chapters focus on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Features: fully updated, revised and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated face detection and recognition systems

  3. Hand Gesture Recognition Based on Improved FRNN

    Institute of Scientific and Technical Information of China (English)

    TENG Xiao-long; WANG Xiang-yang; LIU Chong-qing

    2005-01-01

    The trained Gaussian mixture model is used to make skincolour segmentation for the input image sequences. The hand gesture region is extracted, and the relative normalization images are obtained by interpolation operation. To solve the problem of hand gesture recognition, Fuzzy-Rough based nearest neighbour (FRNN) algorithm is applied for classification. For avoiding the costly compute, an improved nearest neighbour classification algorithm based on fuzzy-rough set theory (FRNNC) is proposed. The algorithm employs the represented cluster points instead of the whole training samples, and takes the hand gesture data's fuzziness and the roughness into account, so the compute spending is decreased and the recognition rate is increased. The 30 gestures in Chinese sign language alphabet are used for approving the effectiveness of the proposed algorithm. The recognition rate is 94.96%, which is better than that of KNN (K nearest neighbor)and Fuzzy-KNN (Fuzzy K nearest neighbor).

  4. Arabic Alphabet and Numbers Sign Language Recognition

    Directory of Open Access Journals (Sweden)

    Mahmoud Zaki Abdo

    2015-11-01

    Full Text Available This paper introduces an Arabic Alphabet and Numbers Sign Language Recognition (ArANSLR. It facilitates the communication between the deaf and normal people by recognizing the alphabet and numbers signs of Arabic sign language to text or speech. To achieve this target, the system able to visually recognize gestures from hand image input. The proposed algorithm uses hand geometry and the different shape of a hand in each sign for classifying letters shape by using Hidden Markov Model (HMM. Experiments on real-world datasets showed that the proposed algorithm for Arabic alphabet and numbers sign language recognition is suitability and reliability compared with other competitive algorithms. The experiment results show that the increasing of the gesture recognition rate depends on the increasing of the number of zones by dividing the rectangle surrounding the hand.

  5. Machine Recognition vs Human Recognition of Voices

    Science.gov (United States)

    2012-05-01

    recognized. The accuracy of speaker recognition for disyllables was 87%. For monosyllables, it was 81%, consonant- vowel excerpts were 63%, and... vowel excerpts were 56%. Thus, they demonstrated that the identification performance decreased as the number of phonemes decreased. In [2], the...will still sound natural and the performance of listeners could be tied directly to the degradation of particular frequencies. If the performance

  6. Work and Recognition

    DEFF Research Database (Denmark)

    Willig, Rasmus

    2004-01-01

    individual and collective identity formation and has led to an increase in social pathological illnesses such as stress and depression. By juxtaposing these analyses with Honneth’s theory on recognition, we conclude that the contemporary logic of work is unable to provide adequate forms of recognition......The article deals with the relationship between work and recognition, taking Axel Honneth’s social-philosophical theory of the struggle for recognition as its point of departure. In order to give sociological substance to Honneth’s theory, we turn to three contemporary social theorists - Jean......-Pierre Le Goff, Christophe Dejours and Emmanuel Renault. In spite of many differences, their work is united by a critical description of the logic of work and its consequences for individual individuation. These theorists agree that the growth of autonomy, flexibility and mobility has destabilised...

  7. Recognition receptors in biosensors

    CERN Document Server

    Zourob, Mohammed

    2010-01-01

    This book presents a significant and up-to-date review of the various recognition receptors, their immobilization, and an overview of the used surface characterization techniques. It includes more than 150 illustrations that help explain the ideas presented.

  8. Human Emotion Recognition System

    Directory of Open Access Journals (Sweden)

    Dilbag Singh

    2012-08-01

    Full Text Available This paper discusses the application of feature extraction of facial expressions with combination of neural network for the recognition of different facial emotions (happy, sad, angry, fear, surprised, neutral etc... Humans are capable of producing thousands of facial actions during communication that vary in complexity, intensity, and meaning. This paper analyses the limitations with existing system Emotion recognition using brain activity. In this paper by using an existing simulator I have achieved 97 percent accurate results and it is easy and simplest way than Emotion recognition using brain activity system. Purposed system depends upon human face as we know face also reflects the human brain activities or emotions. In this paper neural network has been used for better results. In the end of paper comparisons of existing Human Emotion Recognition System has been made with new one.

  9. Forensic speaker recognition

    NARCIS (Netherlands)

    Meuwly, Didier

    2009-01-01

    The aim of forensic speaker recognition is to establish links between individuals and criminal activities, through audio speech recordings. This field is multidisciplinary, combining predominantly phonetics, linguistics, speech signal processing, and forensic statistics. On these bases, expert-based

  10. Work and Recognition

    DEFF Research Database (Denmark)

    Willig, Rasmus

    2004-01-01

    individual and collective identity formation and has led to an increase in social pathological illnesses such as stress and depression. By juxtaposing these analyses with Honneth’s theory on recognition, we conclude that the contemporary logic of work is unable to provide adequate forms of recognition......The article deals with the relationship between work and recognition, taking Axel Honneth’s social-philosophical theory of the struggle for recognition as its point of departure. In order to give sociological substance to Honneth’s theory, we turn to three contemporary social theorists - Jean......-Pierre Le Goff, Christophe Dejours and Emmanuel Renault. In spite of many differences, their work is united by a critical description of the logic of work and its consequences for individual individuation. These theorists agree that the growth of autonomy, flexibility and mobility has destabilised...

  11. Evaluating music emotion recognition

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do...... not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER system, and conclude with recommendations....

  12. Harmonization versus Mutual Recognition

    DEFF Research Database (Denmark)

    Jørgensen, Jan Guldager; Schröder, Philipp

    The present paper examines trade liberalization driven by the coordination of product standards. For oligopolistic firms situated in separate markets that are initially sheltered by national standards, mutual recognition of standards implies entry and reduced profits at home paired......, harmonized standards may fail to harvest the full pro-competitive effects from trade liberalization compared to mutual recognition; moreover, the issue is most pronounced in markets featuring price competition....

  13. The Recognition Of Fatigue

    DEFF Research Database (Denmark)

    Elsass, Peter; Jensen, Bodil; Mørup, Rikke;

    2007-01-01

    Elsass P., Jensen B., Morup R., Thogersen M.H. (2007). The Recognition Of Fatigue: A qualitative study of life-stories from rehabilitation clients. International Journal of Psychosocial Rehabilitation. 11 (2), 75-87......Elsass P., Jensen B., Morup R., Thogersen M.H. (2007). The Recognition Of Fatigue: A qualitative study of life-stories from rehabilitation clients. International Journal of Psychosocial Rehabilitation. 11 (2), 75-87...

  14. Relationship between speech recognition in noise and sparseness.

    Science.gov (United States)

    Li, Guoping; Lutman, Mark E; Wang, Shouyan; Bleeck, Stefan

    2012-02-01

    Established methods for predicting speech recognition in noise require knowledge of clean speech signals, placing limitations on their application. The study evaluates an alternative approach based on characteristics of noisy speech, specifically its sparseness as represented by the statistic kurtosis. Experiments 1 and 2 involved acoustic analysis of vowel-consonant-vowel (VCV) syllables in babble noise, comparing kurtosis, glimpsing areas, and extended speech intelligibility index (ESII) of noisy speech signals with one another and with pre-existing speech recognition scores. Experiment 3 manipulated kurtosis of VCV syllables and investigated effects on speech recognition scores in normal-hearing listeners. Pre-existing speech recognition data for Experiments 1 and 2; seven normal-hearing participants for Experiment 3. Experiments 1 and 2 demonstrated that kurtosis calculated in the time-domain from noisy speech is highly correlated (r > 0.98) with established prediction models: glimpsing and ESII. All three measures predicted speech recognition scores well. The final experiment showed a clear monotonic relationship between speech recognition scores and kurtosis. Speech recognition performance in noise is closely related to the sparseness (kurtosis) of the noisy speech signal, at least for the types of speech and noise used here and for listeners with normal hearing.

  15. Why recognition is rational

    Directory of Open Access Journals (Sweden)

    Clintin P. Davis-Stober

    2010-07-01

    Full Text Available The Recognition Heuristic (Gigerenzer and Goldstein, 1996; Goldstein and Gigerenzer, 2002 makes the counter-intuitive prediction that a decision maker utilizing less information may do as well as, or outperform, an idealized decision maker utilizing more information. We lay a theoretical foundation for the use of single-variable heuristics such as the Recognition Heuristic as an optimal decision strategy within a linear modeling framework. We identify conditions under which over-weighting a single predictor is a mini-max strategy among a class of a priori chosen weights based on decision heuristics with respect to a measure of statistical lack of fit we call ``risk''. These strategies, in turn, outperform standard multiple regression as long as the amount of data available is limited. We also show that, under related conditions, weighting only one variable and ignoring all others produces the same risk as ignoring the single variable and weighting all others. This approach has the advantage of generalizing beyond the original environment of the Recognition Heuristic to situations with more than two choice options, binary or continuous representations of recognition, and to other single variable heuristics. We analyze the structure of data used in some prior recognition tasks and find that it matches the sufficient conditions for optimality in our results. Rather than being a poor or adequate substitute for a compensatory model, the Recognition Heuristic closely approximates an optimal strategy when a decision maker has finite data about the world.

  16. Texture based iris recognition system

    Science.gov (United States)

    Mehrotra, Hunny; Gupta, Phalguni; Kaushik, Anil K.

    2008-04-01

    The paper proposes an efficient iris recognition algorithm, obtained through the fusion of Haar Wavelet and Circular Mellin operator. The recognition system preprocesses the captured iris image to remove the effect of holes or spot of light lying on the pupillary region which creates problem in pupil localization. The processed image is localized by detecting inner and outer boundaries from the pupil center using maximum value of the spectrum image. Then the eyelids are detected by fitting a 3 rd degree polynomial on the suitable edge segments and removing the region occluded by eyelids from the normalized iris image. The features for the iris pattern are extracted using Haar Wavelet and Circular Mellin operator. The Haar Wavelet decomposition reduces the size of feature vector while Circular Mellin operator is used for rotation and scale invariant feature extraction. The features are compared using Hamming Distance method and the fusion is done at decision level using Conjunction rule. The recognizer is found to be more robust with accuracy level more than 95%.

  17. Normal Pressure Hydrocephalus (NPH)

    Science.gov (United States)

    ... your local chapter Join our online community Normal Pressure Hydrocephalus (NPH) Normal pressure hydrocephalus is a brain ... About Symptoms Diagnosis Causes & risks Treatments About Normal Pressure Hydrocephalus Normal pressure hydrocephalus occurs when excess cerebrospinal ...

  18. Recognition memory in developmental prosopagnosia: electrophysiological evidence for abnormal routes to face recognition.

    Science.gov (United States)

    Burns, Edwin J; Tree, Jeremy J; Weidemann, Christoph T

    2014-01-01

    DUAL PROCESS MODELS OF RECOGNITION MEMORY PROPOSE TWO DISTINCT ROUTES FOR RECOGNIZING A FACE: recollection and familiarity. Recollection is characterized by the remembering of some contextual detail from a previous encounter with a face whereas familiarity is the feeling of finding a face familiar without any contextual details. The Remember/Know (R/K) paradigm is thought to index the relative contributions of recollection and familiarity to recognition performance. Despite researchers measuring face recognition deficits in developmental prosopagnosia (DP) through a variety of methods, none have considered the distinct contributions of recollection and familiarity to recognition performance. The present study examined recognition memory for faces in eight individuals with DP and a group of controls using an R/K paradigm while recording electroencephalogram (EEG) data at the scalp. Those with DP were found to produce fewer correct "remember" responses and more false alarms than controls. EEG results showed that posterior "remember" old/new effects were delayed and restricted to the right posterior (RP) area in those with DP in comparison to the controls. A posterior "know" old/new effect commonly associated with familiarity for faces was only present in the controls whereas individuals with DP exhibited a frontal "know" old/new effect commonly associated with words, objects and pictures. These results suggest that individuals with DP do not utilize normal face-specific routes when making face recognition judgments but instead process faces using a pathway more commonly associated with objects.

  19. Recognition Memory in Developmental Prosopagnosia: Electrophysiological Evidence for Abnormal Routes to Face Recognition

    Directory of Open Access Journals (Sweden)

    Edwin James Burns

    2014-08-01

    Full Text Available Dual process models of recognition memory propose two distinct routes for recognizing a face: recollection and familiarity. Recollection is characterized by the remembering of some contextual detail from a previous encounter with a face whereas familiarity is the feeling of finding a face familiar without any contextual details. The Remember/Know (R/K paradigm is thought to index the relative contributions of recollection and familiarity to recognition performance. Despite researchers measuring face recognition deficits in developmental prosopagnosia (DP through a variety of methods, none have considered the distinct contributions of recollection and familiarity to recognition performance. The present study examined recognition memory for faces in 8 individuals with DP and a group of controls using an R/K paradigm while recording electroencephalogram (EEG data at scalp. Those with DP were found to produce fewer correct remember responses and more false alarms than controls. EEG results showed that posterior remember old/new effects were delayed and restricted to the right posterior area in those with DP in comparison to the controls. A posterior know old/new effect commonly associated with familiarity for faces was only present in the controls whereas individuals with DP exhibited a frontal know old/new effect commonly associated with words, objects and pictures. These results suggest that individuals with DP do not utilize normal face specific routes when making face recognition judgments but instead process faces using a pathway more commonly associated with objects.

  20. Character-based Recognition of Simple Word Gesture

    Directory of Open Access Journals (Sweden)

    Paulus Insap Santosa

    2013-11-01

    Full Text Available People with normal senses use spoken language to communicate with others. This method cannot be used by those with hearing and speech impaired. These two groups of people will have difficulty when they try to communicate to each other using their own language. Sign language is not easy to learn, as there are various sign languages, and not many tutors are available. This research focused on a simple word recognition gesture based on characters that form a word to be recognized. The method used for character recognition was the nearest neighbour method. This method identified different fingers using the different markers attached to each finger. Testing a simple word gesture recognition is done by providing a series of characters that make up the intended simple word. The accuracy of a simple word gesture recognition depended upon the accuracy of recognition of each character.

  1. Ear recognition based on Gabor features and KFDA.

    Science.gov (United States)

    Yuan, Li; Mu, Zhichun

    2014-01-01

    We propose an ear recognition system based on 2D ear images which includes three stages: ear enrollment, feature extraction, and ear recognition. Ear enrollment includes ear detection and ear normalization. The ear detection approach based on improved Adaboost algorithm detects the ear part under complex background using two steps: offline cascaded classifier training and online ear detection. Then Active Shape Model is applied to segment the ear part and normalize all the ear images to the same size. For its eminent characteristics in spatial local feature extraction and orientation selection, Gabor filter based ear feature extraction is presented in this paper. Kernel Fisher Discriminant Analysis (KFDA) is then applied for dimension reduction of the high-dimensional Gabor features. Finally distance based classifier is applied for ear recognition. Experimental results of ear recognition on two datasets (USTB and UND datasets) and the performance of the ear authentication system show the feasibility and effectiveness of the proposed approach.

  2. Ear Recognition Based on Gabor Features and KFDA

    Directory of Open Access Journals (Sweden)

    Li Yuan

    2014-01-01

    Full Text Available We propose an ear recognition system based on 2D ear images which includes three stages: ear enrollment, feature extraction, and ear recognition. Ear enrollment includes ear detection and ear normalization. The ear detection approach based on improved Adaboost algorithm detects the ear part under complex background using two steps: offline cascaded classifier training and online ear detection. Then Active Shape Model is applied to segment the ear part and normalize all the ear images to the same size. For its eminent characteristics in spatial local feature extraction and orientation selection, Gabor filter based ear feature extraction is presented in this paper. Kernel Fisher Discriminant Analysis (KFDA is then applied for dimension reduction of the high-dimensional Gabor features. Finally distance based classifier is applied for ear recognition. Experimental results of ear recognition on two datasets (USTB and UND datasets and the performance of the ear authentication system show the feasibility and effectiveness of the proposed approach.

  3. Amygdala damage impairs emotion recognition from music.

    Science.gov (United States)

    Gosselin, Nathalie; Peretz, Isabelle; Johnsen, Erica; Adolphs, Ralph

    2007-01-28

    The role of the amygdala in recognition of danger is well established for visual stimuli such as faces. A similar role in another class of emotionally potent stimuli -- music -- has been recently suggested by the study of epileptic patients with unilateral resection of the anteromedian part of the temporal lobe [Gosselin, N., Peretz, I., Noulhiane, M., Hasboun, D., Beckett, C., & Baulac, M., et al. (2005). Impaired recognition of scary music following unilateral temporal lobe excision. Brain, 128(Pt 3), 628-640]. The goal of the present study was to assess the specific role of the amygdala in the recognition of fear from music. To this aim, we investigated a rare subject, S.M., who has complete bilateral damage relatively restricted to the amygdala and not encompassing other sectors of the temporal lobe. In Experiment 1, S.M. and four matched controls were asked to rate the intensity of fear, peacefulness, happiness, and sadness from computer-generated instrumental music purposely created to express those emotions. Subjects also rated the arousal and valence of each musical stimulus. An error detection task assessed basic auditory perceptual function. S.M. performed normally in this perceptual task, but was selectively impaired in the recognition of scary and sad music. In contrast, her recognition of happy music was normal. Furthermore, S.M. judged the scary music to be less arousing and the peaceful music less relaxing than did the controls. Overall, the pattern of impairment in S.M. is similar to that previously reported in patients with unilateral anteromedial temporal lobe damage. S.M.'s impaired emotional judgments occur in the face of otherwise intact processing of musical features that are emotionally determinant. The use of tempo and mode cues in distinguishing happy from sad music was also spared in S.M. Thus, the amygdala appears to be necessary for emotional processing of music rather than the perceptual processing itself.

  4. Recognition as care

    DEFF Research Database (Denmark)

    Ahlmark, Nanna; Whyte, Susan Reynolds; Harting, Janneke

    2014-01-01

    This longitudinal study provides critical insight into the social processes of municipal diabetes training for Arabic-speaking immigrants in Denmark focusing on participants’ experiences. Our study builds on observations of three diabetes courses and 36 interviews with participants at the start of......-based and solidarity-based recognition to analyse what was at stake in these experiences, and we engage Annemarie Mol’s concept of a logic of care to show how recognition unfolded practically during the training. We propose that participants’ wider social context and experiences of misrecognition situated the training...

  5. Character Recognition (Devanagari Script

    Directory of Open Access Journals (Sweden)

    Ankita Karia

    2015-04-01

    Full Text Available Character Recognition is has found major interest in field of research and practical application to analyze and study characters in different languages using image as their input. In this paper the user writes the Devanagari character using mouse as a plotter and then the corresponding character is saved in the form of image. This image is processed using Optical Character Recognition in which location, segmentation, pre-processing of image is done. Later Neural Networks is used to identify all the characters by the further process of OCR i.e. by using feature extraction and post-processing of image. This entire process is done using MATLAB.

  6. Touchless palmprint recognition systems

    CERN Document Server

    Genovese, Angelo; Scotti, Fabio

    2014-01-01

    This book examines the context, motivation and current status of biometric systems based on the palmprint, with a specific focus on touchless and less-constrained systems. It covers new technologies in this rapidly evolving field and is one of the first comprehensive books on palmprint recognition systems.It discusses the research literature and the most relevant industrial applications of palmprint biometrics, including the low-cost solutions based on webcams. The steps of biometric recognition are described in detail, including acquisition setups, algorithms, and evaluation procedures. Const

  7. FUNDAMENTALS OF SPEAKER RECOGNITION

    Directory of Open Access Journals (Sweden)

    Figen ERTAŞ

    2000-02-01

    Full Text Available The explosive growth of information technology in the last decade has made a considerable impact on the design and construction of systems for human-machine communication, which is becoming increasingly important in many aspects of life. Amongst other speech processing tasks, a great deal of attention has been devoted to developing procedures that identify people from their voices, and the design and construction of speaker recognition systems has been a fascinating enterprise pursued over many decades. This paper introduces speaker recognition in general and discusses its relevant parameters in relation to system performance.

  8. Normalization: A Preprocessing Stage

    OpenAIRE

    Patro, S. Gopal Krishna; Sahu, Kishore Kumar

    2015-01-01

    As we know that the normalization is a pre-processing stage of any type problem statement. Especially normalization takes important role in the field of soft computing, cloud computing etc. for manipulation of data like scale down or scale up the range of data before it becomes used for further stage. There are so many normalization techniques are there namely Min-Max normalization, Z-score normalization and Decimal scaling normalization. So by referring these normalization techniques we are ...

  9. Eye movements during object recognition in visual agnosia.

    Science.gov (United States)

    Charles Leek, E; Patterson, Candy; Paul, Matthew A; Rafal, Robert; Cristino, Filipe

    2012-07-01

    This paper reports the first ever detailed study about eye movement patterns during single object recognition in visual agnosia. Eye movements were recorded in a patient with an integrative agnosic deficit during two recognition tasks: common object naming and novel object recognition memory. The patient showed normal directional biases in saccades and fixation dwell times in both tasks and was as likely as controls to fixate within object bounding contour regardless of recognition accuracy. In contrast, following initial saccades of similar amplitude to controls, the patient showed a bias for short saccades. In object naming, but not in recognition memory, the similarity of the spatial distributions of patient and control fixations was modulated by recognition accuracy. The study provides new evidence about how eye movements can be used to elucidate the functional impairments underlying object recognition deficits. We argue that the results reflect a breakdown in normal functional processes involved in the integration of shape information across object structure during the visual perception of shape.

  10. Pattern recognition of abnormal left ventricle wall motion in cardiac MR.

    Science.gov (United States)

    Lu, Yingli; Radau, Perry; Connelly, Kim; Dick, Alexander; Wright, Graham

    2009-01-01

    There are four main problems that limit application of pattern recognition techniques for recognition of abnormal cardiac left ventricle (LV) wall motion: (1) Normalization of the LV's size, shape, intensity level and position; (2) defining a spatial correspondence between phases and subjects; (3) extracting features; (4) and discriminating abnormal from normal wall motion. Solving these four problems is required for application of pattern recognition techniques to classify the normal and abnormal LV wall motion. In this work, we introduce a normalization scheme to solve the first and second problems. With this scheme, LVs are normalized to the same position, size, and intensity level. Using the normalized images, we proposed an intra-segment classification criterion based on a correlation measure to solve the third and fourth problems. Application of the method to recognition of abnormal cardiac MR LV wall motion showed promising results.

  11. [Prosopagnosia and facial expression recognition].

    Science.gov (United States)

    Koyama, Shinichi

    2014-04-01

    This paper reviews clinical neuropsychological studies that have indicated that the recognition of a person's identity and the recognition of facial expressions are processed by different cortical and subcortical areas of the brain. The fusiform gyrus, especially the right fusiform gyrus, plays an important role in the recognition of identity. The superior temporal sulcus, amygdala, and medial frontal cortex play important roles in facial-expression recognition. Both facial recognition and facial-expression recognition are highly intellectual processes that involve several regions of the brain.

  12. Automatic anatomy recognition on CT images with pathology

    Science.gov (United States)

    Huang, Lidong; Udupa, Jayaram K.; Tong, Yubing; Odhner, Dewey; Torigian, Drew A.

    2016-03-01

    Body-wide anatomy recognition on CT images with pathology becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem because various diseases result in various abnormalities of objects such as shape and intensity patterns. We previously developed an automatic anatomy recognition (AAR) system [1] whose applicability was demonstrated on near normal diagnostic CT images in different body regions on 35 organs. The aim of this paper is to investigate strategies for adapting the previous AAR system to diagnostic CT images of patients with various pathologies as a first step toward automated body-wide disease quantification. The AAR approach consists of three main steps - model building, object recognition, and object delineation. In this paper, within the broader AAR framework, we describe a new strategy for object recognition to handle abnormal images. In the model building stage an optimal threshold interval is learned from near-normal training images for each object. This threshold is optimally tuned to the pathological manifestation of the object in the test image. Recognition is performed following a hierarchical representation of the objects. Experimental results for the abdominal body region based on 50 near-normal images used for model building and 20 abnormal images used for object recognition show that object localization accuracy within 2 voxels for liver and spleen and 3 voxels for kidney can be achieved with the new strategy.

  13. Multi—pose Color Face Recognition in a Complex Background

    Institute of Scientific and Technical Information of China (English)

    ZHUChangren; WANGRunsheng

    2003-01-01

    Face recognition has wider application fields. In recurrent references, most of the algorithms that deal with the face recognition in the static images are with simple background, and only used for ID picture recogni-tion. It is necessary to study the whole process of multi-pose face recognition in a clutter background. In this pa-per an automatic multi-pose face recognition system with multi-feature is proposed. It consists of several steps: face detection, detection and location of the face organs, feature extraction for recognition, recognition decision. In face de-tection the combination of skin-color and multi-verification which consists of the analysis of the shape, local organ fea-tures and head model is applied to improve the perfor-mance. In detection and location of the face organ feature points, with the analysis of multiple features and their pro-jections, the combination of an iterative search with a con-fidence function and template matching at the candidate points is adopted to improve the performance of accuracy and speed. In feature extraction for recognition, geome-try normalization based on three-point afflne transform is adopted to conserve the information to a maximum con-tent before the feature extraction of principal component analysis (PCA). In recognition decision, a hierarchical face model with the division of the face poses is introduced to reduce its retrieval space and thus to cut its time consump-tion. In addition, a fusion decision is applied to improve the face recognition performance. Also, pose recognition result can be got simultaneously. The new approach is ap-plied to 420 color images which consist of multi-pose faces with two visible eyes in a complex background, and the results are satisfactory.

  14. Recognition of Face and Emotional Facial Expressions in Autism

    Directory of Open Access Journals (Sweden)

    Muhammed Tayyib Kadak

    2013-03-01

    Full Text Available Autism is a genetically transferred neurodevelopmental disorder characterized by severe and permanent deficits in many interpersonal relation areas like communication, social interaction and emotional responsiveness. Patients with autism have deficits in face recognition, eye contact and recognition of emotional expression. Both recognition of face and expression of facial emotion carried on face processing. Structural and functional impairment in fusiform gyrus, amygdala, superior temporal sulcus and other brain regions lead to deficits in recognition of face and facial emotion. Therefore studies suggest that face processing deficits resulted in problems in areas of social interaction and emotion in autism. Studies revealed that children with autism had problems in recognition of facial expression and used mouth region more than eye region. It was also shown that autistic patients interpreted ambiguous expressions as negative emotion. In autism, deficits related in various stages of face processing like detection of gaze, face identity, recognition of emotional expression were determined, so far. Social interaction impairments in autistic spectrum disorders originated from face processing deficits during the periods of infancy, childhood and adolescence. Recognition of face and expression of facial emotion could be affected either automatically by orienting towards faces after birth, or by “learning” processes in developmental periods such as identity and emotion processing. This article aimed to review neurobiological basis of face processing and recognition of emotional facial expressions during normal development and in autism.

  15. Word Recognition for Temporally and Spectrally Distorted Materials

    DEFF Research Database (Denmark)

    Smith, Sherri L.; Pichora-Fuller, Margaret Kathleen; Wilson, Richard H.

    2012-01-01

    Objectives: The purpose of Experiment 1 was to measure word recognition in younger adults with normal hearing when speech or babble was temporally or spectrally distorted. In Experiment 2, older listeners with near-normal hearing and with hearing loss (for pure tones) were tested to evaluate...... their susceptibility to changes in speech level and distortion types. The results across groups and listening conditions were compared to assess the extent to which the effects of the distortions on word recognition resembled the effects of age-related differences in auditory processing or pure-tone hearing loss...... were evaluated in four conditions using the Words-in-Noise test in combinations of unaltered or jittered speech and unaltered or jittered babble. In Experiment 2, word recognition in quiet and in babble was measured in 72 older adults with near-normal hearing and 72 older adults with hearing loss...

  16. Tolerance and recognition

    Directory of Open Access Journals (Sweden)

    Hans Marius Hansteen

    2014-12-01

    Full Text Available Even though “toleration” and “recognition” designate opposing attitudes (to tolerate something, implies a negative stance towards it, whereas recognition seems to imply a positive one, the concepts do not constitute mutually exclusive alternatives. However, “toleration” is often associated with liberal universalism, focusing on individual rights, whereas “recognition” often connotes communitarian perspectives, focusing on relations and identity. This paper argues that toleration may be founded on recognition, and that recognition may imply toleration. In outlining a differentiated understanding of the relationship between toleration and recognition, it seems apt to avoid an all-to-general dichotomy between universalism and particularism or, in other words, to reach beyond the debate between liberalism and communitarianism in political philosophy.The paper takes as its starting point the view that the discussion on toleration and diversity in intercultural communication is one of the contexts where it seems important to get beyond the liberal/communitarian dichotomy. Some basic features of Rainer Forst’s theory of toleration and Axel Honneth’s theory of the struggle for recognition are presented, in order to develop a more substantial understanding of the relationship between the concepts of toleration and recognition. One lesson from Forst is that toleration is a normatively dependent concept, i.e., that it is impossible to deduce principles for toleration and its limits from a theory of toleration as such. A central lesson from Honneth is that recognition – understood as a basic human need – is always conflictual and therefore dynamic.Accordingly, a main point in the paper is that the theory of struggles for and about recognition (where struggles for designates struggles within an established order of recognition, and struggles about designates struggles that challenge established orders of recognition may clarify what

  17. Automatic object recognition

    Science.gov (United States)

    Ranganath, H. S.; Mcingvale, Pat; Sage, Heinz

    1988-01-01

    Geometric and intensity features are very useful in object recognition. An intensity feature is a measure of contrast between object pixels and background pixels. Geometric features provide shape and size information. A model based approach is presented for computing geometric features. Knowledge about objects and imaging system is used to estimate orientation of objects with respect to the line of sight.

  18. Facial Expression Recognition

    NARCIS (Netherlands)

    Pantic, Maja; Li, S.; Jain, A.

    2009-01-01

    Facial expression recognition is a process performed by humans or computers, which consists of: 1. Locating faces in the scene (e.g., in an image; this step is also referred to as face detection), 2. Extracting facial features from the detected face region (e.g., detecting the shape of facial

  19. Recognition of fractal graphs

    NARCIS (Netherlands)

    Perepelitsa, VA; Sergienko, [No Value; Kochkarov, AM

    1999-01-01

    Definitions of prefractal and fractal graphs are introduced, and they are used to formulate mathematical models in different fields of knowledge. The topicality of fractal-graph recognition from the point of view, of fundamental improvement in the efficiency of the solution of algorithmic problems i

  20. Automatic aircraft recognition

    Science.gov (United States)

    Hmam, Hatem; Kim, Jijoong

    2002-08-01

    Automatic aircraft recognition is very complex because of clutter, shadows, clouds, self-occlusion and degraded imaging conditions. This paper presents an aircraft recognition system, which assumes from the start that the image is possibly degraded, and implements a number of strategies to overcome edge fragmentation and distortion. The current vision system employs a bottom up approach, where recognition begins by locating image primitives (e.g., lines and corners), which are then combined in an incremental fashion into larger sets of line groupings using knowledge about aircraft, as viewed from a generic viewpoint. Knowledge about aircraft is represented in the form of whole/part shape description and the connectedness property, and is embedded in production rules, which primarily aim at finding instances of the aircraft parts in the image and checking the connectedness property between the parts. Once a match is found, a confidence score is assigned and as evidence in support of an aircraft interpretation is accumulated, the score is increased proportionally. Finally a selection of the resulting image interpretations with the highest scores, is subjected to competition tests, and only non-ambiguous interpretations are allowed to survive. Experimental results demonstrating the effectiveness of the current recognition system are given.

  1. Pattern recognition in bioinformatics.

    Science.gov (United States)

    de Ridder, Dick; de Ridder, Jeroen; Reinders, Marcel J T

    2013-09-01

    Pattern recognition is concerned with the development of systems that learn to solve a given problem using a set of example instances, each represented by a number of features. These problems include clustering, the grouping of similar instances; classification, the task of assigning a discrete label to a given instance; and dimensionality reduction, combining or selecting features to arrive at a more useful representation. The use of statistical pattern recognition algorithms in bioinformatics is pervasive. Classification and clustering are often applied to high-throughput measurement data arising from microarray, mass spectrometry and next-generation sequencing experiments for selecting markers, predicting phenotype and grouping objects or genes. Less explicitly, classification is at the core of a wide range of tools such as predictors of genes, protein function, functional or genetic interactions, etc., and used extensively in systems biology. A course on pattern recognition (or machine learning) should therefore be at the core of any bioinformatics education program. In this review, we discuss the main elements of a pattern recognition course, based on material developed for courses taught at the BSc, MSc and PhD levels to an audience of bioinformaticians, computer scientists and life scientists. We pay attention to common problems and pitfalls encountered in applications and in interpretation of the results obtained.

  2. Whole-book recognition.

    Science.gov (United States)

    Xiu, Pingping; Baird, Henry S

    2012-12-01

    Whole-book recognition is a document image analysis strategy that operates on the complete set of a book's page images using automatic adaptation to improve accuracy. We describe an algorithm which expects to be initialized with approximate iconic and linguistic models--derived from (generally errorful) OCR results and (generally imperfect) dictionaries--and then, guided entirely by evidence internal to the test set, corrects the models which, in turn, yields higher recognition accuracy. The iconic model describes image formation and determines the behavior of a character-image classifier, and the linguistic model describes word-occurrence probabilities. Our algorithm detects "disagreements" between these two models by measuring cross entropy between 1) the posterior probability distribution of character classes (the recognition results resulting from image classification alone) and 2) the posterior probability distribution of word classes (the recognition results from image classification combined with linguistic constraints). We show how disagreements can identify candidates for model corrections at both the character and word levels. Some model corrections will reduce the error rate over the whole book, and these can be identified by comparing model disagreements, summed across the whole book, before and after the correction is applied. Experiments on passages up to 180 pages long show that when a candidate model adaptation reduces whole-book disagreement, it is also likely to correct recognition errors. Also, the longer the passage operated on by the algorithm, the more reliable this adaptation policy becomes, and the lower the error rate achieved. The best results occur when both the iconic and linguistic models mutually correct one another. We have observed recognition error rates driven down by nearly an order of magnitude fully automatically without supervision (or indeed without any user intervention or interaction). Improvement is nearly monotonic, and

  3. A Proposed Arabic Handwritten Text Normalization Method

    Directory of Open Access Journals (Sweden)

    Tarik Abu-Ain

    2014-11-01

    Full Text Available Text normalization is an important technique in document image analysis and recognition. It consists of many preprocessing stages, which include slope correction, text padding, skew correction, and straight the writing line. In this side, text normalization has an important role in many procedures such as text segmentation, feature extraction and characters recognition. In the present article, a new method for text baseline detection, straightening, and slant correction for Arabic handwritten texts is proposed. The method comprises a set of sequential steps: first components segmentation is done followed by components text thinning; then, the direction features of the skeletons are extracted, and the candidate baseline regions are determined. After that, selection of the correct baseline region is done, and finally, the baselines of all components are aligned with the writing line.  The experiments are conducted on IFN/ENIT benchmark Arabic dataset. The results show that the proposed method has a promising and encouraging performance.

  4. Autonomy and Recognition

    Directory of Open Access Journals (Sweden)

    Miguel Giusti

    2007-04-01

    Full Text Available Resumen:El presente ensayo contiene dos partes. En la primera se hace una breve descripción de las carencias de la reflexión moral a las que parece venir al encuentro el concepto de reconocimiento. Charles Taylor y Axel Honneth, protagonistas en estos debates, dan buenas razones para dirigir la discusión hacia el tema del reconocimiento, pero no coinciden ni en su definición, ni en el modo de recuperar la tesis de Hegel, ni tampoco en la forma de tratar la relación entre autonomía y reconocimiento. En la segunda parte se analiza la concepción propiamente hegeliana, con la intención de destacar el nexo esencial, no la ruptura, que existe entre la noción de reconocimiento y el modelo conceptual de la voluntad libre o del espíritu. Abstract:This essay is divided into two parts. The first one is a short description of the deficiencies of moral reflection, which seem to lead the discussion towards the concept of recognition. Charles Taylor and Axel Honneth, two of the protagonists of these debates, give very good reasons for turning the argument towards the issue of recognition, but they do not agree on its definition, on the way to recover the Hegelian thesis, or on how to approach the relationship between autonomy and recognition. The second part constitutes an analysis of the Hegelian conception of recognition, in order to highlight the essential link –rather than the rupture– between the notion of recognition and the conceptual model of free will or spirit.

  5. Testing for normality

    CERN Document Server

    Thode, Henry C

    2002-01-01

    Describes the selection, design, theory, and application of tests for normality. Covers robust estimation, test power, and univariate and multivariate normality. Contains tests ofr multivariate normality and coordinate-dependent and invariant approaches.

  6. Pattern recognition receptors in antifungal immunity.

    Science.gov (United States)

    Plato, Anthony; Hardison, Sarah E; Brown, Gordon D

    2015-03-01

    Receptors of the innate immune system are the first line of defence against infection, being able to recognise and initiate an inflammatory response to invading microorganisms. The Toll-like (TLR), NOD-like (NLR), RIG-I-like (RLR) and C-type lectin-like receptors (CLR) are four receptor families that contribute to the recognition of a vast range of species, including fungi. Many of these pattern recognition receptors (PRRs) are able to initiate innate immunity and polarise adaptive responses upon the recognition of fungal cell wall components and other conserved molecular patterns, including fungal nucleic acids. These receptors induce effective mechanisms of fungal clearance in normal hosts, but medical interventions, immunosuppression or genetic predisposition can lead to susceptibility to fungal infections. In this review, we highlight the importance of PRRs in fungal infection, specifically CLRs, which are the major PRR involved. We will describe specific PRRs in detail, the importance of receptor collaboration in fungal recognition and clearance, and describe how genetic aberrations in PRRs can contribute to disease pathology.

  7. Stereotype Associations and Emotion Recognition

    NARCIS (Netherlands)

    Bijlstra, Gijsbert; Holland, Rob W.; Dotsch, Ron; Hugenberg, Kurt; Wigboldus, Daniel H. J.

    We investigated whether stereotype associations between specific emotional expressions and social categories underlie stereotypic emotion recognition biases. Across two studies, we replicated previously documented stereotype biases in emotion recognition using both dynamic (Study 1) and static

  8. Galeotti on recognition as inclusion

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2008-01-01

    Anna Elisabetta Galeotti's theory of 'toleration as recognition' has been criticised by Peter Jones for being conceptually incoherent, since liberal toleration presupposes a negative attitude to differences, whereas multicultural recognition requires positive affirmation hereof. The paper spells ...

  9. Research on Normal Human Plantar Pressure Test

    Directory of Open Access Journals (Sweden)

    Liu Xi Yang

    2016-01-01

    Full Text Available FSR400 pressure sensor, nRF905 wireless transceiver and MSP40 SCM are used to design the insole pressure collection system, LabVIEW is used to make HMI of data acquisition, collecting a certain amount of normal human foot pressure data, statistical analysis of pressure distribution relations about five stages of swing phase during walking, using the grid closeness degree to identify plantar pressure distribution pattern recognition, and the algorithm simulation, experimental results demonstrated this method feasible.

  10. RECOGNITION AND ASSESSMENT IN ACCOUNTANCY

    Directory of Open Access Journals (Sweden)

    DIMA FLORIN CONSTANTIN

    2012-11-01

    Full Text Available The recognition and assessment of the component elements of the annual financial statements’ structures is crucial in order that the information released by them fulfils the qualitative characteristics and the reflected image is a “true and fair view”. Therefore, our approach takes into consideration the recognition and assessment methods for the component elements of the financial statements’ structures, as well as certain possible risks arising from the erroneous recognition or non-recognition of some of these elements.

  11. Six Regularities of Source Recognition

    Science.gov (United States)

    Glanzer, Murray; Hilford, Andy; Kim, Kisok

    2004-01-01

    In recent work, researchers have shown that source-recognition memory can be incorporated in an extended signal detection model that covers both it and item-recognition memory (A. Hilford, M. Glanzer, K. Kim, & L. T. DeCarlo, 2002). In 5 experiments, using learning variables that have an established effect on item recognition, the authors tested…

  12. Superficial Priming in Episodic Recognition

    Science.gov (United States)

    Dopkins, Stephen; Sargent, Jesse; Ngo, Catherine T.

    2010-01-01

    We explored the effect of superficial priming in episodic recognition and found it to be different from the effect of semantic priming in episodic recognition. Participants made recognition judgments to pairs of items, with each pair consisting of a prime item and a test item. Correct positive responses to the test item were impeded if the prime…

  13. Word Recognition in Auditory Cortex

    Science.gov (United States)

    DeWitt, Iain D. J.

    2013-01-01

    Although spoken word recognition is more fundamental to human communication than text recognition, knowledge of word-processing in auditory cortex is comparatively impoverished. This dissertation synthesizes current models of auditory cortex, models of cortical pattern recognition, models of single-word reading, results in phonetics and results in…

  14. Supporting Quality Teachers with Recognition

    Science.gov (United States)

    Andrews, Hans A.

    2011-01-01

    Value has been found in providing recognition and awards programs for excellent teachers. Research has also found a major lack of these programs in both the USA and in Australia. Teachers receiving recognition and awards for their teaching have praised recognition programs as providing motivation for them to continue high-level instruction.…

  15. Forensic Face Recognition: A Survey

    NARCIS (Netherlands)

    Ali, Tauseef; Spreeuwers, Luuk; Veldhuis, Raymond; Quaglia, Adamo; Epifano, Calogera M.

    2012-01-01

    The improvements of automatic face recognition during the last 2 decades have disclosed new applications like border control and camera surveillance. A new application field is forensic face recognition. Traditionally, face recognition by human experts has been used in forensics, but now there is a

  16. Differential Inequalities, Normality and Quasi-Normality

    CERN Document Server

    Liu, Xiaojun; Pang, Xuecheng

    2011-01-01

    We prove that if D is a domain in C, alpha>1 and c>0, then the family F of functions meromorphic in D such that |f'(z)|/(1+|f(z)|^alpha)>c for every z in D is normalin D. For alpha=1, the same assumptions imply quasi-normality but not necessarily normality.

  17. Normalized Information Distance is Not Semicomputable

    CERN Document Server

    Terwijn, Sebastiaan A; Vitanyi, Paul M B

    2010-01-01

    Normalized information distance (NID) uses the theoretical notion of Kolmogorov complexity, which for practical purposes is approximated by the length of the compressed version of the file involved, using a real-world compression program. This practical application is called 'normalized compression distance' and it is trivially computable. It is a parameter-free similarity measure based on compression, and is used in pattern recognition, data mining, phylogeny, clustering, and classification. The complexity properties of its theoretical precursor, the NID, have been open. We show that the NID is neither upper semicomputable nor lower semicomputable.

  18. Nonapproximablity of the Normalized Information Distance

    CERN Document Server

    Terwijn, Sebastiaan A; Vitanyi, Paul M B

    2009-01-01

    Normalized information distance (NID) uses the theoretical notion of Kolmogorov complexity, which for practical purposes is approximated by the length of the compressed version of the file involved, using a real-world compression program. This practical application is called `normalized compression distance' and it is trivially computable. It is a parameter-free similarity measure based on compression, and is used in pattern recognition, data mining, phylogeny, clustering, and classification. The complexity properties of its theoretical precursor, the NID, have been open. We show that the NID is neither upper semicomputable nor lower semicomputable up to any reasonable precision.

  19. Effects of emotional and perceptual-motor stress on a voice recognition system's accuracy: An applied investigation

    Science.gov (United States)

    Poock, G. K.; Martin, B. J.

    1984-02-01

    This was an applied investigation examining the ability of a speech recognition system to recognize speakers' inputs when the speakers were under different stress levels. Subjects were asked to speak to a voice recognition system under three conditions: (1) normal office environment, (2) emotional stress, and (3) perceptual-motor stress. Results indicate a definite relationship between voice recognition system performance and the type of low stress reference patterns used to achieve recognition.

  20. Vehicle License Plate Recognition Syst

    Directory of Open Access Journals (Sweden)

    Meenakshi,R. B. Dubey

    2012-12-01

    Full Text Available The vehicle license plate recognition system has greater efficiency for vehicle monitoring in automatic zone access control. This Plate recognition system will avoid special tags, since all vehicles possess a unique registration number plate. A number of techniques have been used for car plate characters recognition. This system uses neural network character recognition and pattern matching of characters as two character recognition techniques. In this approach multilayer feed-forward back-propagation algorithm is used. The performance of the proposed algorithm has been tested on several car plates and provides very satisfactory results.

  1. FUNDAMENTALS OF SPEAKER RECOGNITION

    OpenAIRE

    ERTAŞ, Figen

    2000-01-01

    The explosive growth of information technology in the last decade has made a considerable impact on the design and construction of systems for human-machine communication, which is becoming increasingly important in many aspects of life. Amongst other speech processing tasks, a great deal of attention has been devoted to developing procedures that identify people from their voices, and the design and construction of speaker recognition systems has been a fascinating enterprise pursued over ma...

  2. [Recognition of commensal microflora by pattern recognition receptors in human physiology and pathology].

    Science.gov (United States)

    Bondarenko, V M; Likhoded, V G

    2012-01-01

    Contemporary data on the interaction of commensal microflora and Toll-like pattern recognition receptors are presented. These receptors recognize normal intestine microflora in physiological conditions, and this interaction is necessary for the maintenance of homeostasis and damage reparation of the intestine, for the induction of heat shock cytoprotective proteins. As a side effect in disruption of immunologic tolerance and misbalance of protective immunological mechanisms, multiorgan pathologic changes of organs and tissues may develop, including chronic inflammation processes of various localization.

  3. Pattern Recognition Control Design

    Science.gov (United States)

    Gambone, Elisabeth A.

    2018-01-01

    Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.

  4. Chinese character recognition using simulated phosphene maps.

    Science.gov (United States)

    Zhao, Ying; Lu, Yanyu; Zhou, Chuanqing; Chen, Yao; Ren, Qiushi; Chai, Xinyu

    2011-05-01

    A visual prosthetic device may produce phosphene maps in which individual phosphene characteristics can be altered. This study was an investigation of the ability of normally sighted subjects to recognize Chinese characters (CCs) after altering simulated phosphene maps. Thirty volunteers with normal or corrected visual acuity of 20/20 were recruited. CC recognition accuracy and response time were investigated while one parameter was changed (distortion, pixel dropout percentage, pixel size variability, or pixel gray level) or different combinations of three parameters were used. Five hundred CCs consisting of 1 to 16 strokes were used for the character sets. CC recognition accuracy and response times respectively decreased and increased when distortion, dropout, and pixel size variability increased. Gray levels did not significantly affect the results, except when eight levels were used. To maintain an 80% accuracy rate, there should be a distortion index (k) of no more than 0.2 (irregularity), a pixel dropout of 20%, and a pixel size range of 1 to 16 mm (7-112 min arc). Only a combination of a k=0.1 distortion index, a dropout of 10%, and a pixel size range of 1.33 to 12 mm (9.3-84 min arc) achieved a goal of ≥80% accuracy. Distortion, dropout percentage, and pixel size variability have a significant impact on pixelated CC recognition. Although at present the visual ability of prosthesis users is limited, it should be possible to extend this to CC recognition and reading in the future. The results will help visual prosthesis researchers determine the effects of altering phosphene maps and improve outcomes for patients.

  5. Speech recognition in noise as a function of the number of spectral channels : Comparison of acoustic hearing and cochlear implants

    NARCIS (Netherlands)

    Friesen, LM; Shannon, RV; Baskent, D; Wang, YB

    Speech recognition was measured as a function of spectral resolution (number of spectral channels) and speech-to-noise ratio in normal-hearing (NH) and cochlear-implant (CI) listeners. Vowel, consonant, word, and sentence recognition were measured in five normal -hearing listeners, ten listeners

  6. Cursive word recognition based on interactive activation and early visual processing models.

    Science.gov (United States)

    Ruiz-Pinales, Jose; Jaime-Rivas, Rene; Lecolinet, Eric; Castro-Bleda, Maria Jose

    2008-10-01

    We present an off-line cursive word recognition system based completely on neural networks: reading models and models of early visual processing. The first stage (normalization) preprocesses the input image in order to reduce letter position uncertainty; the second stage (feature extraction) is based on the feedforward model of orientation selectivity; the third stage (letter pre-recognition) is based on a convolutional neural network, and the last stage (word recognition) is based on the interactive activation model.

  7. Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

    Directory of Open Access Journals (Sweden)

    Heracleous Panikos

    2007-01-01

    Full Text Available We present the use of stethoscope and silicon NAM (nonaudible murmur microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker's ear and can capture not only normal (audible speech, but also very quietly uttered speech (nonaudible murmur. As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech transform, etc. for sound-impaired people. Using adaptation techniques and a small amount of training data, we achieved for a 20 k dictation task a word accuracy for nonaudible murmur recognition in a clean environment. In this paper, we also investigate nonaudible murmur recognition in noisy environments and the effect of the Lombard reflex on nonaudible murmur recognition. We also propose three methods to integrate audible speech and nonaudible murmur recognition using a stethoscope NAM microphone with very promising results.

  8. The distinctiveness heuristic in false recognition and false recall.

    Science.gov (United States)

    McCabe, David P; Smith, Anderson D

    2006-07-01

    The effects of generative processing on false recognition and recall were examined in four experiments using the Deese-Roediger-McDermott false memory paradigm (Deese, 1959; Roediger & McDermott, 1995). In each experiment, a Generate condition in which subjects generated studied words from audio anagrams was compared to a Control condition in which subjects simply listened to studied words presented normally. Rates of false recognition and false recall were lower for critical lures associated with generated lists, than for critical lures associated with control lists, but only in between-subjects designs. False recall and recognition did not differ when generate and control conditions were manipulated within-subjects. This pattern of results is consistent with the distinctiveness heuristic (Schacter, Israel, & Racine, 1999), a metamemorial decision-based strategy whereby global changes in decision criteria lead to reductions of false memories. This retrieval-based monitoring mechanism appears to operate in a similar fashion in reducing false recognition and false recall.

  9. Feature Extraction based Face Recognition, Gender and Age Classification

    Directory of Open Access Journals (Sweden)

    Venugopal K R

    2010-01-01

    Full Text Available The face recognition system with large sets of training sets for personal identification normally attains good accuracy. In this paper, we proposed Feature Extraction based Face Recognition, Gender and Age Classification (FEBFRGAC algorithm with only small training sets and it yields good results even with one image per person. This process involves three stages: Pre-processing, Feature Extraction and Classification. The geometric features of facial images like eyes, nose, mouth etc. are located by using Canny edge operator and face recognition is performed. Based on the texture and shape information gender and age classification is done using Posteriori Class Probability and Artificial Neural Network respectively. It is observed that the face recognition is 100%, the gender and age classification is around 98% and 94% respectively.

  10. Object recognition with hierarchical discriminant saliency networks.

    Science.gov (United States)

    Han, Sunhyoung; Vasconcelos, Nuno

    2014-01-01

    The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

  11. Chloroquine is grossly under dosed in young children with malaria

    DEFF Research Database (Denmark)

    Ursing, Johan; Eksborg, Staffan; Rombo, Lars

    2014-01-01

    BACKGROUND: Plasmodium falciparum malaria is treated with 25 mg/kg of chloroquine (CQ) irrespective of age. Theoretically, CQ should be dosed according to body surface area (BSA). The effect of dosing CQ according to BSA has not been determined but doubling the dose per kg doubled the efficacy of...

  12. Robust Lasso with missing and grossly corrupted observations

    CERN Document Server

    Nguyen, Nam H

    2011-01-01

    This paper studies the problem of accurately recovering a sparse vector $\\beta^{\\star}$ from highly corrupted linear measurements $y = X \\beta^{\\star} + e^{\\star} + w$ where $e^{\\star}$ is a sparse error vector whose nonzero entries may be unbounded and $w$ is a bounded noise. We propose a so-called extended Lasso optimization which takes into consideration sparse prior information of both $\\beta^{\\star}$ and $e^{\\star}$. Our first result shows that the extended Lasso can faithfully recover both the regression as well as the corruption vector. Our analysis relies on the notion of extended restricted eigenvalue for the design matrix $X$. Our second set of results applies to a general class of Gaussian design matrix $X$ with i.i.d rows $\\oper N(0, \\Sigma)$, for which we can establish a surprising result: the extended Lasso can recover exact signed supports of both $\\beta^{\\star}$ and $e^{\\star}$ from only $\\Omega(k \\log p \\log n)$ observations, even when the fraction of corruption is arbitrarily close to one. O...

  13. Glassfiber Post: An Alternative for Restoring Grossly Decayed Primary Incisors

    OpenAIRE

    Mehra, Manjul; Grover, Rashu

    2012-01-01

    ABSTRACT Restoration of primary incisors, which have been severely damaged by rampant caries or trauma, is a difficult task for the pediatric dentist. With the introduction of new adhesive systems and restorative materials, alternative approaches for treating these teeth have been proposed. This paper discusses the restoration of carious primary maxillary incisors using composite resin restoration reinforced with fiberglass post. Two case reports are presented here to describe the procedure. ...

  14. Rare Cadaveric Finding of a Grossly Enlarged Mucocele Appendix

    Directory of Open Access Journals (Sweden)

    Anna Farias

    2013-12-01

    Full Text Available Appendicular mucoceles are rare clinical findings characterized by dilation and distention of the appendicular lumen by the accumulation of mucus. Their discovery is often incidental from abdominal imaging or more commonly as a secondary surgical finding. In this case study we report the first known recorded case of a cadaveric mucocele appendix discovered during routine dissection of the gastrointestinal system. The recorded cause of death for the 86-year-old female patient was congestive heart failure. We compared the gross anatomy and histology of this enormous appendix with another cadaveric appendix. A pathology report identified the appendicular mucocele as a mucinous cystadenoma.

  15. Massive yet grossly underestimated global costs of invasive insects

    Science.gov (United States)

    Bradshaw, Corey J. A.; Leroy, Boris; Bellard, Céline; Roiz, David; Albert, Céline; Fournier, Alice; Barbet-Massin, Morgane; Salles, Jean-Michel; Simard, Frédéric; Courchamp, Franck

    2016-10-01

    Insects have presented human society with some of its greatest development challenges by spreading diseases, consuming crops and damaging infrastructure. Despite the massive human and financial toll of invasive insects, cost estimates of their impacts remain sporadic, spatially incomplete and of questionable quality. Here we compile a comprehensive database of economic costs of invasive insects. Taking all reported goods and service estimates, invasive insects cost a minimum of US$70.0 billion per year globally, while associated health costs exceed US$6.9 billion per year. Total costs rise as the number of estimate increases, although many of the worst costs have already been estimated (especially those related to human health). A lack of dedicated studies, especially for reproducible goods and service estimates, implies gross underestimation of global costs. Global warming as a consequence of climate change, rising human population densities and intensifying international trade will allow these costly insects to spread into new areas, but substantial savings could be achieved by increasing surveillance, containment and public awareness.

  16. Object Recognition with Severe Spatial Deficits in Williams Syndrome: Sparing and Breakdown

    Science.gov (United States)

    Landau, Barbara; Hoffman, James E.; Kurz, Nicole

    2006-01-01

    Williams syndrome (WS) is a rare genetic disorder that results in severe visual-spatial cognitive deficits coupled with relative sparing in language, face recognition, and certain aspects of motion processing. Here, we look for evidence for sparing or impairment in another cognitive system--object recognition. Children with WS, normal mental-age…

  17. Vocabulary and Environment Adaptation in Vocabulary-Independent Speech Recognition

    Science.gov (United States)

    1992-01-01

    normalization (ISDCN) proposed by Acero et al. [2] for microphone adaptation are incorporated into the our VI system to achieve environmental...reverberation from surface reflec- tions, etc. Acero at al. [1,2] proposed a series of environment normal- ization algorithms based on joint...support. References [1] Acero , A. Acoustical and Environmental Robustness in Auto- matic Speech Recognition. Department of Electrical Engineer- ing

  18. Data set for Tifinagh handwriting character recognition

    Directory of Open Access Journals (Sweden)

    Omar Bencharef

    2015-09-01

    Full Text Available The Tifinagh alphabet-IRCAM is the official alphabet of the Amazigh language widely used in North Africa [1]. It includes thirty-one basic letter and two letters each composed of a base letter followed by the sign of labialization. Normalized only in 2003 (Unicode [2], ICRAM-Tifinagh is a young character repertoire. Which needs more work on all levels. In this context we propose a data set for handwritten Tifinagh characters composed of 1376 image; 43 Image For Each character. The dataset can be used to train a Tifinagh character recognition system, or to extract the meaning characteristics of each character.

  19. Data set for Tifinagh handwriting character recognition.

    Science.gov (United States)

    Bencharef, Omar; Chihab, Younes; Mousaid, Nouredine; Oujaoura, Mustapha

    2015-09-01

    The Tifinagh alphabet-IRCAM is the official alphabet of the Amazigh language widely used in North Africa [1]. It includes thirty-one basic letter and two letters each composed of a base letter followed by the sign of labialization. Normalized only in 2003 (Unicode) [2], ICRAM-Tifinagh is a young character repertoire. Which needs more work on all levels. In this context we propose a data set for handwritten Tifinagh characters composed of 1376 image; 43 Image For Each character. The dataset can be used to train a Tifinagh character recognition system, or to extract the meaning characteristics of each character.

  20. Advances in Speech Recognition

    CERN Document Server

    Neustein, Amy

    2010-01-01

    This volume is comprised of contributions from eminent leaders in the speech industry, and presents a comprehensive and in depth analysis of the progress of speech technology in the topical areas of mobile settings, healthcare and call centers. The material addresses the technical aspects of voice technology within the framework of societal needs, such as the use of speech recognition software to produce up-to-date electronic health records, not withstanding patients making changes to health plans and physicians. Included will be discussion of speech engineering, linguistics, human factors ana

  1. SEX RECOGNITION IN ZEBRA FINCH MALES RESULTS FROM EARLY EXPERIENCE

    NARCIS (Netherlands)

    VOS, DR

    1994-01-01

    This study investigated whether sexual imprinting plays a role in the recognition of the sex of conspecifics. Subjects were zebra finch males that had been raised with either normal pairs, white pairs or pairs of both morphs. They were tested for their preferences in six two-stimuli tests covering a

  2. Use of Adaptive Digital Signal Processing to Improve Speech Communication for Normally Hearing aand Hearing-Impaired Subjects.

    Science.gov (United States)

    Harris, Richard W.; And Others

    1988-01-01

    A two-microphone adaptive digital noise cancellation technique improved word-recognition ability for 20 normal and 12 hearing-impaired adults by reducing multitalker speech babble and speech spectrum noise 18-22 dB. Word recognition improvements averaged 37-50 percent for normal and 27-40 percent for hearing-impaired subjects. Improvement was best…

  3. Human activity recognition and prediction

    CERN Document Server

    2016-01-01

    This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques. .

  4. Recent progress in fingerprint recognition

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Fingerprint recognition has been increasingly used to realize personal identification in civilian's daily life, such as ID card, fingerprints hard disk and so on. Great improvement has been achieved in the on-line fingerprint sensing technology and automatic fingerprint recognition algorithms. Various fingerprint recognition techniques, including fingerprint acquisition, classification, enhancement and matching, are highly improved. This paper overviews recent advances in fingerprint recognition and summarizes the algorithm proposed for every step with special focuses on the enhancement of low-quality fingerprints and the matching of the distorted fingerprint images. Both issues are believed to be significant and challenging tasks. In addition, we also discuss the common evaluation for the fingerprint recognition algorithm of the Fingerprint Verification Competition 2004 (FVC2004) and the Fingerprint Vendor Technology Evaluation 2003 (FpVTE2003), based on which we could measure the performance of the recognition algorithm objectively and uniformly.

  5. [Comparative studies of face recognition].

    Science.gov (United States)

    Kawai, Nobuyuki

    2012-07-01

    Every human being is proficient in face recognition. However, the reason for and the manner in which humans have attained such an ability remain unknown. These questions can be best answered-through comparative studies of face recognition in non-human animals. Studies in both primates and non-primates show that not only primates, but also non-primates possess the ability to extract information from their conspecifics and from human experimenters. Neural specialization for face recognition is shared with mammals in distant taxa, suggesting that face recognition evolved earlier than the emergence of mammals. A recent study indicated that a social insect, the golden paper wasp, can distinguish their conspecific faces, whereas a closely related species, which has a less complex social lifestyle with just one queen ruling a nest of underlings, did not show strong face recognition for their conspecifics. Social complexity and the need to differentiate between one another likely led humans to evolve their face recognition abilities.

  6. Genetic specificity of face recognition.

    Science.gov (United States)

    Shakeshaft, Nicholas G; Plomin, Robert

    2015-10-13

    Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities.

  7. Pilgrims Face Recognition Dataset -- HUFRD

    OpenAIRE

    Aly, Salah A.

    2012-01-01

    In this work, we define a new pilgrims face recognition dataset, called HUFRD dataset. The new developed dataset presents various pilgrims' images taken from outside the Holy Masjid El-Harram in Makkah during the 2011-2012 Hajj and Umrah seasons. Such dataset will be used to test our developed facial recognition and detection algorithms, as well as assess in the missing and found recognition system \\cite{crowdsensing}.

  8. Speech recognition in university classrooms

    OpenAIRE

    Wald, Mike; Bain, Keith; Basson, Sara H

    2002-01-01

    The LIBERATED LEARNING PROJECT (LLP) is an applied research project studying two core questions: 1) Can speech recognition (SR) technology successfully digitize lectures to display spoken words as text in university classrooms? 2) Can speech recognition technology be used successfully as an alternative to traditional classroom notetaking for persons with disabilities? This paper addresses these intriguing questions and explores the underlying complex relationship between speech recognition te...

  9. Radically enhanced molecular recognition

    KAUST Repository

    Trabolsi, Ali

    2009-12-17

    The tendency for viologen radical cations to dimerize has been harnessed to establish a recognition motif based on their ability to form extremely strong inclusion complexes with cyclobis(paraquat-p-phenylene) in its diradical dicationic redox state. This previously unreported complex involving three bipyridinium cation radicals increases the versatility of host-guest chemistry, extending its practice beyond the traditional reliance on neutral and charged guests and hosts. In particular, transporting the concept of radical dimerization into the field of mechanically interlocked molecules introduces a higher level of control within molecular switches and machines. Herein, we report that bistable and tristable [2]rotaxanes can be switched by altering electrochemical potentials. In a tristable [2]rotaxane composed of a cyclobis(paraquat-p-phenylene) ring and a dumbbell with tetrathiafulvalene, dioxynaphthalene and bipyridinium recognition sites, the position of the ring can be switched. On oxidation, it moves from the tetrathiafulvalene to the dioxynaphthalene, and on reduction, to the bipyridinium radical cation, provided the ring is also reduced simultaneously to the diradical dication. © 2010 Macmillan Publishers Limited. All rights reserved.

  10. Factors influencing recognition of interrupted speech.

    Science.gov (United States)

    Wang, Xin; Humes, Larry E

    2010-10-01

    This study examined the effect of interruption parameters (e.g., interruption rate, on-duration and proportion), linguistic factors, and other general factors, on the recognition of interrupted consonant-vowel-consonant (CVC) words in quiet. Sixty-two young adults with normal-hearing were randomly assigned to one of three test groups, "male65," "female65" and "male85," that differed in talker (male/female) and presentation level (65/85 dB SPL), with about 20 subjects per group. A total of 13 stimulus conditions, representing different interruption patterns within the words (i.e., various combinations of three interruption parameters), in combination with two values (easy and hard) of lexical difficulty were examined (i.e., 13×2=26 test conditions) within each group. Results showed that, overall, the proportion of speech and lexical difficulty had major effects on the integration and recognition of interrupted CVC words, while the other variables had small effects. Interactions between interruption parameters and linguistic factors were observed: to reach the same degree of word-recognition performance, less acoustic information was required for lexically easy words than hard words. Implications of the findings of the current study for models of the temporal integration of speech are discussed.

  11. Statistical feature extraction based iris recognition system

    Indian Academy of Sciences (India)

    ATUL BANSAL; RAVINDER AGARWAL; R K SHARMA

    2016-05-01

    Iris recognition systems have been proposed by numerous researchers using different feature extraction techniques for accurate and reliable biometric authentication. In this paper, a statistical feature extraction technique based on correlation between adjacent pixels has been proposed and implemented. Hamming distance based metric has been used for matching. Performance of the proposed iris recognition system (IRS) has been measured by recording false acceptance rate (FAR) and false rejection rate (FRR) at differentthresholds in the distance metric. System performance has been evaluated by computing statistical features along two directions, namely, radial direction of circular iris region and angular direction extending from pupil tosclera. Experiments have also been conducted to study the effect of number of statistical parameters on FAR and FRR. Results obtained from the experiments based on different set of statistical features of iris images show thatthere is a significant improvement in equal error rate (EER) when number of statistical parameters for feature extraction is increased from three to six. Further, it has also been found that increasing radial/angular resolution,with normalization in place, improves EER for proposed iris recognition system

  12. Markov Models for Handwriting Recognition

    CERN Document Server

    Plotz, Thomas

    2011-01-01

    Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden

  13. Sudden Event Recognition: A Survey

    Science.gov (United States)

    Suriani, Nor Surayahani; Hussain, Aini; Zulkifley, Mohd Asyraf

    2013-01-01

    Event recognition is one of the most active research areas in video surveillance fields. Advancement in event recognition systems mainly aims to provide convenience, safety and an efficient lifestyle for humanity. A precise, accurate and robust approach is necessary to enable event recognition systems to respond to sudden changes in various uncontrolled environments, such as the case of an emergency, physical threat and a fire or bomb alert. The performance of sudden event recognition systems depends heavily on the accuracy of low level processing, like detection, recognition, tracking and machine learning algorithms. This survey aims to detect and characterize a sudden event, which is a subset of an abnormal event in several video surveillance applications. This paper discusses the following in detail: (1) the importance of a sudden event over a general anomalous event; (2) frameworks used in sudden event recognition; (3) the requirements and comparative studies of a sudden event recognition system and (4) various decision-making approaches for sudden event recognition. The advantages and drawbacks of using 3D images from multiple cameras for real-time application are also discussed. The paper concludes with suggestions for future research directions in sudden event recognition. PMID:23921828

  14. Speech Recognition on Mobile Devices

    DEFF Research Database (Denmark)

    Tan, Zheng-Hua; Lindberg, Børge

    2010-01-01

    The enthusiasm of deploying automatic speech recognition (ASR) on mobile devices is driven both by remarkable advances in ASR technology and by the demand for efficient user interfaces on such devices as mobile phones and personal digital assistants (PDAs). This chapter presents an overview of ASR...... in the mobile context covering motivations, challenges, fundamental techniques and applications. Three ASR architectures are introduced: embedded speech recognition, distributed speech recognition and network speech recognition. Their pros and cons and implementation issues are discussed. Applications within...... command and control, text entry and search are presented with an emphasis on mobile text entry....

  15. Frequency-Based Fingerprint Recognition

    Science.gov (United States)

    Aguilar, Gualberto; Sánchez, Gabriel; Toscano, Karina; Pérez, Héctor

    abstract Fingerprint recognition is one of the most popular methods used for identification with greater success degree. Fingerprint has unique characteristics called minutiae, which are points where a curve track ends, intersects, or branches off. In this chapter a fingerprint recognition method is proposed in which a combination of Fast Fourier Transform (FFT) and Gabor filters is used for image enhancement. A novel recognition stage using local features for recognition is also proposed. Also a verification stage is introduced to be used when the system output has more than one person.

  16. Study of Face Recognition Techniques

    Directory of Open Access Journals (Sweden)

    Sangeeta Kaushik

    2014-12-01

    Full Text Available A study of both face recognition and detection techniques is carried out using the algorithms like Principal Component Analysis (PCA, Kernel Principal Component Analysis (KPCA, Linear Discriminant Analysis (LDA and Line Edge Map (LEM. These algorithms show different rates of accuracy under different conditions. The automatic recognition of human faces presents a challenge to the pattern recognition community. Typically, human faces are different in shapes with minor similarity from person to person. Furthermore, lighting condition changes, facial expressions and pose variations further complicate the face recognition task as one of the difficult problems in pattern analysis.

  17. USE OF IMAGE ENHANCEMENT TECHNIQUES FOR IMPROVING REAL TIME FACE RECOGNITION EFFICIENCY ON WEARABLE GADGETS

    OpenAIRE

    MUHAMMAD EHSAN RANA; AHMAD AFZAL ZADEH; AHMAD MOHAMMAD MAHMOOD ALQURNEH

    2017-01-01

    The objective of this research is to study the effects of image enhancement techniques on face recognition performance of wearable gadgets with an emphasis on recognition rate.In this research, a number of image enhancement techniques are selected that include brightness normalization, contrast normalization, sharpening, smoothing, and various combinations of these. Subsequently test images are obtained from AT&T database and Yale Face Database B to investigate the effect of these image enhan...

  18. [Improvement in Phoneme Discrimination in Noise in Normal Hearing Adults].

    Science.gov (United States)

    Schumann, A; Garea Garcia, L; Hoppe, U

    2017-02-01

    Objective: The study's aim was to examine the possibility to train phoneme-discrimination in noise with normal hearing adults, and its effectivity on speech recognition in noise. A specific computerised training program was used, consisting of special nonsense-syllables with background noise, to train participants' discrimination ability. Material and Methods: 46 normal hearing subjects took part in this study, 28 as training group participants, 18 as control group participants. Only the training group subjects were asked to train over a period of 3 weeks, twice a week for an hour with a computer-based training program. Speech recognition in noise were measured pre- to posttraining for the training group subjects with the Freiburger Einsilber Test. The control group subjects obtained test and restest measures within a 2-3 week break. For the training group follow-up speech recognition was measured 2-3 months after the end of the training. Results: The majority of training group subjects improved their phoneme discrimination significantly. Besides, their speech recognition in noise improved significantly during the training compared to the control group, and remained stable for a period of time. Conclusions: Phonem-Discrimination in noise can be trained by normal hearing adults. The improvements have got a positiv effect on speech recognition in noise, also for a longer period of time.

  19. Normal composite face effects in developmental prosopagnosia.

    Science.gov (United States)

    Biotti, Federica; Wu, Esther; Yang, Hua; Jiahui, Guo; Duchaine, Bradley; Cook, Richard

    2017-08-10

    Upright face perception is thought to involve holistic processing, whereby local features are integrated into a unified whole. Consistent with this view, the top half of one face appears to fuse perceptually with the bottom half of another, when aligned spatially and presented upright. This 'composite face effect' reveals a tendency to integrate information from disparate regions when faces are presented canonically. In recent years, the relationship between susceptibility to the composite effect and face recognition ability has received extensive attention both in participants with normal face recognition and participants with developmental prosopagnosia. Previous results suggest that individuals with developmental prosopagnosia may show reduced susceptibility to the effect suggestive of diminished holistic face processing. Here we describe two studies that examine whether developmental prosopagnosia is associated with reduced composite face effects. Despite using independent samples of developmental prosopagnosics and different composite procedures, we find no evidence for reduced composite face effects. The experiments yielded similar results; highly significant composite effects in both prosopagnosic groups that were similar in magnitude to the effects found in participants with normal face processing. The composite face effects exhibited by both samples and the controls were greatly diminished when stimulus arrangements were inverted. Our finding that the whole-face binding process indexed by the composite effect is intact in developmental prosopagnosia indicates that other factors are responsible for developmental prosopagnosia. These results are also inconsistent with suggestions that susceptibility to the composite face effect and face recognition ability are tightly linked. While the holistic process revealed by the composite face effect may be necessary for typical face perception, it is not sufficient; individual differences in face recognition ability

  20. Attribute measure recognition approach and its applications to emitter recognition

    Institute of Scientific and Technical Information of China (English)

    GUAN Xin; HE You; YI Xiao

    2005-01-01

    This paper studies the emitter recognition problem. A new recognition method based on attribute measure for emitter recognition is put forward. The steps of the method are presented. The approach to determining the weight coefficient is also discussed. Moreover, considering the temporal redundancy of emitter information detected by multi-sensor system, this new recognition method is generalized to multi-sensor system. A method based on the combination of attribute measure and D-S evidence theory is proposed. The implementation of D-S reasoning is always restricted by basic probability assignment function. Constructing basic probability assignment function based on attribute measure is presented in multi-sensor recognition system. Examples of recognizing the emitter purpose and system are selected to demonstrate the method proposed. Experimental results show that the performance of this new method is accurate and effective.

  1. Object recognition with hierarchical discriminant saliency networks

    Directory of Open Access Journals (Sweden)

    Sunhyoung eHan

    2014-09-01

    Full Text Available The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognitionmodel, the hierarchical discriminant saliency network (HDSN, whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. The HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a neuralnetwork implementation, all layers are convolutional and implement acombination of filtering, rectification, and pooling. The rectificationis performed with a parametric extension of the now popular rectified linearunits (ReLUs, whose parameters can be tuned for the detection of targetobject classes. This enables a number of functional enhancementsover neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation ofsaliency responses by the discriminant power of the underlying features,and the ability to detect both feature presence and absence.In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity totarget object classes and invariance. The resulting performance demonstrates benefits for all the functional enhancements of the HDSN.

  2. The Legal Recognition of Sign Languages

    Science.gov (United States)

    De Meulder, Maartje

    2015-01-01

    This article provides an analytical overview of the different types of explicit legal recognition of sign languages. Five categories are distinguished: constitutional recognition, recognition by means of general language legislation, recognition by means of a sign language law or act, recognition by means of a sign language law or act including…

  3. Recognition memory in noise for speech of varying intelligibility.

    Science.gov (United States)

    Gilbert, Rachael C; Chandrasekaran, Bharath; Smiljanic, Rajka

    2014-01-01

    This study investigated the extent to which noise impacts normal-hearing young adults' speech processing of sentences that vary in intelligibility. Intelligibility and recognition memory in noise were examined for conversational and clear speech sentences recorded in quiet (quiet speech, QS) and in response to the environmental noise (noise-adapted speech, NAS). Results showed that (1) increased intelligibility through conversational-to-clear speech modifications led to improved recognition memory and (2) NAS presented a more naturalistic speech adaptation to noise compared to QS, leading to more accurate word recognition and enhanced sentence recognition memory. These results demonstrate that acoustic-phonetic modifications implemented in listener-oriented speech enhance speech-in-noise processing beyond word recognition. Effortful speech processing in challenging listening environments can thus be improved by speaking style adaptations on the part of the talker. In addition to enhanced intelligibility, a substantial improvement in recognition memory can be achieved through speaker adaptations to the environment and to the listener when in adverse conditions.

  4. Chemical recognition software

    Energy Technology Data Exchange (ETDEWEB)

    Wagner, J.S.; Trahan, M.W.; Nelson, W.E.; Hargis, P.H. Jr.; Tisone, G.C.

    1994-06-01

    We have developed a capability to make real time concentration measurements of individual chemicals in a complex mixture using a multispectral laser remote sensing system. Our chemical recognition and analysis software consists of three parts: (1) a rigorous multivariate analysis package for quantitative concentration and uncertainty estimates, (2) a genetic optimizer which customizes and tailors the multivariate algorithm for a particular application, and (3) an intelligent neural net chemical filter which pre-selects from the chemical database to find the appropriate candidate chemicals for quantitative analyses by the multivariate algorithms, as well as providing a quick-look concentration estimate and consistency check. Detailed simulations using both laboratory fluorescence data and computer synthesized spectra indicate that our software can make accurate concentration estimates from complex multicomponent mixtures, even when the mixture is noisy and contaminated with unknowns.

  5. Chemical recognition software

    Energy Technology Data Exchange (ETDEWEB)

    Wagner, J.S.; Trahan, M.W.; Nelson, W.E.; Hargis, P.J. Jr.; Tisone, G.C.

    1994-12-01

    We have developed a capability to make real time concentration measurements of individual chemicals in a complex mixture using a multispectral laser remote sensing system. Our chemical recognition and analysis software consists of three parts: (1) a rigorous multivariate analysis package for quantitative concentration and uncertainty estimates, (2) a genetic optimizer which customizes and tailors the multivariate algorithm for a particular application, and (3) an intelligent neural net chemical filter which pre-selects from the chemical database to find the appropriate candidate chemicals for quantitative analyses by the multivariate algorithms, as well as providing a quick-look concentration estimate and consistency check. Detailed simulations using both laboratory fluorescence data and computer synthesized spectra indicate that our software can make accurate concentration estimates from complex multicomponent mixtures. even when the mixture is noisy and contaminated with unknowns.

  6. Iris Recognition Using Wavelet

    Directory of Open Access Journals (Sweden)

    Khaliq Masood

    2013-08-01

    Full Text Available Biometric systems are getting more attention in the present era. Iris recognition is one of the most secure and authentic among the other biometrics and this field demands more authentic, reliable and fast algorithms to implement these biometric systems in real time. In this paper, an efficient localization technique is presented to identify pupil and iris boundaries using histogram of the iris image. Two small portions of iris have been used for polar transformation to reduce computational time and to increase the efficiency of the system. Wavelet transform is used for feature vector generation. Rotation of iris is compensated without shifts in the iris code. System is tested on Multimedia University Iris Database and results show that proposed system has encouraging performance.

  7. SAR: Stroke Authorship Recognition

    KAUST Repository

    Shaheen, Sara

    2015-10-15

    Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR\\'s ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

  8. Forensic Face Recognition: A Survey

    NARCIS (Netherlands)

    Ali, Tauseef; Veldhuis, Raymond; Spreeuwers, Luuk

    2010-01-01

    Beside a few papers which focus on the forensic aspects of automatic face recognition, there is not much published about it in contrast to the literature on developing new techniques and methodologies for biometric face recognition. In this report, we review forensic facial identification which is t

  9. Coordinate Transformations in Object Recognition

    Science.gov (United States)

    Graf, Markus

    2006-01-01

    A basic problem of visual perception is how human beings recognize objects after spatial transformations. Three central classes of findings have to be accounted for: (a) Recognition performance varies systematically with orientation, size, and position; (b) recognition latencies are sequentially additive, suggesting analogue transformation…

  10. FILTWAM and Voice Emotion Recognition

    NARCIS (Netherlands)

    Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

    2014-01-01

    This paper introduces the voice emotion recognition part of our framework for improving learning through webcams and microphones (FILTWAM). This framework enables multimodal emotion recognition of learners during game-based learning. The main goal of this study is to validate the use of microphone d

  11. Quantum-Limited Image Recognition

    Science.gov (United States)

    1989-12-01

    J. S. Bomba ,’Alpha-numeric character recognition using local operations,’ Fall Joint Comput. Conf., 218-224 (1959). 53. D. Barnea and H. Silverman...for Chapter 6 1. J. S. Bomba ,’Alpha-numeric character recognition using local operations,’ Fall Joint Comput. Conf., 218-224 (1959). 2. D. Bamea and H

  12. Side-View Face Recognition

    NARCIS (Netherlands)

    Santemiz, Pinar; Spreeuwers, Luuk J.; Veldhuis, Raymond N.J.; Biggelaar , van den Olivier

    2011-01-01

    As a widely used biometrics, face recognition has many advantages such as being non-intrusive, natural and passive. On the other hand, in real-life scenarios with uncontrolled environment, pose variation up to side-view positions makes face recognition a challenging work. In this paper we discuss th

  13. Methods of Teaching Speech Recognition

    Science.gov (United States)

    Rader, Martha H.; Bailey, Glenn A.

    2010-01-01

    Objective: This article introduces the history and development of speech recognition, addresses its role in the business curriculum, outlines related national and state standards, describes instructional strategies, and discusses the assessment of student achievement in speech recognition classes. Methods: Research methods included a synthesis of…

  14. FILTWAM and Voice Emotion Recognition

    NARCIS (Netherlands)

    Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

    2014-01-01

    This paper introduces the voice emotion recognition part of our framework for improving learning through webcams and microphones (FILTWAM). This framework enables multimodal emotion recognition of learners during game-based learning. The main goal of this study is to validate the use of microphone

  15. Recognition of emotion in others

    NARCIS (Netherlands)

    Frijda, N.H.; Paglieri, F.

    2012-01-01

    This chapter argues that recognition of emotion had a simple basis and a highly complex edifice above it. Its basis is formed by catching intent from expressive and other emotional behavior, using elementary principles of perceptual integration. In intent recognition, mirror neurons under particular

  16. Integrating various resources for gene name normalization.

    Directory of Open Access Journals (Sweden)

    Yuncui Hu

    Full Text Available The recognition and normalization of gene mentions in biomedical literature are crucial steps in biomedical text mining. We present a system for extracting gene names from biomedical literature and normalizing them to gene identifiers in databases. The system consists of four major components: gene name recognition, entity mapping, disambiguation and filtering. The first component is a gene name recognizer based on dictionary matching and semi-supervised learning, which utilizes the co-occurrence information of a large amount of unlabeled MEDLINE abstracts to enhance feature representation of gene named entities. In the stage of entity mapping, we combine the strategies of exact match and approximate match to establish linkage between gene names in the context and the EntrezGene database. For the gene names that map to more than one database identifiers, we develop a disambiguation method based on semantic similarity derived from the Gene Ontology and MEDLINE abstracts. To remove the noise produced in the previous steps, we design a filtering method based on the confidence scores in the dictionary used for NER. The system is able to adjust the trade-off between precision and recall based on the result of filtering. It achieves an F-measure of 83% (precision: 82.5% recall: 83.5% on BioCreative II Gene Normalization (GN dataset, which is comparable to the current state-of-the-art.

  17. Machine learning techniques for gait biometric recognition using the ground reaction force

    CERN Document Server

    Mason, James Eric; Woungang, Isaac

    2016-01-01

    This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of ...

  18. [Association between intelligence development and facial expression recognition ability in children with autism spectrum disorder].

    Science.gov (United States)

    Pan, Ning; Wu, Gui-Hua; Zhang, Ling; Zhao, Ya-Fen; Guan, Han; Xu, Cai-Juan; Jing, Jin; Jin, Yu

    2017-03-01

    To investigate the features of intelligence development, facial expression recognition ability, and the association between them in children with autism spectrum disorder (ASD). A total of 27 ASD children aged 6-16 years (ASD group, full intelligence quotient >70) and age- and gender-matched normally developed children (control group) were enrolled. Wechsler Intelligence Scale for Children Fourth Edition and Chinese Static Facial Expression Photos were used for intelligence evaluation and facial expression recognition test. Compared with the control group, the ASD group had significantly lower scores of full intelligence quotient, verbal comprehension index, perceptual reasoning index (PRI), processing speed index(PSI), and working memory index (WMI) (Pchildren have delayed intelligence development compared with normally developed children and impaired expression recognition ability. Perceptual reasoning and working memory abilities are positively correlated with expression recognition ability, which suggests that insufficient perceptual reasoning and working memory abilities may be important factors affecting facial expression recognition ability in ASD children.

  19. Normalization in econometrics

    OpenAIRE

    Hamilton, James D.; Daniel F. Waggoner; Zha, Tao

    2004-01-01

    The issue of normalization arises whenever two different values for a vector of unknown parameters imply the identical economic model. A normalization does not just imply a rule for selecting which point, among equivalent ones, to call the maximum likelihood estimator (MLE). It also governs the topography of the set of points that go into a small-sample confidence interval associated with that MLE. A poor normalization can lead to multimodal distributions, disjoint confidence intervals, and v...

  20. Illumination normalization based on simplified local binary patterns for a face verification system

    NARCIS (Netherlands)

    Tao, Q.; Veldhuis, Raymond N.J.

    2007-01-01

    Illumination normalization is a very important step in face recognition. In this paper we propose a simple implementation of Local Binary Patterns, which effectively reduces the variability caused by illumination changes. In combination with a likelihood ratio classifier, this illumination

  1. Viewpoint Manifolds for Action Recognition

    Directory of Open Access Journals (Sweden)

    Souvenir Richard

    2009-01-01

    Full Text Available Abstract Action recognition from video is a problem that has many important applications to human motion analysis. In real-world settings, the viewpoint of the camera cannot always be fixed relative to the subject, so view-invariant action recognition methods are needed. Previous view-invariant methods use multiple cameras in both the training and testing phases of action recognition or require storing many examples of a single action from multiple viewpoints. In this paper, we present a framework for learning a compact representation of primitive actions (e.g., walk, punch, kick, sit that can be used for video obtained from a single camera for simultaneous action recognition and viewpoint estimation. Using our method, which models the low-dimensional structure of these actions relative to viewpoint, we show recognition rates on a publicly available dataset previously only achieved using multiple simultaneous views.

  2. Viewpoint Manifolds for Action Recognition

    Directory of Open Access Journals (Sweden)

    Richard Souvenir

    2009-01-01

    Full Text Available Action recognition from video is a problem that has many important applications to human motion analysis. In real-world settings, the viewpoint of the camera cannot always be fixed relative to the subject, so view-invariant action recognition methods are needed. Previous view-invariant methods use multiple cameras in both the training and testing phases of action recognition or require storing many examples of a single action from multiple viewpoints. In this paper, we present a framework for learning a compact representation of primitive actions (e.g., walk, punch, kick, sit that can be used for video obtained from a single camera for simultaneous action recognition and viewpoint estimation. Using our method, which models the low-dimensional structure of these actions relative to viewpoint, we show recognition rates on a publicly available dataset previously only achieved using multiple simultaneous views.

  3. Online handwritten mathematical expression recognition

    Science.gov (United States)

    Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül

    2007-01-01

    We describe a system for recognizing online, handwritten mathematical expressions. The system is designed with a user-interface for writing scientific articles, supporting the recognition of basic mathematical expressions as well as integrals, summations, matrices etc. A feed-forward neural network recognizes symbols which are assumed to be single-stroke and a recursive algorithm parses the expression by combining neural network output and the structure of the expression. Preliminary results show that writer-dependent recognition rates are very high (99.8%) while writer-independent symbol recognition rates are lower (75%). The interface associated with the proposed system integrates the built-in recognition capabilities of the Microsoft's Tablet PC API for recognizing textual input and supports conversion of hand-drawn figures into PNG format. This enables the user to enter text, mathematics and draw figures in a single interface. After recognition, all output is combined into one LATEX code and compiled into a PDF file.

  4. Galeotti on recognition as inclusion

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2008-01-01

    out Galeotti's justification for recognition as a requirement of liberal justice in detail and asks in what sense the policies supported by Galeotti are policies of recognition. It is argued that Jones misrepresents Galeotti's theory, insofar as this sense of recognition actually is compatible......Anna Elisabetta Galeotti's theory of 'toleration as recognition' has been criticised by Peter Jones for being conceptually incoherent, since liberal toleration presupposes a negative attitude to differences, whereas multicultural recognition requires positive affirmation hereof. The paper spells...... with liberal toleration. This does not prove Jones's criticism to be wrong, since the justification may have implications unacknowledged by Galeotti, which might be liberally problematic. The paper considers this problem and possible ways of responding to it, but concludes that Galeotti's theory is incomplete...

  5. Optimizing Face Recognition Using PCA

    Directory of Open Access Journals (Sweden)

    Manal Abdullah

    2012-03-01

    Full Text Available Principle Component Analysis PCA is a classical feature extraction and data representation technique widely used in pattern recognition. It is one of the most successful techniques in face recognition. But it has drawback of high computational especially for big size database. This paper conducts a study to optimize the time complexity of PCA (eigenfaces that does not affects the recognition performance. The authors minimize the participated eigenvectors which consequently decreases the computational time. A comparison is done to compare the differences between the recognition time in the original algorithm and in the enhanced algorithm. The performance of the original and the enhanced proposed algorithm is tested on face94 face database. Experimental results show that the recognition time is reduced by 35% by applying our proposed enhanced algorithm. DET Curves are used to illustrate the experimental results.

  6. Optimizing Face Recognition Using PCA

    Directory of Open Access Journals (Sweden)

    Manal Abdullah

    2012-04-01

    Full Text Available Principle Component Analysis PCA is a classical feature extraction and data representation technique widely used in pattern recognition. It is one of the most successful techniques in face recognition. But it has drawback of high computational especially for big size database. This paper conducts a study to optimize the time complexity of PCA (eigenfaces that does not affects the recognition performance. The authorsminimize the participated eigenvectors which consequently decreases the computational time. A comparison is done to compare the differences between the recognition time in the original algorithm and in the enhanced algorithm. The performance of the original and the enhanced proposed algorithm is tested on face94 face database. Experimental results show that the recognition time is reduced by 35% by applying our proposed enhanced algorithm. DET Curves are used to illustrate the experimental results.

  7. Normal cognitive aging.

    Science.gov (United States)

    Harada, Caroline N; Natelson Love, Marissa C; Triebel, Kristen L

    2013-11-01

    Even those who do not experience dementia or mild cognitive impairment may experience subtle cognitive changes associated with aging. Normal cognitive changes can affect an older adult's everyday function and quality of life, and a better understanding of this process may help clinicians distinguish normal from disease states. This article describes the neurocognitive changes observed in normal aging, followed by a description of the structural and functional alterations seen in aging brains. Practical implications of normal cognitive aging are then discussed, followed by a discussion of what is known about factors that may mitigate age-associated cognitive decline.

  8. Normalizers of Irreducible Subfactors

    CERN Document Server

    Smith, Roger R; Wiggins, Alan D

    2007-01-01

    We consider normalizers of an irreducible inclusion $N\\subseteq M$ of $\\mathrm{II}_1$ factors. In the infinite index setting an inclusion $uNu^*\\subseteq N$ can be strict, forcing us to also investigate the semigroup of one-sided normalizers. We relate these normalizers of $N$ in $M$ to projections in the basic construction and show that every trace one projection in the relative commutant $N'\\cap $ is of the form $u^*e_Nu$ for some unitary $u\\in M$ with $uNu^*\\subseteq N$. This enables us to identify the normalizers and the algebras they generate in several situations. In particular each normalizer of a tensor product of irreducible subfactors is a tensor product of normalizers modulo a unitary. We also examine normalizers of irreducible subfactors arising from subgroup--group inclusions $H\\subseteq G$. Here the normalizers are the normalizing group elements modulo a unitary from $L(H)$. We are also able to identify the finite trace $L(H)$-bimodules in $\\ell^2(G)$ as double cosets which are also finite union...

  9. Emotion Recognition from Persian Speech with Neural Network

    Directory of Open Access Journals (Sweden)

    Mina Hamidi

    2012-10-01

    Full Text Available In this paper, we report an effort towards automatic recognition of emotional states from continuousPersian speech. Due to the unavailability of appropriate database in the Persian language for emotionrecognition, at first, we built a database of emotional speech in Persian. This database consists of 2400wave clips modulated with anger, disgust, fear, sadness, happiness and normal emotions. Then we extractprosodic features, including features related to the pitch, intensity and global characteristics of the speechsignal. Finally, we applied neural networks for automatic recognition of emotion. The resulting averageaccuracy was about 78%.

  10. Implementation of Reliable Open Source IRIS Recognition System

    Directory of Open Access Journals (Sweden)

    Dhananjay Ikhar

    2013-12-01

    Full Text Available RELIABLE automatic recognition of persons has long been an attractive goal. As in all pattern recognition problems, the key issue is the relation between inter-class and intra-class variability: objects can be reliably classified only if the variability among different instances of a given class is less than the variability between different classes.The objective of this paper is to implement an open-source iris recognition system in order to verify the claimed performance of the technology. The development tool used will be MATLAB, and emphasis will be only on the software for performing recognition and not hardware for capturing an eye image. A reliable application development approach will be employed in order to produce results quickly. MATLAB provides an excellent environment, with its image processing toolbox. To test the system, a database of 756 grayscale eye images courtesy of Chinese Academy of Sciences-Institute of Automation (CASIA is used. The system is to be composed of a number of sub-systems, which correspond to each stage of iris recognition. These stages are- image acquisition, segmentation, normalization and feature encoding. The input to the system will be an eye image, and the output will be an iris template, which will provide a mathematical representation of the iris region. Which conclude the objectives to design recognition system are- study of different biometrics and their features? Study of different recognition systems and their steps, selection of simple and efficient recognition algorithm for implementation, selection of fast and efficient tool for processing, apply the implemented algorithm to different database and find out performance factors.

  11. Speech Recognition: How Do We Teach It?

    Science.gov (United States)

    Barksdale, Karl

    2002-01-01

    States that growing use of speech recognition software has made voice writing an essential computer skill. Describes how to present the topic, develop basic speech recognition skills, and teach speech recognition outlining, writing, proofreading, and editing. (Contains 14 references.) (SK)

  12. Is Hong Kong experiencing normalization of adolescent drug use? Some reflections on the normalization thesis.

    Science.gov (United States)

    Cheung, Nicole W T; Cheung, Yuet W

    2006-01-01

    The upsurge of consumption of party drugs among adolescents in recent years in Hong Kong has been part of the global trend of adolescent recreational use of drugs at rave parties, discos and similar party settings. Scholars in Western societies have recently proposed the thesis of "normalization of adolescent drug use" to describe such a trend. The normalization thesis points at three major aspects of the normalization phenomenon, namely, a rapid increase of the prevalence of drug use in young people, the widespread popularity of recreational drug use that is closely linked with the recent arrival of dance club culture, and a receptive attitude towards drug use as a normal part of leisure. This article aims to examine whether the normalization thesis can be applied to analyze the situation of adolescent drug use in Hong Kong. Data are drawn from official statistics and a recent survey conducted in 2002-2004 of drug use of Hong Kong marginal youths (N = 504). The case of Hong Kong only partially supports the thesis. Our findings show that the normalization of drug use among young people has occurred in Hong Kong, but the extent of normalization is smaller than those in Western societies like the United Kingdom. They also suggest that a recognition of possible cultural differences may be complementary to the normalization thesis. Limitations of the study are also noted.

  13. Monitoring the normal body

    DEFF Research Database (Denmark)

    Nissen, Nina Konstantin; Holm, Lotte; Baarts, Charlotte

    2015-01-01

    recruited by strategic sampling based on self-reported BMI 18.5-29.9 kg/m2 and socio-demographic factors. Inductive analysis was conducted. Results : Normal-weight and moderately overweight people have clear ideals for their body size. Despite being normal weight or close to this, they construct a variety...

  14. Spectral recognition of graphs

    Directory of Open Access Journals (Sweden)

    Cvetković Dragoš

    2012-01-01

    Full Text Available At some time, in the childhood of spectral graph theory, it was conjectured that non-isomorphic graphs have different spectra, i.e. that graphs are characterized by their spectra. Very quickly this conjecture was refuted and numerous examples and families of non-isomorphic graphs with the same spectrum (cospectral graphs were found. Still some graphs are characterized by their spectra and several mathematical papers are devoted to this topic. In applications to computer sciences, spectral graph theory is considered as very strong. The benefit of using graph spectra in treating graphs is that eigenvalues and eigenvectors of several graph matrices can be quickly computed. Spectral graph parameters contain a lot of information on the graph structure (both global and local including some information on graph parameters that, in general, are computed by exponential algorithms. Moreover, in some applications in data mining, graph spectra are used to encode graphs themselves. The Euclidean distance between the eigenvalue sequences of two graphs on the same number of vertices is called the spectral distance of graphs. Some other spectral distances (also based on various graph matrices have been considered as well. Two graphs are considered as similar if their spectral distance is small. If two graphs are at zero distance, they are cospectral. In this sense, cospectral graphs are similar. Other spectrally based measures of similarity between networks (not necessarily having the same number of vertices have been used in Internet topology analysis, and in other areas. The notion of spectral distance enables the design of various meta-heuristic (e.g., tabu search, variable neighbourhood search algorithms for constructing graphs with a given spectrum (spectral graph reconstruction. Several spectrally based pattern recognition problems appear in many areas (e.g., image segmentation in computer vision, alignment of protein-protein interaction networks in bio

  15. Kernel learning algorithms for face recognition

    CERN Document Server

    Li, Jun-Bao; Pan, Jeng-Shyang

    2013-01-01

    Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new

  16. CHARACTER RECOGNITION OF VIDEO SUBTITLES\\

    Directory of Open Access Journals (Sweden)

    Satish S Hiremath

    2016-11-01

    Full Text Available An important task in content based video indexing is to extract text information from videos. The challenges involved in text extraction and recognition are variation of illumination on each video frame with text, the text present on the complex background and different font size of the text. Using various image processing algorithms like morphological operations, blob detection and histogram of oriented gradients the character recognition of video subtitles is implemented. Segmentation, feature extraction and classification are the major steps of character recognition. Several experimental results are shown to demonstrate the performance of the proposed algorithm

  17. Logo Recognition Theory and Practice

    CERN Document Server

    Chen, Jingying

    2011-01-01

    Used by companies, organizations, and even individuals to promote recognition of their brand, logos can also act as a valuable means of identifying the source of a document. E-business applications can retrieve and catalog products according to their logos. Governmental agencies can easily inspect goods using smart mobile devices that use logo recognition techniques. However, because logos are two-dimensional shapes of varying complexity, the recognition process can be challenging. Although promising results have been found for clean logos, they have not been as robust for noisy logos. Logo Re

  18. Shared values and normality

    Institute of Scientific and Technical Information of China (English)

    ZHANG Wen-hua; PANG Xue-cheng

    2006-01-01

    This paper investigates the relationship between the normality and the shared values for a meromorphic function on the unit disc △.Based on Marty's normality criterion and through a detailed analysis of the meromorphic functions,it is shown that if for every f∈F,f and f(k) share a and b on △ and the zeros of f(z)-a are of multiplicity k≥3,then F is normal on △,where F is a family of meromorphic functions on the unit disc △,and a and b are distinct values.

  19. Improvements on EMG-based handwriting recognition with DTW algorithm.

    Science.gov (United States)

    Li, Chengzhang; Ma, Zheren; Yao, Lin; Zhang, Dingguo

    2013-01-01

    Previous works have shown that Dynamic Time Warping (DTW) algorithm is a proper method of feature extraction for electromyography (EMG)-based handwriting recognition. In this paper, several modifications are proposed to improve the classification process and enhance recognition accuracy. A two-phase template making approach has been introduced to generate templates with more salient features, and modified Mahalanobis Distance (mMD) approach is used to replace Euclidean Distance (ED) in order to minimize the interclass variance. To validate the effectiveness of such modifications, experiments were conducted, in which four subjects wrote lowercase letters at a normal speed and four-channel EMG signals from forearms were recorded. Results of offline analysis show that the improvements increased the average recognition accuracy by 9.20%.

  20. Neural Network Based Color Recognition for Bobbin Sorting Machine

    Directory of Open Access Journals (Sweden)

    Mu Zhang

    2013-07-01

    Full Text Available Winding is a key process in the manufacturing process of textile industry. The normal and effective operation of winding process plays a very important role on the textiles’ quality and economic effects. At present, a large proportion of bobbins which collected from winder still have yarn left over. The bobbin recycling is severely limited and quick running of winder is seriously restricted, the invention of the the automatic bobbin sorting machine has solved this problem. The ability to distinguish bobbin which has yarn left over from the rest and the classification accuracy of color are the two important performance indicators for bobbin sorting machine. According to the development and application of the color recognition technology and the artificial intelligence method, this study proposes a novel color recognition method that based on BP neural networks. The result shows that the accuracy of color recognition reaches 98%.  

  1. [Developmental change in facial recognition by premature infants during infancy].

    Science.gov (United States)

    Konishi, Yukihiko; Kusaka, Takashi; Nishida, Tomoko; Isobe, Kenichi; Itoh, Susumu

    2014-09-01

    Premature infants are thought to be at increased risk for developmental disorders. We evaluated facial recognition by premature infants during early infancy, as this ability has been reported to be impaired commonly in developmentally disabled children. In premature infants and full-term infants at the age of 4 months (4 corrected months for premature infants), visual behaviors while performing facial recognition tasks were determined and analyzed using an eye-tracking system (Tobii T60 manufactured by Tobii Technologics, Sweden). Both types of infants had a preference towards normal facial expressions; however, no preference towards the upper face was observed in premature infants. Our study suggests that facial recognition ability in premature infants may develop differently from that in full-term infants.

  2. Age-Related Differences in Lexical Access Relate to Speech Recognition in Noise

    Science.gov (United States)

    Carroll, Rebecca; Warzybok, Anna; Kollmeier, Birger; Ruigendijk, Esther

    2016-01-01

    Vocabulary size has been suggested as a useful measure of “verbal abilities” that correlates with speech recognition scores. Knowing more words is linked to better speech recognition. How vocabulary knowledge translates to general speech recognition mechanisms, how these mechanisms relate to offline speech recognition scores, and how they may be modulated by acoustical distortion or age, is less clear. Age-related differences in linguistic measures may predict age-related differences in speech recognition in noise performance. We hypothesized that speech recognition performance can be predicted by the efficiency of lexical access, which refers to the speed with which a given word can be searched and accessed relative to the size of the mental lexicon. We tested speech recognition in a clinical German sentence-in-noise test at two signal-to-noise ratios (SNRs), in 22 younger (18–35 years) and 22 older (60–78 years) listeners with normal hearing. We also assessed receptive vocabulary, lexical access time, verbal working memory, and hearing thresholds as measures of individual differences. Age group, SNR level, vocabulary size, and lexical access time were significant predictors of individual speech recognition scores, but working memory and hearing threshold were not. Interestingly, longer accessing times were correlated with better speech recognition scores. Hierarchical regression models for each subset of age group and SNR showed very similar patterns: the combination of vocabulary size and lexical access time contributed most to speech recognition performance; only for the younger group at the better SNR (yielding about 85% correct speech recognition) did vocabulary size alone predict performance. Our data suggest that successful speech recognition in noise is mainly modulated by the efficiency of lexical access. This suggests that older adults’ poorer performance in the speech recognition task may have arisen from reduced efficiency in lexical access

  3. Normal pressure hydrocephalus

    Science.gov (United States)

    Hydrocephalus - occult; Hydrocephalus - idiopathic; Hydrocephalus - adult; Hydrocephalus - communicating; Dementia - hydrocephalus; NPH ... Ferri FF. Normal pressure hydrocephalus. In: Ferri FF, ed. ... Elsevier; 2016:chap 648. Rosenberg GA. Brain edema and disorders ...

  4. Normality in analytical psychology.

    Science.gov (United States)

    Myers, Steve

    2013-12-01

    Although C.G. Jung's interest in normality wavered throughout his career, it was one of the areas he identified in later life as worthy of further research. He began his career using a definition of normality which would have been the target of Foucault's criticism, had Foucault chosen to review Jung's work. However, Jung then evolved his thinking to a standpoint that was more aligned to Foucault's own. Thereafter, the post Jungian concept of normality has remained relatively undeveloped by comparison with psychoanalysis and mainstream psychology. Jung's disjecta membra on the subject suggest that, in contemporary analytical psychology, too much focus is placed on the process of individuation to the neglect of applications that consider collective processes. Also, there is potential for useful research and development into the nature of conflict between individuals and societies, and how normal people typically develop in relation to the spectrum between individuation and collectivity.

  5. Normal Functioning Family

    Science.gov (United States)

    ... Spread the Word Shop AAP Find a Pediatrician Family Life Medical Home Family Dynamics Adoption & Foster Care ... Español Text Size Email Print Share Normal Functioning Family Page Content Article Body Is there any way ...

  6. Gesture recognition on smart cameras

    Science.gov (United States)

    Dziri, Aziz; Chevobbe, Stephane; Darouich, Mehdi

    2013-02-01

    Gesture recognition is a feature in human-machine interaction that allows more natural interaction without the use of complex devices. For this reason, several methods of gesture recognition have been developed in recent years. However, most real time methods are designed to operate on a Personal Computer with high computing resources and memory. In this paper, we analyze relevant methods found in the literature in order to investigate the ability of smart camera to execute gesture recognition algorithms. We elaborate two hand gesture recognition pipelines. The first method is based on invariant moments extraction and the second on finger tips detection. The hand detection method used for both pipeline is based on skin color segmentation. The results obtained show that the un-optimized versions of invariant moments method and finger tips detection method can reach 10 fps on embedded processor and use about 200 kB of memory.

  7. Stimulus Recognition and Associative Coding

    Science.gov (United States)

    Runquist, Willard N.; Evans, Annabel

    1972-01-01

    Purpose of this experiment was to investigate the relationship between stimulus recognition and various learning conditions which were designed to affect both stimulus encoding and associative learning in a paired-associate task. (Authors)

  8. Similarity measures for face recognition

    CERN Document Server

    Vezzetti, Enrico

    2015-01-01

    Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.

  9. Defect Recognition in Thermosonic Imaging

    Institute of Scientific and Technical Information of China (English)

    CHEN Dapeng; WU Naiming; ZHANG Zheng

    2012-01-01

    This work is aimed at developing an effective method for defect recognition in thermosonic imaging.The heat mechanism of thermosonic imaging is introduced,and the problem for defect recognition is discussed.For this purpose,defect existing in the inner wall of a metal pipeline specimen and defects embedded in a carbon fiber reinforced plastic (CFRP) laminate are tested.The experimental data are processed by pulse phase thermography (PPT) method to show the phase images at different frequencies,and the characteristic of phase angle vs frequency curve of thermal anomalies and sound area is analyzed.A binary image,which is based on the characteristic value of defects,is obtained by a new recognition algorithm to show the defects.Results demonstrate good defect recognition performance for thermosonic imaging,and the reliability of this technique can be improved by the method.

  10. Pattern recognition and string matching

    CERN Document Server

    Cheng, Xiuzhen

    2002-01-01

    The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica­ tion, matching, mining, feature selection, and applications. Each chapter is self-contained, and presents either novel methodological approaches or applications of existing theories and techniques. The aim, intent, and motivation for publishing this book is to pro­ vide a reference tool for the increasing number of readers who depend upon pattern recognition or string matching in some way. This includes student...

  11. Proficient Character Recognition from Images

    National Research Council Canada - National Science Library

    Poornima T M; M Amanullah

    2016-01-01

    .... Two key components of most systems are (i) text detection from images and (ii) text recognition, and many methods have been introduced to design better feature representations and models for both...

  12. Effective indexing for face recognition

    Science.gov (United States)

    Sochenkov, I.; Sochenkova, A.; Vokhmintsev, A.; Makovetskii, A.; Melnikov, A.

    2016-09-01

    Face recognition is one of the most important tasks in computer vision and pattern recognition. Face recognition is useful for security systems to provide safety. In some situations it is necessary to identify the person among many others. In this case this work presents new approach in data indexing, which provides fast retrieval in big image collections. Data indexing in this research consists of five steps. First, we detect the area containing face, second we align face, and then we detect areas containing eyes and eyebrows, nose, mouth. After that we find key points of each area using different descriptors and finally index these descriptors with help of quantization procedure. The experimental analysis of this method is performed. This paper shows that performing method has results at the level of state-of-the-art face recognition methods, but it is also gives results fast that is important for the systems that provide safety.

  13. Idiopathic Normal Pressure Hydrocephalus

    OpenAIRE

    2016-01-01

    Idiopathic normal pressure hydrocephalus (iNPH) is a potentially reversible neurodegenerative disease commonly characterized by a triad of dementia, gait, and urinary disturbance. Advancements in diagnosis and treatment have aided in properly identifying and improving symptoms in patients. However, a large proportion of iNPH patients remain either undiagnosed or misdiagnosed. Using PubMed search engine of keywords “normal pressure hydrocephalus,” “diagnosis,” “shunt treatment,” “biomarkers,” ...

  14. On Tangut Historical Documents Recognition*

    Science.gov (United States)

    Liu, Changqing

    As the Tangut studies have made progress, a considerable number of Tangut historical documents' copies have been published. It is of great importance to carry out digitalization and domestication of these copies. The paper firstly makes an initial processing of images by global threshold, then dissect the photocopies by scanning. Finally adopts the recognition approach of principal component analysis. The experiment shows that a better recognition can be achieved by calculation without extra time.

  15. [Neurological disease and facial recognition].

    Science.gov (United States)

    Kawamura, Mitsuru; Sugimoto, Azusa; Kobayakawa, Mutsutaka; Tsuruya, Natsuko

    2012-07-01

    To discuss the neurological basis of facial recognition, we present our case reports of impaired recognition and a review of previous literature. First, we present a case of infarction and discuss prosopagnosia, which has had a large impact on face recognition research. From a study of patient symptoms, we assume that prosopagnosia may be caused by unilateral right occipitotemporal lesion and right cerebral dominance of facial recognition. Further, circumscribed lesion and degenerative disease may also cause progressive prosopagnosia. Apperceptive prosopagnosia is observed in patients with posterior cortical atrophy (PCA), pathologically considered as Alzheimer's disease, and associative prosopagnosia in frontotemporal lobar degeneration (FTLD). Second, we discuss face recognition as part of communication. Patients with Parkinson disease show social cognitive impairments, such as difficulty in facial expression recognition and deficits in theory of mind as detected by the reading the mind in the eyes test. Pathological and functional imaging studies indicate that social cognitive impairment in Parkinson disease is possibly related to damages in the amygdalae and surrounding limbic system. The social cognitive deficits can be observed in the early stages of Parkinson disease, and even in the prodromal stage, for example, patients with rapid eye movement (REM) sleep behavior disorder (RBD) show impairment in facial expression recognition. Further, patients with myotonic dystrophy type 1 (DM 1), which is a multisystem disease that mainly affects the muscles, show social cognitive impairment similar to that of Parkinson disease. Our previous study showed that facial expression recognition impairment of DM 1 patients is associated with lesion in the amygdalae and insulae. Our study results indicate that behaviors and personality traits in DM 1 patients, which are revealed by social cognitive impairment, are attributable to dysfunction of the limbic system.

  16. Pattern Recognition Theory of Mind

    OpenAIRE

    2009-01-01

    I propose that pattern recognition, memorization and processing are key concepts that can be a principle set for the theoretical modeling of the mind function. Most of the questions about the mind functioning can be answered by a descriptive modeling and definitions from these principles. An understandable consciousness definition can be drawn based on the assumption that a pattern recognition system can recognize its own patterns of activity. The principles, descriptive modeling and definiti...

  17. A REVIEW ON THE DEVELOPMENT OF INDONESIAN SIGN LANGUAGE RECOGNITION SYSTEM

    Directory of Open Access Journals (Sweden)

    Sutarman

    2013-01-01

    Full Text Available Sign language is mainly employed by hearing-impaired people to communicate with each other. However, communication with normal people is a major handicap for them since normal people do not understand their sign language. Sign language recognition is needed for realizing a human oriented interactive system that can perform an interaction like normal communication. Sign language recognition basically uses two approaches: (1 computer vision-based gesture recognition, in which a camera is used as input and videos are captured in the form of video files stored before being processed using image processing; (2 approach based on sensor data, which is done by using a series of sensors that are integrated with gloves to get the motion features finger grooves and hand movements. Different of sign languages exist around the world, each with its own vocabulary and gestures. Some examples are American Sign Language (ASL, Chinese Sign Language (CSL, British Sign Language (BSL, Indonesian Sign Language (ISL and so on. The structure of Indonesian Sign Language (ISL is different from the sign language of other countries, in that words can be formed from the prefix and or suffix. In order to improve recognition accuracy, researchers use methods, such as the hidden Markov model, artificial neural networks and dynamic time warping. Effective algorithms for segmentation, matching the classification and pattern recognition have evolved. The main objective of this study is to review the sign language recognition methods in order to choose the best method for developing the Indonesian sign language recognition system.

  18. Holistic processing predicts face recognition.

    Science.gov (United States)

    Richler, Jennifer J; Cheung, Olivia S; Gauthier, Isabel

    2011-04-01

    The concept of holistic processing is a cornerstone of face-recognition research. In the study reported here, we demonstrated that holistic processing predicts face-recognition abilities on the Cambridge Face Memory Test and on a perceptual face-identification task. Our findings validate a large body of work that relies on the assumption that holistic processing is related to face recognition. These findings also reconcile the study of face recognition with the perceptual-expertise work it inspired; such work links holistic processing of objects with people's ability to individuate them. Our results differ from those of a recent study showing no link between holistic processing and face recognition. This discrepancy can be attributed to the use in prior research of a popular but flawed measure of holistic processing. Our findings salvage the central role of holistic processing in face recognition and cast doubt on a subset of the face-perception literature that relies on a problematic measure of holistic processing.

  19. Voice congruency facilitates word recognition.

    Directory of Open Access Journals (Sweden)

    Sandra Campeanu

    Full Text Available Behavioral studies of spoken word memory have shown that context congruency facilitates both word and source recognition, though the level at which context exerts its influence remains equivocal. We measured event-related potentials (ERPs while participants performed both types of recognition task with words spoken in four voices. Two voice parameters (i.e., gender and accent varied between speakers, with the possibility that none, one or two of these parameters was congruent between study and test. Results indicated that reinstating the study voice at test facilitated both word and source recognition, compared to similar or no context congruency at test. Behavioral effects were paralleled by two ERP modulations. First, in the word recognition test, the left parietal old/new effect showed a positive deflection reflective of context congruency between study and test words. Namely, the same speaker condition provided the most positive deflection of all correctly identified old words. In the source recognition test, a right frontal positivity was found for the same speaker condition compared to the different speaker conditions, regardless of response success. Taken together, the results of this study suggest that the benefit of context congruency is reflected behaviorally and in ERP modulations traditionally associated with recognition memory.

  20. Pattern Recognition Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Santaji Ghorpade

    2010-12-01

    Full Text Available Face Recognition has been identified as one of the attracting research areas and it has drawn the attention of many researchers due to its varying applications such as security systems, medical systems,entertainment, etc. Face recognition is the preferred mode of identification by humans: it is natural,robust and non-intrusive. A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else.Examples of such applications include secure access to buildings, computer systems, laptops, cellular phones, and ATMs. In the absence of robust personal recognition schemes, these systems are vulnerable to the wiles of an impostor.In this paper we have developed and illustrated a recognition system for human faces using a novel Kohonen self-organizing map (SOM or Self-Organizing Feature Map (SOFM based retrieval system.SOM has good feature extracting property due to its topological ordering. The Facial Analytics results for the 400 images of AT&T database reflects that the face recognition rate using one of the neural network algorithm SOM is 85.5% for 40 persons.

  1. Impaired recognition of scary music following unilateral temporal lobe excision.

    Science.gov (United States)

    Gosselin, Nathalie; Peretz, Isabelle; Noulhiane, Marion; Hasboun, Dominique; Beckett, Christine; Baulac, Michel; Samson, Séverine

    2005-03-01

    Music constitutes an ideal means to create a sense of suspense in films. However, there has been minimal investigation into the underlying cerebral organization for perceiving danger created by music. In comparison, the amygdala's role in recognition of fear in non-musical contexts has been well established. The present study sought to fill this gap in exploring how patients with amygdala resection recognize emotional expression in music. To this aim, we tested 16 patients with left (LTR; n = 8) or right (RTR; n = 8) medial temporal resection (including amygdala) for the relief of medically intractable seizures and 16 matched controls in an emotion recognition task involving instrumental music. The musical selections were purposely created to induce fear, peacefulness, happiness and sadness. Participants were asked to rate to what extent each musical passage expressed these four emotions on 10-point scales. In order to check for the presence of a perceptual problem, the same musical selections were presented to the participants in an error detection task. None of the patients was found to perform below controls in the perceptual task. In contrast, both LTR and RTR patients were found to be impaired in the recognition of scary music. Recognition of happy and sad music was normal. These findings suggest that the anteromedial temporal lobe (including the amygdala) plays a role in the recognition of danger in a musical context.

  2. Discrete Meyer Wavelet Transform Features For online Hangul Script Recognition

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2012-09-01

    Full Text Available Online hangul script recognition is important when writers input characters into computer and communication apparatus (such as PDA, Mobile Phone. In this study, a Wavelet Transform Features-based method for performance improvement of online handwritten hangul character recognition is proposed. The main idea is applying the Discrete Wavelet Transform (DWT spectral analysis to the recognition of online hangul script. This method is based on the fact that online scripts offer space and time information. Locations of sample points belonging to a script give only space information and the order of occurrences of sample points provides time information. Given an online handwritten character sample, after a series of preprocessing, we obtain a 64×64 normalized online hangul handwritten script with the time information. The order of sample points can be the index of sequences. One sequence is the vertical coordinate of sample points. The second sequence is the horizontal coordinate of sample points. The third sequence is the product of the vertical coordinate and horizontal coordinate of sample points. The fourth sequence is the ratio between the vertical coordinate difference and horizontal coordinate difference of two sample points. The four sequences are combined as a vector whose size is 512. The vector is convoluted with the Meyer Wavelet and its dimension is reduced from 512 to 128 by Linear Discriminant Analysis (LDA scheme. Modified Quadratic Discriminant Functions (MQDF is utilized as the classifier for charter recognition. The Experiment results demonstrate that the method can improve the accuracy of character recognition.

  3. Recognition of control chart patterns with incomplete samples

    Science.gov (United States)

    Miftah Abdelrahman Senoussi, Ahmed; Masood, Ibrahim; Nasrull Abdol Rahman, Mohd; Fahrul Hassan, Mohd

    2017-08-01

    In quality control, automated recognition of statistical process control (SPC) chart patterns is an effective technique for monitoring unnatural variation (UV) in manufacturing process. In most studies, focus was given on complete patterns by assuming there is no constrain in the SPC samples. Nevertheless, there is in-practice case whereby the SPC samples cannot be captured properly due to measurement sensor error or human error. Thus, this research aims to design a recognition scheme for incomplete samples pattern that will be useful for an industrial application. The design methodology involves three phases: (i) simulation of UV and SPC chart patterns, (ii) design of pattern recognition scheme, and (iii) evaluation of performance recognition. It involves modelling of the simulated SPC samples in bivariate quality control, raw data input representation, and recognizer training and testing. The proposed technique indicates a high recognition accuracy (normal pattern = 99.5%, shift patterns = 97.5%). This research will provide a new perspective in SPC charting scheme when dealing with constraint in terms of incomplete samples, which is greatly useful for an industrial practitioner in finding the solution for corrective action.

  4. Comparing Face Detection and Recognition Techniques

    OpenAIRE

    Korra, Jyothi

    2016-01-01

    This paper implements and compares different techniques for face detection and recognition. One is find where the face is located in the images that is face detection and second is face recognition that is identifying the person. We study three techniques in this paper: Face detection using self organizing map (SOM), Face recognition by projection and nearest neighbor and Face recognition using SVM.

  5. Tuning Iris Recognition for Noisy Images

    Science.gov (United States)

    Ferreira, Artur; Lourenço, André; Pinto, Bárbara; Tendeiro, Jorge

    The use of iris recognition for human authentication has been spreading in the past years. Daugman has proposed a method for iris recognition, composed by four stages: segmentation, normalization, feature extraction, and matching. In this paper we propose some modifications and extensions to Daugman's method to cope with noisy images. These modifications are proposed after a study of images of CASIA and UBIRIS databases. The major modification is on the computationally demanding segmentation stage, for which we propose a faster and equally accurate template matching approach. The extensions on the algorithm address the important issue of pre-processing, that depends on the image database, being mandatory when we have a non infra-red camera, like a typical WebCam. For this scenario, we propose methods for reflection removal and pupil enhancement and isolation. The tests, carried out by our C# application on grayscale CASIA and UBIRIS images, show that the template matching segmentation method is more accurate and faster than the previous one, for noisy images. The proposed algorithms are found to be efficient and necessary when we deal with non infra-red images and non uniform illumination.

  6. Intrusion detection using pattern recognition methods

    Science.gov (United States)

    Jiang, Nan; Yu, Li

    2007-09-01

    Today, cyber attacks such as worms, scanning, active attackers are pervasive in Internet. A number of security approaches are proposed to address this problem, among which the intrusion detection system (IDS) appears to be one of the major and most effective solutions for defending against malicious users. Essentially, intrusion detection problem can be generalized as a classification problem, whose goal is to distinguish normal behaviors and anomalies. There are many well-known pattern recognition algorithms for classification purpose. In this paper we describe the details of applying pattern recognition methods to the intrusion detection research field. Experimenting on the KDDCUP 99 data set, we first use information gain metric to reduce the dimensionality of the original feature space. Two supervised methods, the support vector machine as well as the multi-layer neural network have been tested and the results display high detection rate and low false alarm rate, which is promising for real world applications. In addition, three unsupervised methods, Single-Linkage, K-Means, and CLIQUE, are also implemented and evaluated in the paper. The low computational complexity reveals their application in initial data reduction process.

  7. Ratios of Normal Variables

    Directory of Open Access Journals (Sweden)

    George Marsaglia

    2006-05-01

    Full Text Available This article extends and amplifies on results from a paper of over forty years ago. It provides software for evaluating the density and distribution functions of the ratio z/w for any two jointly normal variates z,w, and provides details on methods for transforming a general ratio z/w into a standard form, (a+x/(b+y , with x and y independent standard normal and a, b non-negative constants. It discusses handling general ratios when, in theory, none of the moments exist yet practical considerations suggest there should be approximations whose adequacy can be verified by means of the included software. These approximations show that many of the ratios of normal variates encountered in practice can themselves be taken as normally distributed. A practical rule is developed: If a < 2.256 and 4 < b then the ratio (a+x/(b+y is itself approximately normally distributed with mean μ = a/(1.01b − .2713 and variance 2 = (a2 + 1/(b2 + .108b − 3.795 − μ2.

  8. Ratios of Normal Variables

    Directory of Open Access Journals (Sweden)

    George Marsaglia

    2006-05-01

    Full Text Available This article extends and amplifies on results from a paper of over forty years ago. It provides software for evaluating the density and distribution functions of the ratio z/w for any two jointly normal variates z,w, and provides details on methods for transforming a general ratio z/w into a standard form, (a+x/(b+y , with x and y independent standard normal and a, b non-negative constants. It discusses handling general ratios when, in theory, none of the moments exist yet practical considerations suggest there should be approximations whose adequacy can be verified by means of the included software. These approximations show that many of the ratios of normal variates encountered in practice can themselves be taken as normally distributed. A practical rule is developed: If a < 2.256 and 4 < b then the ratio (a+x/(b+y is itself approximately normally distributed with mean μ = a/(1.01b - .2713 and variance σ2 = (a2 + 1/(b2 + .108b - 3.795 μ2.

  9. Effects of Training of Affect Recognition on the recognition and visual exploration of emotional faces in schizophrenia.

    Science.gov (United States)

    Drusch, Katharina; Stroth, Sanna; Kamp, Daniel; Frommann, Nicole; Wölwer, Wolfgang

    2014-11-01

    Schizophrenia patients have impairments in facial affect recognition and display scanpath abnormalities during the visual exploration of faces. These abnormalities are characterized by fewer fixations on salient feature areas and longer fixation durations. The present study investigated whether social-cognitive remediation not only improves performance in facial affect recognition but also normalizes patients' gaze behavior while looking at faces. Within a 2 × 2-design (group × time), 16 schizophrenia patients and 16 healthy controls performed a facial affect recognition task with concomitant infrared oculography at baseline (T0) and after six weeks (T1). Between the measurements, patients completed the Training of Affect Recognition (TAR) program. The influence of the training on facial affect recognition (percent of correct answers) and gaze behavior (number and mean duration of fixations into salient or non-salient facial areas) was assessed. In line with former studies, at baseline patients showed poorer facial affect recognition than controls and aberrant scanpaths, and after TAR facial affect recognition was improved. Concomitant with improvements in performance, the number of fixations in feature areas ('mouth') increased while fixations in non-feature areas ('white space') decreased. However, the change in fixation behavior did not correlate with the improvement in performance. After TAR, patients pay more attention to facial areas that contain information about a displayed emotion. Although this may contribute to the improved performance, the lack of a statistical correlation implies that this factor is not sufficient to explain the underlying mechanism of the treatment effect. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Visual object recognition and category-specificity

    DEFF Research Database (Denmark)

    Gerlach, Christian

    in visual long-term memory. In the thesis it is described how this simple model can account for a wide range of findings on category-specificity in both patients with brain damage and normal subjects. Finally, two hypotheses regarding the neural substrates of the model's components - and how activation......This thesis is based on seven published papers. The majority of the papers address two topics in visual object recognition: (i) category-effects at pre-semantic stages, and (ii) the integration of visual elements into elaborate shape descriptions corresponding to whole objects or large object parts...... (shape configuration). In the early writings these two topics were examined more or less independently. In later works, findings concerning category-effects and shape configuration merge into an integrated model, termed RACE, advanced to explain category-effects arising at pre-semantic stages in visual...

  11. Visual object recognition and category-specificity

    DEFF Research Database (Denmark)

    Gerlach, Christian

    This thesis is based on seven published papers. The majority of the papers address two topics in visual object recognition: (i) category-effects at pre-semantic stages, and (ii) the integration of visual elements into elaborate shape descriptions corresponding to whole objects or large object parts...... is a description that can be matched with structural representations of whole objects or object parts stored in visual long-term memory. The process of finding a match between the configured description and stored object representations is thought of as a race among stored object representations that compete...... in visual long-term memory. In the thesis it is described how this simple model can account for a wide range of findings on category-specificity in both patients with brain damage and normal subjects. Finally, two hypotheses regarding the neural substrates of the model's components - and how activation...

  12. Normalized Information Distance

    CERN Document Server

    Vitanyi, Paul M B; Cilibrasi, Rudi L; Li, Ming

    2008-01-01

    The normalized information distance is a universal distance measure for objects of all kinds. It is based on Kolmogorov complexity and thus uncomputable, but there are ways to utilize it. First, compression algorithms can be used to approximate the Kolmogorov complexity if the objects have a string representation. Second, for names and abstract concepts, page count statistics from the World Wide Web can be used. These practical realizations of the normalized information distance can then be applied to machine learning tasks, expecially clustering, to perform feature-free and parameter-free data mining. This chapter discusses the theoretical foundations of the normalized information distance and both practical realizations. It presents numerous examples of successful real-world applications based on these distance measures, ranging from bioinformatics to music clustering to machine translation.

  13. Face Recognition Combining Eigen Features with a Parzen Classifier

    Institute of Scientific and Technical Information of China (English)

    SUN Xin; LIU Bing; LIU Ben-yong

    2005-01-01

    A face recognition scheme is proposed, wherein a face image is preprocessed by pixel averaging and energy normalizing to reduce data dimension and brightness variation effect, followed by the Fourier transform to estimate the spectrum of the preprocessed image. The principal component analysis is conducted on the spectra of a face image to obtain eigen features. Combining eigen features with a Parzen classifier, experiments are taken on the ORL face database.

  14. Normalization of satellite imagery

    Science.gov (United States)

    Kim, Hongsuk H.; Elman, Gregory C.

    1990-01-01

    Sets of Thematic Mapper (TM) imagery taken over the Washington, DC metropolitan area during the months of November, March and May were converted into a form of ground reflectance imagery. This conversion was accomplished by adjusting the incident sunlight and view angles and by applying a pixel-by-pixel correction for atmospheric effects. Seasonal color changes of the area can be better observed when such normalization is applied to space imagery taken in time series. In normalized imagery, the grey scale depicts variations in surface reflectance and tonal signature of multi-band color imagery can be directly interpreted for quantitative information of the target.

  15. Kazakh Traditional Dance Gesture Recognition

    Science.gov (United States)

    Nussipbekov, A. K.; Amirgaliyev, E. N.; Hahn, Minsoo

    2014-04-01

    Full body gesture recognition is an important and interdisciplinary research field which is widely used in many application spheres including dance gesture recognition. The rapid growth of technology in recent years brought a lot of contribution in this domain. However it is still challenging task. In this paper we implement Kazakh traditional dance gesture recognition. We use Microsoft Kinect camera to obtain human skeleton and depth information. Then we apply tree-structured Bayesian network and Expectation Maximization algorithm with K-means clustering to calculate conditional linear Gaussians for classifying poses. And finally we use Hidden Markov Model to detect dance gestures. Our main contribution is that we extend Kinect skeleton by adding headwear as a new skeleton joint which is calculated from depth image. This novelty allows us to significantly improve the accuracy of head gesture recognition of a dancer which in turn plays considerable role in whole body gesture recognition. Experimental results show the efficiency of the proposed method and that its performance is comparable to the state-of-the-art system performances.

  16. An audiovisual emotion recognition system

    Science.gov (United States)

    Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun

    2007-12-01

    Human emotions could be expressed by many bio-symbols. Speech and facial expression are two of them. They are both regarded as emotional information which is playing an important role in human-computer interaction. Based on our previous studies on emotion recognition, an audiovisual emotion recognition system is developed and represented in this paper. The system is designed for real-time practice, and is guaranteed by some integrated modules. These modules include speech enhancement for eliminating noises, rapid face detection for locating face from background image, example based shape learning for facial feature alignment, and optical flow based tracking algorithm for facial feature tracking. It is known that irrelevant features and high dimensionality of the data can hurt the performance of classifier. Rough set-based feature selection is a good method for dimension reduction. So 13 speech features out of 37 ones and 10 facial features out of 33 ones are selected to represent emotional information, and 52 audiovisual features are selected due to the synchronization when speech and video fused together. The experiment results have demonstrated that this system performs well in real-time practice and has high recognition rate. Our results also show that the work in multimodules fused recognition will become the trend of emotion recognition in the future.

  17. Research on Space Target Recognition Algorithm Based on Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    Shen Yiying

    2013-07-01

    Full Text Available The space target recognition algorithm, which is based on the time series of radar cross section (RCS, is proposed in this paper to solve the problems of space target recognition in the active radar system. In the algorithm, EMD method is applied for the first time to extract the eigen of RCS time series. The normalized instantaneous frequencies of high-frequency intrinsic mode functions obtained by EMD are used as the eigen values for the recognition, and an effective target recognition criterion is established. The effectiveness and the stability of the algorithm are verified by both simulation data and real data. In addition, the algorithm could reduce the estimation bias of RCS caused by inaccurate evaluation, and it is of great significance in promoting the target recognition ability of narrow-band radar in practice.  

  18. Implementation of age and gender recognition system for intelligent digital signage

    Science.gov (United States)

    Lee, Sang-Heon; Sohn, Myoung-Kyu; Kim, Hyunduk

    2015-12-01

    Intelligent digital signage systems transmit customized advertising and information by analyzing users and customers, unlike existing system that presented advertising in the form of broadcast without regard to type of customers. Currently, development of intelligent digital signage system has been pushed forward vigorously. In this study, we designed a system capable of analyzing gender and age of customers based on image obtained from camera, although there are many different methods for analyzing customers. We conducted age and gender recognition experiments using public database. The age/gender recognition experiments were performed through histogram matching method by extracting Local binary patterns (LBP) features after facial area on input image was normalized. The results of experiment showed that gender recognition rate was as high as approximately 97% on average. Age recognition was conducted based on categorization into 5 age classes. Age recognition rates for women and men were about 67% and 68%, respectively when that conducted separately for different gender.

  19. Effect of Vowel Context on the Recognition of Initial Consonants in Kannada.

    Science.gov (United States)

    Kalaiah, Mohan Kumar; Bhat, Jayashree S

    2017-09-01

    The present study was carried out to investigate the effect of vowel context on the recognition of Kannada consonants in quiet for young adults. A total of 17 young adults with normal hearing in both ears participated in the study. The stimuli included consonant-vowel syllables, spoken by 12 native speakers of Kannada. Consonant recognition task was carried out as a closed-set (fourteen-alternative forced-choice). The present study showed an effect of vowel context on the perception of consonants. Maximum consonant recognition score was obtained in the /o/ vowel context, followed by the /a/ and /u/ vowel contexts, and then the /e/ context. Poorest consonant recognition score was obtained in the vowel context /i/. Vowel context has an effect on the recognition of Kannada consonants, and the vowel effect was unique for Kannada consonants.

  20. Human Motion Recognition Using Ultra-Wideband Radar and Cameras on Mobile Robot

    Institute of Scientific and Technical Information of China (English)

    LI Tuanjie; GE Mengmeng

    2009-01-01

    Cameras can reliably detect human motions in a normal environment, but they are usually affected by sudden illumination changes and complex conditions, which are the major obstacles to the reliability and robustness of the system. To solve this problem, a novel integration method was proposed to combine bi-static uitra-wideband radar and cameras. In this recognition system, two cameras are used to localize the object's region, regions while a radar is used to obtain its 3D motion models on a mobile robot. The recognition results can be matched in the 3D motion library in order to recognize its motions. To confirm the effectiveness of the proposed method, the experi-mental results of recognition using vision sensors and those of recognition using the integration method were com-pared in different environments. Higher correct-recognition rate is achieved in the experiment.

  1. Normalized information distance

    NARCIS (Netherlands)

    Vitányi, P.M.B.; Balbach, F.J.; Cilibrasi, R.L.; Li, M.; Emmert-Streib, F.; Dehmer, M.

    2009-01-01

    The normalized information distance is a universal distance measure for objects of all kinds. It is based on Kolmogorov complexity and thus uncomputable, but there are ways to utilize it. First, compression algorithms can be used to approximate the Kolmogorov complexity if the objects have a string

  2. Normalized information distance

    NARCIS (Netherlands)

    Vitányi, P.M.B.; Balbach, F.J.; Cilibrasi, R.L.; Li, M.

    2008-01-01

    The normalized information distance is a universal distance measure for objects of all kinds. It is based on Kolmogorov complexity and thus uncomputable, but there are ways to utilize it. First, compression algorithms can be used to approximate the Kolmogorov complexity if the objects have a string

  3. Normals to a Parabola

    Science.gov (United States)

    Srinivasan, V. K.

    2013-01-01

    Given a parabola in the standard form y[superscript 2] = 4ax, corresponding to three points on the parabola, such that the normals at these three points P, Q, R concur at a point M = (h, k), the equation of the circumscribing circle through the three points P, Q, and R provides a tremendous opportunity to illustrate "The Art of Algebraic…

  4. Back to Normal

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Xinjiang officials speed up the investigation of July 5 riot suspects and restore social order Life in Urumqi has gone back to normal one month after the July 5 riot that killed nearly 200 people in the capital city of China’s northwestern

  5. Normality in Analytical Psychology

    Directory of Open Access Journals (Sweden)

    Steve Myers

    2013-11-01

    Full Text Available Although C.G. Jung’s interest in normality wavered throughout his career, it was one of the areas he identified in later life as worthy of further research. He began his career using a definition of normality which would have been the target of Foucault’s criticism, had Foucault chosen to review Jung’s work. However, Jung then evolved his thinking to a standpoint that was more aligned to Foucault’s own. Thereafter, the post Jungian concept of normality has remained relatively undeveloped by comparison with psychoanalysis and mainstream psychology. Jung’s disjecta membra on the subject suggest that, in contemporary analytical psychology, too much focus is placed on the process of individuation to the neglect of applications that consider collective processes. Also, there is potential for useful research and development into the nature of conflict between individuals and societies, and how normal people typically develop in relation to the spectrum between individuation and collectivity.

  6. Normal modal preferential consequence

    CSIR Research Space (South Africa)

    Britz, K

    2012-12-01

    Full Text Available of necessitation holds for the corresponding consequence relations, as one would expect it to. We present a representation result for this tightened framework, and investigate appropriate notions of entailment in this context|normal entailment, and a rational...

  7. Statokinesigram normalization method.

    Science.gov (United States)

    de Oliveira, José Magalhães

    2017-02-01

    Stabilometry is a technique that aims to study the body sway of human subjects, employing a force platform. The signal obtained from this technique refers to the position of the foot base ground-reaction vector, known as the center of pressure (CoP). The parameters calculated from the signal are used to quantify the displacement of the CoP over time; there is a large variability, both between and within subjects, which prevents the definition of normative values. The intersubject variability is related to differences between subjects in terms of their anthropometry, in conjunction with their muscle activation patterns (biomechanics); and the intrasubject variability can be caused by a learning effect or fatigue. Age and foot placement on the platform are also known to influence variability. Normalization is the main method used to decrease this variability and to bring distributions of adjusted values into alignment. In 1996, O'Malley proposed three normalization techniques to eliminate the effect of age and anthropometric factors from temporal-distance parameters of gait. These techniques were adopted to normalize the stabilometric signal by some authors. This paper proposes a new method of normalization of stabilometric signals to be applied in balance studies. The method was applied to a data set collected in a previous study, and the results of normalized and nonnormalized signals were compared. The results showed that the new method, if used in a well-designed experiment, can eliminate undesirable correlations between the analyzed parameters and the subjects' characteristics and show only the experimental conditions' effects.

  8. Mobile-Customer Identity Recognition

    Institute of Scientific and Technical Information of China (English)

    LI Zhan; XU Ji-sheng; XU Min; SUN Hong

    2005-01-01

    By utilizing artificial intelligence and pattern recognition techniques, we propose an integrated mobile-customer identity recognition approach in this paper, based on customer's behavior characteristics extracted from the customer information database. To verify the effectiveness of this approach, a test has been run on the dataset consisting of 1 000 customers in 3 consecutive months. The result is compared with the real dataset in the fourth month consisting of 162 customers, which has been set as the customers for recognition. The high correct rate of the test (96.30%), together with 1.87% of the judge-by-mistake rate and 7.82% of the leaving-out rate, demonstrates the effectiveness of this approach.

  9. Mandarin recognition over the telephone

    Science.gov (United States)

    Kao, Yuhung

    1996-06-01

    Mandarin Chinese is the official language in China and Taiwan, it is the native language of a quarter of the world population. As the services enabled by speech recognition technology (e.g. telephone voice dialing, information query) become more popular in English, we would like to extend this capability to other languages. Mandarin is one of the major languages under research in our laboratory. This paper describes how we extend our work in English speech recognition into Mandarin. We will described the corpus: Voice Across Taiwan, the training of a complete set of Mandarin syllable models, preliminary performance results and error analysis. A fast prototyping system was built, where a user can write any context free grammar with no restriction of vocabulary, then the grammar can be compiled into recognition models. It enables user to quickly test the performance of a new vocabulary.

  10. Emotion-independent face recognition

    Science.gov (United States)

    De Silva, Liyanage C.; Esther, Kho G. P.

    2000-12-01

    Current face recognition techniques tend to work well when recognizing faces under small variations in lighting, facial expression and pose, but deteriorate under more extreme conditions. In this paper, a face recognition system to recognize faces of known individuals, despite variations in facial expression due to different emotions, is developed. The eigenface approach is used for feature extraction. Classification methods include Euclidean distance, back propagation neural network and generalized regression neural network. These methods yield 100% recognition accuracy when the training database is representative, containing one image representing the peak expression for each emotion of each person apart from the neutral expression. The feature vectors used for comparison in the Euclidean distance method and for training the neural network must be all the feature vectors of the training set. These results are obtained for a face database consisting of only four persons.

  11. Individual Recognition in Ant Queens

    DEFF Research Database (Denmark)

    D'Ettorre, Patrizia; Heinze, Jürgen

    2005-01-01

    recognize each other's unique facial color patterns [3] . Individual recognition is advantageous when dominance hierarchies control the partitioning of work and reproduction 2 and 4 . Here, we show that unrelated founding queens of the ant Pachycondyla villosa use chemical cues to recognize each other......Personal relationships are the cornerstone of vertebrate societies, but insect societies are either too large for individual recognition, or their members were assumed to lack the necessary cognitive abilities 1 and 2 . This paradigm has been challenged by the recent discovery that paper wasps...... perception, was prevented and in tests with anaesthetized queens. The cuticular chemical profiles of queens were neither associated with dominance nor fertility and, therefore, do not represent status badges 5 and 6 , and nestmate queens did not share a common odor. Personal recognition facilitates...

  12. Text Recognition from an Image

    Directory of Open Access Journals (Sweden)

    Shrinath Janvalkar

    2014-04-01

    Full Text Available To achieve high speed in data processing it is necessary to convert the analog data into digital data. Storage of hard copy of any document occupies large space and retrieving of information from that document is time consuming. Optical character recognition system is an effective way in recognition of printed character. It provides an easy way to recognize and convert the printed text on image into the editable text. It also increases the speed of data retrieval from the image. The image which contains characters can be scanned through scanner and then recognition engine of the OCR system interpret the images and convert images of printed characters into machine-readable characters [8].It improving the interface between man and machine in many applications

  13. DNA recognition by synthetic constructs.

    Science.gov (United States)

    Pazos, Elena; Mosquera, Jesús; Vázquez, M Eugenio; Mascareñas, José L

    2011-09-05

    The interaction of transcription factors with specific DNA sites is key for the regulation of gene expression. Despite the availability of a large body of structural data on protein-DNA complexes, we are still far from fully understanding the molecular and biophysical bases underlying such interactions. Therefore, the development of non-natural agents that can reproduce the DNA-recognition properties of natural transcription factors remains a major and challenging goal in chemical biology. In this review we summarize the basics of double-stranded DNA recognition by transcription factors, and describe recent developments in the design and preparation of synthetic DNA binders. We mainly focus on synthetic peptides that have been designed by following the DNA interaction of natural proteins, and we discuss how the tools of organic synthesis can be used to make artificial constructs equipped with functionalities that introduce additional properties to the recognition process, such as sensing and controllability.

  14. Early development of visual recognition.

    Science.gov (United States)

    Plebe, Alessio; Domenella, Rosaria Grazia

    2006-01-01

    The most important ability of the human vision is object recognition, yet it is exactly the less understood aspect of the vision system. Computational models have been helpful in progressing towards an explanation of this obscure cognitive ability, and today it is possible to conceive more refined models, thanks to the new availability of neuroscientific data about the human visual cortex. This work proposes a model of the development of the object recognition capability, under a different perspective with respect to the most common approaches, with a precise theoretical epistemology. It is assumed that the main processing functions involved in recognition are not genetically determined and hardwired in the neural circuits, but are the result of interactions between epigenetic influences and the basic neural plasticity mechanisms. The model is organized in modules related with the main visual biological areas, and is implemented mainly using the LISSOM architecture, a recent self-organizing algorithm closely reflecting the essential behavior of cortical circuits.

  15. Gesture Recognition Using Character Recognition Techniques on Two-dimensional Eigenspace

    OpenAIRE

    大野, 宏; 山本, 正信; Ohno, Hiroshi; Yamamoto, Masanobu

    1999-01-01

    This paper describes a novel method for gesture recognition using character recognition techniques on two-dimensional eigenspace. An image-based approach can capture human body poses in 3D motion from multiple image sequences. The sequence of poses can be reduced into a trajectory on the two-dimensional eigenspace with preserving the main features in gesture, so that the gesture recognition equals the character recognition. Experiments for the gesture recognition using some character recognit...

  16. Familiar Person Recognition: Is Autonoetic Consciousness More Likely to Accompany Face Recognition Than Voice Recognition?

    Science.gov (United States)

    Barsics, Catherine; Brédart, Serge

    2010-11-01

    Autonoetic consciousness is a fundamental property of human memory, enabling us to experience mental time travel, to recollect past events with a feeling of self-involvement, and to project ourselves in the future. Autonoetic consciousness is a characteristic of episodic memory. By contrast, awareness of the past associated with a mere feeling of familiarity or knowing relies on noetic consciousness, depending on semantic memory integrity. Present research was aimed at evaluating whether conscious recollection of episodic memories is more likely to occur following the recognition of a familiar face than following the recognition of a familiar voice. Recall of semantic information (biographical information) was also assessed. Previous studies that investigated the recall of biographical information following person recognition used faces and voices of famous people as stimuli. In this study, the participants were presented with personally familiar people's voices and faces, thus avoiding the presence of identity cues in the spoken extracts and allowing a stricter control of frequency exposure with both types of stimuli (voices and faces). In the present study, the rate of retrieved episodic memories, associated with autonoetic awareness, was significantly higher from familiar faces than familiar voices even though the level of overall recognition was similar for both these stimuli domains. The same pattern was observed regarding semantic information retrieval. These results and their implications for current Interactive Activation and Competition person recognition models are discussed.

  17. Human ear recognition by computer

    CERN Document Server

    Bhanu, Bir; Chen, Hui

    2010-01-01

    Biometrics deals with recognition of individuals based on their physiological or behavioral characteristics. The human ear is a new feature in biometrics that has several merits over the more common face, fingerprint and iris biometrics. Unlike the fingerprint and iris, it can be easily captured from a distance without a fully cooperative subject, although sometimes it may be hidden with hair, scarf and jewellery. Also, unlike a face, the ear is a relatively stable structure that does not change much with the age and facial expressions. ""Human Ear Recognition by Computer"" is the first book o

  18. Acoustic modeling for emotion recognition

    CERN Document Server

    Anne, Koteswara Rao; Vankayalapati, Hima Deepthi

    2015-01-01

     This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications – gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared, with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques.

  19. Discriminative learning for speech recognition

    CERN Document Server

    He, Xiadong

    2008-01-01

    In this book, we introduce the background and mainstream methods of probabilistic modeling and discriminative parameter optimization for speech recognition. The specific models treated in depth include the widely used exponential-family distributions and the hidden Markov model. A detailed study is presented on unifying the common objective functions for discriminative learning in speech recognition, namely maximum mutual information (MMI), minimum classification error, and minimum phone/word error. The unification is presented, with rigorous mathematical analysis, in a common rational-functio

  20. Unequal recognition, misrecognition and injustice

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2012-01-01

    Euro-multiculturalism is (1) concerned with religiously defined immigrant minorities; (2) sees policies of recognition as a means to secure multicultural equality between groups; (3) endorses the moderate secularism of European states; and (4) adopts a contextualist approach to answering the norm......Euro-multiculturalism is (1) concerned with religiously defined immigrant minorities; (2) sees policies of recognition as a means to secure multicultural equality between groups; (3) endorses the moderate secularism of European states; and (4) adopts a contextualist approach to answering...... endorses moderate secularism and contextualism....

  1. Pattern Recognition Theory of Mind

    CERN Document Server

    de Paiva, Gilberto

    2009-01-01

    I propose that pattern recognition, memorization and processing are key concepts that can be a principle set for the theoretical modeling of the mind function. Most of the questions about the mind functioning can be answered by a descriptive modeling and definitions from these principles. An understandable consciousness definition can be drawn based on the assumption that a pattern recognition system can recognize its own patterns of activity. The principles, descriptive modeling and definitions can be a basis for theoretical and applied research on cognitive sciences, particularly at artificial intelligence studies.

  2. Traffic-Sign Recognition Systems

    CERN Document Server

    Escalera, Sergio

    2011-01-01

    This work presents a full generic approach to the detection and recognition of traffic signs. The approach is based on the latest computer vision methods for object detection, and on powerful methods for multiclass classification. The challenge was to robustly detect a set of different sign classes in real time, and to classify each detected sign into a large, extensible set of classes. To address this challenge, several state-of-the-art methods were developed that can be used for different recognition problems. Following an introduction to the problems of traffic sign detection and categoriza

  3. A Survey: Face Recognition Techniques

    Directory of Open Access Journals (Sweden)

    Muhammad Sharif

    2012-12-01

    Full Text Available In this study, the existing techniques of face recognition are to be encountered along with their pros and cons to conduct a brief survey. The most general methods include Eigenface (Eigenfeatures, Hidden Markov Model (HMM, geometric based and template matching approaches. This survey actually performs analysis on these approaches in order to constitute face representations which will be discussed as under. In the second phase of the survey, factors affecting the recognition rates and processes are also discussed along with the solutions provided by different authors.

  4. STUDY ON THE COAL-ROCK INTER-FACE RECOGNITION METHOD BASED ON MULTI-SENSOR DATA FUSION TECHNIQUE

    Institute of Scientific and Technical Information of China (English)

    Ren Fang; Yang Zhaojian; Xiong Shibo

    2003-01-01

    The coal-rock interface recognition method based on multi-sensor data fusion technique is put forward because of the localization of single type sensor recognition method. The measuring theory based on multi-sensor data fusion technique is analyzed, and hereby the test platform of recognition system is manufactured. The advantage of data fusion with the fuzzy neural network (FNN) technique has been probed. The two-level FNN is constructed and data fusion is carried out. The experiments show that in various conditions the method can always acquire a much higher recognition rate than normal ones.

  5. Pattern Recognition Based Detection Recognition of Traffic Sign Using SVM

    Directory of Open Access Journals (Sweden)

    S. Sathiya

    2014-05-01

    Full Text Available The objective of this work describes a method for Traffic sign detection and recognition from the traffic panel board(signage. It detect the traffic signs especially for Indian conditions. Images are acquired through the camera and it is invariant to size then it is scaled. It consist of the following steps, first, it detect the traffic sign, if it has sufficient contrast from the background then we use sobel edge detection technique and morphological dilation. Second, extract the detected traffic sign from the board using row count and column count. Third, to extract the feature using DCT, DWT and Hybrid DWT-DCT. In training phase, DCT 20 highest energy coefficients are extracted, In DWT 300 features extracted from each traffic sign and in Hybrid DWT-DCT 20 features are extracted. Finally recognition are performed through SVM. The application is to improve the efficiency of transportation networks through applications of communication visually impaired person wear the camera to identify the traffic destination board. Experimental results show that state-of-the-art algorithms obtains highly competitive performance and is especially efficient to different levels of corruptions. The performance of Traffic Sign recognition is evaluated for Traffic Sign board image and the system achieves a recognition rate of 86% using DCT, 90% using DWT and 96% using Hybrid DWT-DCT and SVM.

  6. Idiopathic Normal Pressure Hydrocephalus

    Directory of Open Access Journals (Sweden)

    Basant R. Nassar BS

    2016-04-01

    Full Text Available Idiopathic normal pressure hydrocephalus (iNPH is a potentially reversible neurodegenerative disease commonly characterized by a triad of dementia, gait, and urinary disturbance. Advancements in diagnosis and treatment have aided in properly identifying and improving symptoms in patients. However, a large proportion of iNPH patients remain either undiagnosed or misdiagnosed. Using PubMed search engine of keywords “normal pressure hydrocephalus,” “diagnosis,” “shunt treatment,” “biomarkers,” “gait disturbances,” “cognitive function,” “neuropsychology,” “imaging,” and “pathogenesis,” articles were obtained for this review. The majority of the articles were retrieved from the past 10 years. The purpose of this review article is to aid general practitioners in further understanding current findings on the pathogenesis, diagnosis, and treatment of iNPH.

  7. Idiopathic Normal Pressure Hydrocephalus

    Directory of Open Access Journals (Sweden)

    Basant R. Nassar BS

    2016-04-01

    Full Text Available Idiopathic normal pressure hydrocephalus (iNPH is a potentially reversible neurodegenerative disease commonly characterized by a triad of dementia, gait, and urinary disturbance. Advancements in diagnosis and treatment have aided in properly identifying and improving symptoms in patients. However, a large proportion of iNPH patients remain either undiagnosed or misdiagnosed. Using PubMed search engine of keywords “normal pressure hydrocephalus,” “diagnosis,” “shunt treatment,” “biomarkers,” “gait disturbances,” “cognitive function,” “neuropsychology,” “imaging,” and “pathogenesis,” articles were obtained for this review. The majority of the articles were retrieved from the past 10 years. The purpose of this review article is to aid general practitioners in further understanding current findings on the pathogenesis, diagnosis, and treatment of iNPH.

  8. Monitoring the normal body

    DEFF Research Database (Denmark)

    Nissen, Nina Konstantin; Holm, Lotte; Baarts, Charlotte

    2015-01-01

    Introduction : An extensive body of literature is concerned with obese people, risk, and weight management. However, little is known about weight management among people not belonging to the extreme BMI categories. Management of weight among normal-weight and moderately overweight individuals...... provides us with knowledge about how to prevent future overweight or obesity. This paper investigates body size ideals and monitoring practices among normal-weight and moderately overweight people. Methods : The study is based on in-depth interviews combined with observations. 24 participants were...... of practices for monitoring their bodies based on different kinds of calculations of weight and body size, observations of body shape, and measurements of bodily firmness. Biometric measurements are familiar to them as are health authorities' recommendations. Despite not belonging to an extreme BMI category...

  9. Normal Order: Combinatorial Graphs

    CERN Document Server

    Solomon, A I; Blasiak, P; Horzela, A; Penson, K A; Solomon, Allan I.; Duchamp, Gerard; Blasiak, Pawel; Horzela, Andrzej; Penson, Karol A.

    2004-01-01

    A conventional context for supersymmetric problems arises when we consider systems containing both boson and fermion operators. In this note we consider the normal ordering problem for a string of such operators. In the general case, upon which we touch briefly, this problem leads to combinatorial numbers, the so-called Rook numbers. Since we assume that the two species, bosons and fermions, commute, we subsequently restrict ourselves to consideration of a single species, single-mode boson monomials. This problem leads to elegant generalisations of well-known combinatorial numbers, specifically Bell and Stirling numbers. We explicitly give the generating functions for some classes of these numbers. In this note we concentrate on the combinatorial graph approach, showing how some important classical results of graph theory lead to transparent representations of the combinatorial numbers associated with the boson normal ordering problem.

  10. Normality concerning shared values

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Let F be a family of meromorphic functions in a plane domain D, and a and b be finite non-zero complex values such that a/b ∈ N \\ {1}. If for every f ∈ F, f(z) = a =■ f (z) = a and f (z) = b =■ f (z) = b, then F is normal. We also construct a non-normal family F of meromorphic functions in the unit disk Δ = {|z| < 1} such that for every f ∈ F, f(z) = m + 1  f (z) = m + 1 and f (z) = 1  f (z) = 1 in Δ, where m is a given positive integer. This answers Problem 5.1 in the works of Gu, Pang and Fang.

  11. Normality concerning shared values

    Institute of Scientific and Technical Information of China (English)

    CHANG JianMing

    2009-01-01

    Let F be a family of meromorphic functions in a plane domain D,and a and b be finite non-zero complex values such that a/b ∈ N \\ {1}.If for every f ∈ F,f(z)=a=>(z) = a and f'(z)=b=>f"(z)=b,then F is normal.We also construct a non-normal family F of meromorphic functions in the unit disk △= {|z|<1} such that for every f ∈F,f(z) =m+1f'(z) = m+1and f'(z)=1 f"(z) = 1 in △ A,where m is a given positive integer.This answers Problem 5.1 in the works of Gu,Pang and Fang.

  12. Pattern recognition in speech and language processing

    CERN Document Server

    Chou, Wu

    2003-01-01

    Minimum Classification Error (MSE) Approach in Pattern Recognition, Wu ChouMinimum Bayes-Risk Methods in Automatic Speech Recognition, Vaibhava Goel and William ByrneA Decision Theoretic Formulation for Adaptive and Robust Automatic Speech Recognition, Qiang HuoSpeech Pattern Recognition Using Neural Networks, Shigeru KatagiriLarge Vocabulary Speech Recognition Based on Statistical Methods, Jean-Luc GauvainToward Spontaneous Speech Recognition and Understanding, Sadaoki FuruiSpeaker Authentication, Qi Li and Biing-Hwang JuangHMMs for Language Processing Problems, Ri

  13. An objective auditory measure to assess speech recognition in adult cochlear implant users.

    Science.gov (United States)

    Turgeon, C; Lazzouni, L; Lepore, F; Ellemberg, D

    2014-04-01

    To verify if a mismatch negativity (MMN) paradigm based on speech syllables can differentiate between good and poorer cochlear implant (CI) users on a speech recognition task. Twenty adults with a CI and 11 normal hearing adults participated in the study. Based on a speech recognition test, ten CI users were classified as good performers and ten as poor performers. We measured the MMN with /da/ as the standard stimulus and /ba/ and /ga/ as the deviants. Separate analyses were conducted on the amplitude and latency of the MMN. A MMN was evoked by both deviant stimuli in all normal hearing participants and in well performing CI users, with similar amplitudes for both groups. However, the amplitude of the MMN was significantly reduced for the poorer CI users compared to the normal hearing group and the good CI users. The latency was longer for both groups of cochlear implant users. A bivariate correlation showed a significant positive correlation between the speech recognition score and the amplitude of the MMN. The MMN can distinguish between CI users who have good versus poor speech recognition as assessed with conventional tasks. Our findings suggest that the MMN can be use to assess speech recognition proficiency in CI users who cannot be tested with regular speech recognition tasks, like infants and other non-verbal populations. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  14. Classification of signals by using normal orthogonal transformation

    Directory of Open Access Journals (Sweden)

    Y. Kh. Nizhebetska

    2011-12-01

    Full Text Available Possibility of pattern recognition is considered on the procedure of creation of discrete ortogonal transformation offered by an author, in that the first transform coincides with a etalon signal. At the coincidence of the investigated signal with a test the spectrum of such transformation contains one unzero transform only, while appearance of other transforms in a spectrum testifies to their differences. Application of normal transformation for the estimation of similarity of signals by coefficients of transforms allows to enter numeral measure of estimation of such similarity. Procedure of recognition is widespread on the cases of two-dimensional and complex signals. Results over of the use of normal transformation are brought for the tasks of authentification of person by the dinamically entered signature and classification of the state of person by the pulse wave.

  15. Face recognition, a landmarks tale

    NARCIS (Netherlands)

    Beumer, Gerrit Maarten

    2009-01-01

    Face recognition is a technology that appeals to the imagination of many people. This is particularly reflected in the popularity of science-fiction films and forensic detective series such as CSI, CSI New York, CSI Miami, Bones and NCIS. Although these series tend to be set in the present, their a

  16. Non-Intrusive Appliance Recognition

    NARCIS (Netherlands)

    Hoogsteen, G; Hoogsteen, Gerwin; Krist, J.O.; Bakker, Vincent; Smit, Gerardus Johannes Maria

    2012-01-01

    Energy conservation becomes more important nowadays. The use of smart meters and, in the near future, smart appliances, are the key to achieve reduction in energy consumption. This research proposes a non-intrusive appliance monitor and recognition system for implementation on an embedded system. Th

  17. Age-invariant face recognition.

    Science.gov (United States)

    Park, Unsang; Tong, Yiying; Jain, Anil K

    2010-05-01

    One of the challenges in automatic face recognition is to achieve temporal invariance. In other words, the goal is to come up with a representation and matching scheme that is robust to changes due to facial aging. Facial aging is a complex process that affects both the 3D shape of the face and its texture (e.g., wrinkles). These shape and texture changes degrade the performance of automatic face recognition systems. However, facial aging has not received substantial attention compared to other facial variations due to pose, lighting, and expression. We propose a 3D aging modeling technique and show how it can be used to compensate for the age variations to improve the face recognition performance. The aging modeling technique adapts view-invariant 3D face models to the given 2D face aging database. The proposed approach is evaluated on three different databases (i.g., FG-NET, MORPH, and BROWNS) using FaceVACS, a state-of-the-art commercial face recognition engine.

  18. Phosphate Recognition in Structural Biology

    NARCIS (Netherlands)

    Hirsch, Anna K.H.; Fischer, Felix R.; Diederich, François

    2007-01-01

    Drug-discovery research in the past decade has seen an increased selection of targets with phosphate recognition sites, such as protein kinases and phosphatases, in the past decade. This review attempts, with the help of database-mining tools, to give an overview of the most important principles in

  19. License plate recognition using DTCNNs

    NARCIS (Netherlands)

    ter Brugge, M.H; Stevens, J.H; Nijhuis, J.A G; Spaanenburg, L; Tavsanonoglu, V

    1998-01-01

    Automatic license plate recognition requires a series of complex image processing steps. For practical use, the amount of data to he processed must be minimized early on. This paper shows that the computationally most intensive steps can be realized by DTCNNs. Moreover; high-level operations like fi

  20. Face recognition, a landmarks tale

    NARCIS (Netherlands)

    Beumer, G.M.

    2009-01-01

    Face recognition is a technology that appeals to the imagination of many people. This is particularly reflected in the popularity of science-fiction films and forensic detective series such as CSI, CSI New York, CSI Miami, Bones and NCIS. Although these series tend to be set in the present, their ap

  1. Simultaneous tracking and activity recognition

    DEFF Research Database (Denmark)

    Manfredotti, Cristina Elena; Fleet, David J.; Hamilton, Howard J.

    2011-01-01

    Many tracking problems involve several distinct objects interacting with each other. We develop a framework that takes into account interactions between objects allowing the recognition of complex activities. In contrast to classic approaches that consider distinct phases of tracking and activity...

  2. Towards automatic forensic face recognition

    NARCIS (Netherlands)

    Ali, Tauseef; Spreeuwers, Luuk; Veldhuis, Raymond

    2011-01-01

    In this paper we present a methodology and experimental results for evidence evaluation in the context of forensic face recognition. In forensic applications, the matching score (hereafter referred to as similarity score) from a biometric system must be represented as a Likelihood Ratio (LR). In our

  3. Target recognition by wavelet transform

    CERN Document Server

    Li Zheng Dong; He Wu Liang; Pei Chun Lan; Peng Wen; SongChen; Zheng Xiao Dong

    2002-01-01

    Wavelet transform has an important character of multi-resolution power, which presents pyramid structure, and this character coincides the way by which people distinguish object from coarse to fineness and from large to tiny. In addition to it, wavelet transform benefits to reducing image noise, simplifying calculation, and embodying target image characteristic point. A method of target recognition by wavelet transform is provided

  4. Neural mechanisms for voice recognition

    NARCIS (Netherlands)

    Andics, A.V.; McQueen, J.M.; Petersson, K.M.; Gal, V.; Rudas, G.; Vidnyanszky, Z.

    2010-01-01

    We investigated neural mechanisms that support voice recognition in a training paradigm with fMRI. The same listeners were trained on different weeks to categorize the mid-regions of voice-morph continua as an individual's voice. Stimuli implicitly defined a voice-acoustics space, and training expli

  5. Data complexity in pattern recognition

    CERN Document Server

    Kam Ho Tin

    2006-01-01

    Machines capable of automatic pattern recognition have many fascinating uses. Algorithms for supervised classification, where one infers a decision boundary from a set of training examples, are at the core of this capability. This book looks at data complexity and its role in shaping the theories and techniques in different disciplines

  6. Computer Recognition of Facial Profiles

    Science.gov (United States)

    1974-08-01

    z30 o u u cr W, 137 REFERENCES 1. Fischer , C. L., Pollock, D. K., Raddack, B., and Stevens, M. E., Optical Character Recognition, Spartan Books...K. W., and Haworth , P. A., "Automatic Shape betectinn for Programmed Terrain Classifica-’ tion," Proc. Soc. Photographic Instrumentation Engrs

  7. Output Interference in Recognition Memory

    Science.gov (United States)

    Criss, Amy H.; Malmberg, Kenneth J.; Shiffrin, Richard M.

    2011-01-01

    Dennis and Humphreys (2001) proposed that interference in recognition memory arises solely from the prior contexts of the test word: Interference does not arise from memory traces of other words (from events prior to the study list or on the study list, and regardless of similarity to the test item). We evaluate this model using output…

  8. Mobile Visual Recognition on Smartphones

    Directory of Open Access Journals (Sweden)

    Zhenwen Gui

    2013-01-01

    Full Text Available This paper addresses the recognition of large-scale outdoor scenes on smartphones by fusing outputs of inertial sensors and computer vision techniques. The main contributions can be summarized as follows. Firstly, we propose an ORD (overlap region divide method to plot image position area, which is fast enough to find the nearest visiting area and can also reduce the search range compared with the traditional approaches. Secondly, the vocabulary tree-based approach is improved by introducing GAGCC (gravity-aligned geometric consistency constraint. Our method involves no operation in the high-dimensional feature space and does not assume a global transform between a pair of images. Thus, it substantially reduces the computational complexity and memory usage, which makes the city scale image recognition feasible on the smartphone. Experiments on a collected database including 0.16 million images show that the proposed method demonstrates excellent recognition performance, while maintaining the average recognition time about 1 s.

  9. Normal and Time-Compressed Speech

    Science.gov (United States)

    Lemke, Ulrike; Kollmeier, Birger; Holube, Inga

    2016-01-01

    Short-term and long-term learning effects were investigated for the German Oldenburg sentence test (OLSA) using original and time-compressed fast speech in noise. Normal-hearing and hearing-impaired participants completed six lists of the OLSA in five sessions. Two groups of normal-hearing listeners (24 and 12 listeners) and two groups of hearing-impaired listeners (9 listeners each) performed the test with original or time-compressed speech. In general, original speech resulted in better speech recognition thresholds than time-compressed speech. Thresholds decreased with repetition for both speech materials. Confirming earlier results, the largest improvements were observed within the first measurements of the first session, indicating a rapid initial adaptation phase. The improvements were larger for time-compressed than for original speech. The novel results on long-term learning effects when using the OLSA indicate a longer phase of ongoing learning, especially for time-compressed speech, which seems to be limited by a floor effect. In addition, for normal-hearing participants, no complete transfer of learning benefits from time-compressed to original speech was observed. These effects should be borne in mind when inviting listeners repeatedly, for example, in research settings.

  10. Timbre perception and object separation with normal and impaired hearing

    OpenAIRE

    Emiroglu, Suzan Selma

    2007-01-01

    Timbre is a combination of all auditory object attributes other than pitch, loudness and duration. A timbre distortion caused by a sensorineural hearing loss not only affects music perception, but may also influence object recognition in general. In order to quantify differences in object segregation and timbre discrimination between normal-hearing and hearing-impaired listeners with a sensorineural hearing loss, a new method for studying timbre perception was developed, which uses cross-fade...

  11. Improving the dictionary lookup approach for disease normalization using enhanced dictionary and query expansion.

    Science.gov (United States)

    Jonnagaddala, Jitendra; Jue, Toni Rose; Chang, Nai-Wen; Dai, Hong-Jie

    2016-01-01

    The rapidly increasing biomedical literature calls for the need of an automatic approach in the recognition and normalization of disease mentions in order to increase the precision and effectivity of disease based information retrieval. A variety of methods have been proposed to deal with the problem of disease named entity recognition and normalization. Among all the proposed methods, conditional random fields (CRFs) and dictionary lookup method are widely used for named entity recognition and normalization respectively. We herein developed a CRF-based model to allow automated recognition of disease mentions, and studied the effect of various techniques in improving the normalization results based on the dictionary lookup approach. The dataset from the BioCreative V CDR track was used to report the performance of the developed normalization methods and compare with other existing dictionary lookup based normalization methods. The best configuration achieved an F-measure of 0.77 for the disease normalization, which outperformed the best dictionary lookup based baseline method studied in this work by an F-measure of 0.13.Database URL: https://github.com/TCRNBioinformatics/DiseaseExtract.

  12. Improving the dictionary lookup approach for disease normalization using enhanced dictionary and query expansion

    Science.gov (United States)

    Jonnagaddala, Jitendra; Jue, Toni Rose; Chang, Nai-Wen; Dai, Hong-Jie

    2016-01-01

    The rapidly increasing biomedical literature calls for the need of an automatic approach in the recognition and normalization of disease mentions in order to increase the precision and effectivity of disease based information retrieval. A variety of methods have been proposed to deal with the problem of disease named entity recognition and normalization. Among all the proposed methods, conditional random fields (CRFs) and dictionary lookup method are widely used for named entity recognition and normalization respectively. We herein developed a CRF-based model to allow automated recognition of disease mentions, and studied the effect of various techniques in improving the normalization results based on the dictionary lookup approach. The dataset from the BioCreative V CDR track was used to report the performance of the developed normalization methods and compare with other existing dictionary lookup based normalization methods. The best configuration achieved an F-measure of 0.77 for the disease normalization, which outperformed the best dictionary lookup based baseline method studied in this work by an F-measure of 0.13. Database URL: https://github.com/TCRNBioinformatics/DiseaseExtract PMID:27504009

  13. Object recognition memory in zebrafish.

    Science.gov (United States)

    May, Zacnicte; Morrill, Adam; Holcombe, Adam; Johnston, Travis; Gallup, Joshua; Fouad, Karim; Schalomon, Melike; Hamilton, Trevor James

    2016-01-01

    The novel object recognition, or novel-object preference (NOP) test is employed to assess recognition memory in a variety of organisms. The subject is exposed to two identical objects, then after a delay, it is placed back in the original environment containing one of the original objects and a novel object. If the subject spends more time exploring one object, this can be interpreted as memory retention. To date, this test has not been fully explored in zebrafish (Danio rerio). Zebrafish possess recognition memory for simple 2- and 3-dimensional geometrical shapes, yet it is unknown if this translates to complex 3-dimensional objects. In this study we evaluated recognition memory in zebrafish using complex objects of different sizes. Contrary to rodents, zebrafish preferentially explored familiar over novel objects. Familiarity preference disappeared after delays of 5 mins. Leopard danios, another strain of D. rerio, also preferred the familiar object after a 1 min delay. Object preference could be re-established in zebra danios by administration of nicotine tartrate salt (50mg/L) prior to stimuli presentation, suggesting a memory-enhancing effect of nicotine. Additionally, exploration biases were present only when the objects were of intermediate size (2 × 5 cm). Our results demonstrate zebra and leopard danios have recognition memory, and that low nicotine doses can improve this memory type in zebra danios. However, exploration biases, from which memory is inferred, depend on object size. These findings suggest zebrafish ecology might influence object preference, as zebrafish neophobia could reflect natural anti-predatory behaviour.

  14. Face Recognition by Metropolitan Police Super-Recognisers.

    Science.gov (United States)

    Robertson, David J; Noyes, Eilidh; Dowsett, Andrew J; Jenkins, Rob; Burton, A Mike

    2016-01-01

    Face recognition is used to prove identity across a wide variety of settings. Despite this, research consistently shows that people are typically rather poor at matching faces to photos. Some professional groups, such as police and passport officers, have been shown to perform just as poorly as the general public on standard tests of face recognition. However, face recognition skills are subject to wide individual variation, with some people showing exceptional ability-a group that has come to be known as 'super-recognisers'. The Metropolitan Police Force (London) recruits 'super-recognisers' from within its ranks, for deployment on various identification tasks. Here we test four working super-recognisers from within this police force, and ask whether they are really able to perform at levels above control groups. We consistently find that the police 'super-recognisers' perform at well above normal levels on tests of unfamiliar and familiar face matching, with degraded as well as high quality images. Recruiting employees with high levels of skill in these areas, and allocating them to relevant tasks, is an efficient way to overcome some of the known difficulties associated with unfamiliar face recognition.

  15. Face Recognition by Metropolitan Police Super-Recognisers.

    Directory of Open Access Journals (Sweden)

    David J Robertson

    Full Text Available Face recognition is used to prove identity across a wide variety of settings. Despite this, research consistently shows that people are typically rather poor at matching faces to photos. Some professional groups, such as police and passport officers, have been shown to perform just as poorly as the general public on standard tests of face recognition. However, face recognition skills are subject to wide individual variation, with some people showing exceptional ability-a group that has come to be known as 'super-recognisers'. The Metropolitan Police Force (London recruits 'super-recognisers' from within its ranks, for deployment on various identification tasks. Here we test four working super-recognisers from within this police force, and ask whether they are really able to perform at levels above control groups. We consistently find that the police 'super-recognisers' perform at well above normal levels on tests of unfamiliar and familiar face matching, with degraded as well as high quality images. Recruiting employees with high levels of skill in these areas, and allocating them to relevant tasks, is an efficient way to overcome some of the known difficulties associated with unfamiliar face recognition.

  16. Effects of speech clarity on recognition memory for spoken sentences.

    Science.gov (United States)

    Van Engen, Kristin J; Chandrasekaran, Bharath; Smiljanic, Rajka

    2012-01-01

    Extensive research shows that inter-talker variability (i.e., changing the talker) affects recognition memory for speech signals. However, relatively little is known about the consequences of intra-talker variability (i.e. changes in speaking style within a talker) on the encoding of speech signals in memory. It is well established that speakers can modulate the characteristics of their own speech and produce a listener-oriented, intelligibility-enhancing speaking style in response to communication demands (e.g., when speaking to listeners with hearing impairment or non-native speakers of the language). Here we conducted two experiments to examine the role of speaking style variation in spoken language processing. First, we examined the extent to which clear speech provided benefits in challenging listening environments (i.e. speech-in-noise). Second, we compared recognition memory for sentences produced in conversational and clear speaking styles. In both experiments, semantically normal and anomalous sentences were included to investigate the role of higher-level linguistic information in the processing of speaking style variability. The results show that acoustic-phonetic modifications implemented in listener-oriented speech lead to improved speech recognition in challenging listening conditions and, crucially, to a substantial enhancement in recognition memory for sentences.

  17. Method and System for Object Recognition Search

    Science.gov (United States)

    Duong, Tuan A. (Inventor); Duong, Vu A. (Inventor); Stubberud, Allen R. (Inventor)

    2012-01-01

    A method for object recognition using shape and color features of the object to be recognized. An adaptive architecture is used to recognize and adapt the shape and color features for moving objects to enable object recognition.

  18. Speech Recognition: Its Place in Business Education.

    Science.gov (United States)

    Szul, Linda F.; Bouder, Michele

    2003-01-01

    Suggests uses of speech recognition devices in the classroom for students with disabilities. Compares speech recognition software packages and provides guidelines for selection and teaching. (Contains 14 references.) (SK)

  19. Urban building recognition during significant temporal variations

    DEFF Research Database (Denmark)

    Nguyen, Phuong Giang; Andersen, Hans Jørgen

    2008-01-01

    In literature, existing researches on building recognition mainly concentrate on scales, rotations, and viewpoints variance. In urban environment, large temporal variations of weather and lighting conditions should also be considered as major challenges for robust recognition. For instances...

  20. Ultrasonography of histologically normal parathyroid glands and thyroid lobules in normocalcemic dogs.

    Science.gov (United States)

    Liles, Sofija R; Linder, Keith E; Cain, Brandon; Pease, Anthony P

    2010-01-01

    The purpose of this study is to characterize the sonographic appearance of canine parathyroid glands using high-resolution ultrasonography. Ten cadaver dogs were studied after euthanasia for reasons not relating to the parathyroid. The cervical region was examined using a 13-5 MHz linear transducer in right and left recumbency. Ultrasonographic features of the parathyroid and thyroid glands were compared with the gross and histopathologic findings. Thirty-five structures were identified sonographically as parathyroid glands but only 26 of 35 glands (74% positive predictive value) were proven to be normal parathyroid glands histopathologically. Of the nine false positives, five (14%) were proven to be lobular thyroid tissue. The remaining four (11%) structures were visible grossly or found histopathologically. There were no statistical differences between ultrasonographic and gross measurements of the parathyroid glands. The average size as seen sonographically was 3.3 x 2.2 x 1.7 mm and the average gross size was 3.7 x 2.6 x 1.6 mm (length, width, height). The average size of the thyroid lobules assessed sonographically was 2.3 x1.6 x 0.8 mm (length, width, height). Normal parathyroid glands can be identified using high-resolution ultrasonography. But some thyroid lobules will be misinterpreted as parathyroid glands; this will result in false positives when identifying parathyroid glands with ultrasonography.

  1. Identification, recognition and misidentification syndromes. A psychoanalytical perspective.

    Directory of Open Access Journals (Sweden)

    Stéphane eThibierge

    2013-11-01

    Full Text Available Misidentification syndromes are currently often understood as cognitive disorders of either the sense of uniqueness (Margariti & Kontaxakis, 2006 or the recognition of people (Ellis, Lewis, 2001. It is however necessary to consider how a normal sense of uniqueness or a normal people recognition are acquired by normal or neurotic subjects. It will be shown here that the normal conditions of cognition can be considered as one of the possible forms of a complex structure and not as just a setting for our sense and perception data. The consistency and the permanency of the body image in neurosis is what permits that we recognize other people and ourselves as unique beings. These consistency and permanency are related to object repression, as shown by neurological disorders of body image (somatoparaphrenia, which cause the object to come to the foreground in the patient’s words (Thibierge and Morin, 2010. In misidentification syndromes, as in other psychotic syndromes, one can also observe a damage of the specular image as well as an absence of object repression. This leads us to question whether, in the psychiatric disorders related to a damaged specular image, cognition disorders can be studied and managed using the same methods as for neurotic patients.

  2. Age Dependent Face Recognition using Eigenface

    OpenAIRE

    Hlaing Htake Khaung Tin

    2013-01-01

    Face recognition is the most successful form of human surveillance. Face recognition technology, is being used to improve human efficiency when recognition faces, is one of the fastest growing fields in the biometric industry. In the first stage, the age is classified into eleven categories which distinguish the person oldness in terms of age. In the second stage of the process is face recognition based on the predicted age. Age prediction has considerable potential applications in human comp...

  3. Employee recognition and performance: A field experiment

    OpenAIRE

    Bradler, C.; Dur, R.; Neckermann, S.; Non, J.A.

    2013-01-01

    This paper reports the results from a controlled field experiment designed to investigate the causal effect of public recognition on employee performance. We hired more than 300 employees to work on a three-hour data-entry task. In a random sample of work groups, workers unexpectedly received recognition after two hours of work. We find that recognition increases subsequent performance substantially, and particularly so when recognition is exclusively provided to the best performers. Remarkab...

  4. Recognition of an Independent Self-Consciousness

    DEFF Research Database (Denmark)

    Bjerre, Henrik Jøker

    2009-01-01

    Hegel's concept in the Phenomenology of the Spirit of the "recognition of an independent self-consciousness" is investigated as a point of separation for contemporary philosophy of recognition. I claim that multiculturalism and the theories of recognition (such as Axel Honneth's) based on empirical...... psychology neglect or deny crucial metaphysical aspects of the Hegelian legacy. Instead, I seek to point at an additional, "spiritual", level of recognition, based on the concept of the subject in Lacanian psychoanalysis....

  5. Hand Gesture Recognition: A Literature Review

    OpenAIRE

    Rafiqul Zaman Khan; Noor Adnan Ibraheem

    2012-01-01

    Hand gesture recognition system received great attention in the recent few years because of its manifoldness applications and the ability to interact with machine efficiently through human computer interaction. In this paper a survey of recent hand gesture recognition systems is presented. Key issues of hand gesture recognition system are presented with challenges of gesture system. Review methods of recent postures and gestures recognition system presented as well. Summary of res...

  6. Exemplar Based Recognition of Visual Shapes

    DEFF Research Database (Denmark)

    Olsen, Søren I.

    2005-01-01

    This paper presents an approach of visual shape recognition based on exemplars of attributed keypoints. Training is performed by storing exemplars of keypoints detected in labeled training images. Recognition is made by keypoint matching and voting according to the labels for the matched keypoints....... The matching is insensitive to rotations, limited scalings and small deformations. The recognition is robust to noise, background clutter and partial occlusion. Recognition is possible from few training images and improve with the number of training images....

  7. Data structures, computer graphics, and pattern recognition

    CERN Document Server

    Klinger, A; Kunii, T L

    1977-01-01

    Data Structures, Computer Graphics, and Pattern Recognition focuses on the computer graphics and pattern recognition applications of data structures methodology.This book presents design related principles and research aspects of the computer graphics, system design, data management, and pattern recognition tasks. The topics include the data structure design, concise structuring of geometric data for computer aided design, and data structures for pattern recognition algorithms. The survey of data structures for computer graphics systems, application of relational data structures in computer gr

  8. Computing negentropy based signatures for texture recognition

    Directory of Open Access Journals (Sweden)

    Daniela COLTUC

    2007-12-01

    Full Text Available The proposed method aims to provide a new tool for texture recognition. For this purpose, a set of texture samples are decomposed by using the FastICA algorithm and characterized by a negentropy based signature. In order to do recognition, the texture signatures are compared by means of Minkowski distance. The recognition rates, computed for a set of 320 texture samples, show a medium recognition accuracy and the method may be further improved.

  9. Pattern recognition, machine intelligence and biometrics

    CERN Document Server

    Wang, Patrick S P

    2012-01-01

    ""Pattern Recognition, Machine Intelligence and Biometrics"" covers the most recent developments in Pattern Recognition and its applications, using artificial intelligence technologies within an increasingly critical field. It covers topics such as: image analysis and fingerprint recognition; facial expressions and emotions; handwriting and signatures; iris recognition; hand-palm gestures; and multimodal based research. The applications span many fields, from engineering, scientific studies and experiments, to biomedical and diagnostic applications, to personal identification and homeland secu

  10. Recognition of an Independent Self-Consciousness

    DEFF Research Database (Denmark)

    Bjerre, Henrik Jøker

    2009-01-01

    Hegel's concept in the Phenomenology of the Spirit of the "recognition of an independent self-consciousness" is investigated as a point of separation for contemporary philosophy of recognition. I claim that multiculturalism and the theories of recognition (such as Axel Honneth's) based on empiric...... psychology neglect or deny crucial metaphysical aspects of the Hegelian legacy. Instead, I seek to point at an additional, "spiritual", level of recognition, based on the concept of the subject in Lacanian psychoanalysis....

  11. MODIFIED VIEW BASED APPROACHES FOR HANDWRITTEN TAMIL CHARACTER RECOGNITION

    Directory of Open Access Journals (Sweden)

    S. Sobhana Mari

    2015-08-01

    Full Text Available Finding simple and efficient features for offline hand written character recognition is still an active area of research. In this work, we propose modified view based feature extraction approaches for the recognition of handwritten Tamil characters. In the first approach, the five views of a normalized and binarized character image viz, top, bottom, left, right and front are extracted. Each view is then divided into 16 equal zones and the total numbers of background pixel in each zone are counted. The 80 values so obtained form a feature vector. In the second approach, the normalized and binaraized character images are divided into 16 equal zones. Five views are extracted from each zone and the total number of background pixel in each view is counted, resulting in 80 feature values. Further the above two approaches are modified by employing thinned images instead of the whole image. The extracted features are classified using SVM, MLP and ELM classifier. The discriminative powers of the proposed approaches are compared with that of four popular feature extraction approaches in character recognition. The feature extraction time and classification performances are also compared. The proposed modified approaches results in high classification performance (95.26% with comparatively less feature extraction time.

  12. Recognition of Active Faults and Stress Field

    Science.gov (United States)

    Azuma, T.

    2012-12-01

    Around the plate-boundary region, the directions of maximum and minimum stress related to the plate motion is one of the key for the recognition of active faults. For example, it is typical idea that there are many N-S trading reverse faults, NE-SW and NW-SE trending strike slip faults and less normal faults (only near volcanoes) in Japan, where the compressional stress with E-W direction is dominant caused by the motion of the subduction of the Pacific Plate beneath the North American Plate. After the 2011 Tohoku earthquake (Mj 9.0), however, many earthquakes with the mechanism of the normal fault type occurred in the coastal region of the northern-east Japan. On 11th April 2011, the Fukushima Hamadori Earthquake (Mj 7.0) occurred accompanying surface faults along two faults, the Idosawa fault and the Yunotake fault, that recognized as active faults by the Research Group for Active Fault of Japan (1980, 1991). It impacted on active fault study by the reason of not only the appearance of two traces of significant surface faults with maximum displacement up to 2.1 m, but also the reactivation of the normal faults under the E-W compressional stress field. When we identify the active faults, it is one of the key whether the direction of slip on the fault consists with the stress field in that area or not. And there is a technique to recognized whether the fault is active or not by using the data of the direction of stress in the field and the geometry of the fault plane. Though it is useful for the fault in the rock without overlain Quaternary deposits, we should care that the active faults may react caused by the temporal stress condition after the generation of large earthquakes.

  13. Alteration of pain recognition in schizophrenia.

    Science.gov (United States)

    Wojakiewicz, A; Januel, D; Braha, S; Prkachin, K; Danziger, N; Bouhassira, D

    2013-10-01

    Schizophrenia patients display impaired recognition of their own emotions and those of others and deficits in several domains of empathy. The first-person experience of pain and observing others in pain normally trigger strong emotional mechanisms. We therefore hypothesized that schizophrenia patients would display impaired recognition and categorization of both their own pain and the pain of others. We studied 29 patients (18 men/11 women; 36 ± 13 years old) with paranoid schizophrenia-spectrum disorder and 27 healthy volunteers (20 men/7 women; 31 ± 9 years old) matched for age, gender, IQ and socio-cultural level. We assessed symptom severity and theory of mind. The participants' ability to detect and categorize pain in others was assessed with the sensitivity to expressions of pain (STEP) test, which is based on facial expressions, and another dynamic test involving a series of video sequences showing various pain-inducing events. The ability of patients to evaluate their own pain was assessed with the situational pain questionnaire (SPQ), which includes a series of questions assessing how one would expect to feel in different imaginary situations. Empathic tendencies were assessed with the interpersonal reactivity index. Patients and controls differed significantly in STEP, pain video and SPQ scores. By contrast with control subjects, the patients' pain judgements were not correlated with their affective or cognitive empathic capacities. Schizophrenic patients have a deficit of the identification and categorization of pain both in themselves and in others. © 2013 European Federation of International Association for the Study of Pain Chapters.

  14. Neurobiological mechanisms associated with facial affect recognition deficits after traumatic brain injury.

    Science.gov (United States)

    Neumann, Dawn; McDonald, Brenna C; West, John; Keiski, Michelle A; Wang, Yang

    2016-06-01

    The neurobiological mechanisms that underlie facial affect recognition deficits after traumatic brain injury (TBI) have not yet been identified. Using functional magnetic resonance imaging (fMRI), study aims were to 1) determine if there are differences in brain activation during facial affect processing in people with TBI who have facial affect recognition impairments (TBI-I) relative to people with TBI and healthy controls who do not have facial affect recognition impairments (TBI-N and HC, respectively); and 2) identify relationships between neural activity and facial affect recognition performance. A facial affect recognition screening task performed outside the scanner was used to determine group classification; TBI patients who performed greater than one standard deviation below normal performance scores were classified as TBI-I, while TBI patients with normal scores were classified as TBI-N. An fMRI facial recognition paradigm was then performed within the 3T environment. Results from 35 participants are reported (TBI-I = 11, TBI-N = 12, and HC = 12). For the fMRI task, TBI-I and TBI-N groups scored significantly lower than the HC group. Blood oxygenation level-dependent (BOLD) signals for facial affect recognition compared to a baseline condition of viewing a scrambled face, revealed lower neural activation in the right fusiform gyrus (FG) in the TBI-I group than the HC group. Right fusiform gyrus activity correlated with accuracy on the facial affect recognition tasks (both within and outside the scanner). Decreased FG activity suggests facial affect recognition deficits after TBI may be the result of impaired holistic face processing. Future directions and clinical implications are discussed.

  15. Natural Language Processing: Word Recognition without Segmentation.

    Science.gov (United States)

    Saeed, Khalid; Dardzinska, Agnieszka

    2001-01-01

    Discussion of automatic recognition of hand and machine-written cursive text using the Arabic alphabet focuses on an algorithm for word recognition. Describes results of testing words for recognition without segmentation and considers the algorithms' use for words of different fonts and for processing whole sentences. (Author/LRW)

  16. Confidence and rejection in automatic speech recognition

    Science.gov (United States)

    Colton, Larry Don

    Automatic speech recognition (ASR) is performed imperfectly by computers. For some designated part (e.g., word or phrase) of the ASR output, rejection is deciding (yes or no) whether it is correct, and confidence is the probability (0.0 to 1.0) of it being correct. This thesis presents new methods of rejecting errors and estimating confidence for telephone speech. These are also called word or utterance verification and can be used in wordspotting or voice-response systems. Open-set or out-of-vocabulary situations are a primary focus. Language models are not considered. In vocabulary-dependent rejection all words in the target vocabulary are known in advance and a strategy can be developed for confirming each word. A word-specific artificial neural network (ANN) is shown to discriminate well, and scores from such ANNs are shown on a closed-set recognition task to reorder the N-best hypothesis list (N=3) for improved recognition performance. Segment-based duration and perceptual linear prediction (PLP) features are shown to perform well for such ANNs. The majority of the thesis concerns vocabulary- and task-independent confidence and rejection based on phonetic word models. These can be computed for words even when no training examples of those words have been seen. New techniques are developed using phoneme ranks instead of probabilities in each frame. These are shown to perform as well as the best other methods examined despite the data reduction involved. Certain new weighted averaging schemes are studied but found to give no performance benefit. Hierarchical averaging is shown to improve performance significantly: frame scores combine to make segment (phoneme state) scores, which combine to make phoneme scores, which combine to make word scores. Use of intermediate syllable scores is shown to not affect performance. Normalizing frame scores by an average of the top probabilities in each frame is shown to improve performance significantly. Perplexity of the wrong

  17. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

    Directory of Open Access Journals (Sweden)

    Muhammad Hameed Siddiqi

    2013-12-01

    Full Text Available Over the last decade, human facial expressions recognition (FER has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER.

  18. Embedded Face Detection and Recognition

    Directory of Open Access Journals (Sweden)

    Göksel Günlü

    2012-10-01

    Full Text Available The need to increase security in open or public spaces has in turn given rise to the requirement to monitor these spaces and analyse those images on‐site and on‐time. At this point, the use of smart cameras ‐ of which the popularity has been increasing ‐ is one step ahead. With sensors and Digital Signal Processors (DSPs, smart cameras generate ad hoc results by analysing the numeric images transmitted from the sensor by means of a variety of image‐processing algorithms. Since the images are not transmitted to a distance processing unit but rather are processed inside the camera, it does not necessitate high‐ bandwidth networks or high processor powered systems; it can instantaneously decide on the required access. Nonetheless, on account of restricted memory, processing power and overall power, image processing algorithms need to be developed and optimized for embedded processors. Among these algorithms, one of the most important is for face detection and recognition. A number of face detection and recognition methods have been proposed recently and many of these methods have been tested on general‐purpose processors. In smart cameras ‐ which are real‐life applications of such methods ‐ the widest use is on DSPs. In the present study, the Viola‐Jones face detection method ‐ which was reported to run faster on PCs ‐ was optimized for DSPs; the face recognition method was combined with the developed sub‐region and mask‐based DCT (Discrete Cosine Transform. As the employed DSP is a fixed‐point processor, the processes were performed with integers insofar as it was possible. To enable face recognition, the image was divided into sub‐ regions and from each sub‐region the robust coefficients against disruptive elements ‐ like face expression, illumination, etc. ‐ were selected as the features. The discrimination of the selected features was enhanced via LDA (Linear Discriminant Analysis and then employed for

  19. Embedded Face Detection and Recognition

    Directory of Open Access Journals (Sweden)

    Göksel Günlü

    2012-10-01

    Full Text Available The need to increase security in open or public spaces has in turn given rise to the requirement to monitor these spaces and analyse those images on-site and on-time. At this point, the use of smart cameras – of which the popularity has been increasing – is one step ahead. With sensors and Digital Signal Processors (DSPs, smart cameras generate ad hoc results by analysing the numeric images transmitted from the sensor by means of a variety of image-processing algorithms. Since the images are not transmitted to a distance processing unit but rather are processed inside the camera, it does not necessitate high-bandwidth networks or high processor powered systems; it can instantaneously decide on the required access. Nonetheless, on account of restricted memory, processing power and overall power, image processing algorithms need to be developed and optimized for embedded processors. Among these algorithms, one of the most important is for face detection and recognition. A number of face detection and recognition methods have been proposed recently and many of these methods have been tested on general-purpose processors. In smart cameras – which are real-life applications of such methods – the widest use is on DSPs. In the present study, the Viola-Jones face detection method – which was reported to run faster on PCs – was optimized for DSPs; the face recognition method was combined with the developed sub-region and mask-based DCT (Discrete Cosine Transform. As the employed DSP is a fixed-point processor, the processes were performed with integers insofar as it was possible. To enable face recognition, the image was divided into sub-regions and from each sub-region the robust coefficients against disruptive elements – like face expression, illumination, etc. – were selected as the features. The discrimination of the selected features was enhanced via LDA (Linear Discriminant Analysis and then employed for recognition. Thanks to its

  20. Normal mode gating motions of a ligand-gated ion channel persist in a fully hydrated lipid bilayer model.

    Science.gov (United States)

    Bertaccini, Edward J; Trudell, James R; Lindahl, Erik

    2010-08-18

    We have previously used molecular modeling and normal-mode analyses combined with experimental data to visualize a plausible model of a transmembrane ligand-gated ion channel. We also postulated how the gating motion of the channel may be affected by the presence of various ligands, especially anesthetics. As is typical for normal-mode analyses, those studies were performed in vacuo to reduce the computational complexity of the problem. While such calculations constitute an efficient way to model the large scale structural flexibility of transmembrane proteins, they can be criticized for neglecting the effects of an explicit phospholipid bilayer or hydrated environment. Here, we show the successful calculation of normal-mode motions for our model of a glycine α-1 receptor, now suspended in a fully hydrated lipid bilayer. Despite the almost uniform atomic density, the introduction of water and lipid does not grossly distort the overall gating motion. Normal-mode analysis revealed that even a fully immersed glycine α-1 receptor continues to demonstrate an iris-like channel gating motion as a low-frequency, high-amplitude natural harmonic vibration consistent with channel gating. Furthermore, the introduction of periodic boundary conditions allows the examination of simultaneous harmonic vibrations of lipid in synchrony with the protein gating motions that are compatible with reasonable lipid bilayer perturbations. While these perturbations tend to influence the overall protein motion, this work provides continued support for the iris-like motion model that characterizes gating within the family of ligand-gated ion channels.

  1. Revisiting the Process of Normalization.

    Science.gov (United States)

    Zener, Rita Schaefer

    1999-01-01

    Defines normalization and deviations in child development. Discusses the three different levels in the normalization process. Asserts that guiding the process of normalization should drive the practice of Montessori education. Concludes that whenever there are brief episodes of normalization, the true nature of the child shows itself. (JS)

  2. Image Reconstruction, Recognition, Using Image Processing, Pattern Recognition and the Hough Transform.

    Science.gov (United States)

    Seshadri, M. D.

    1992-01-01

    In this dissertation research, we have demonstrated the need for integration of various imaging methodologies, such as image reconstruction from projections, image processing, pattern and feature recognition using chain codes and the Hough transform. Further an integration of these image processing techniques have been brought about for medical imaging systems. An example of this is, classification and identification of brain scans, into normal, haemorrhaged, and lacunar infarcted brain scans. Low level processing was performed using LOG and a variation of LOG. Intermediate level processing used contour completion and chain encoding. Hough transform was used to detect any analytic shapes in the edge images. All these information were used by the data abstraction routine which also extracted information from the user, in the form of a general query. These were input into a backpropagation, which is a very popular supervised neural network. During learning process an output vector was supplied by the expert to the neural network. While performing the neural network compared the input and with the help of the weight matrix computed the output. This output was compared with the expert's opinion and a percentage deviation was calculated. In the case of brain scans this value was about 95%, when the test input vector did not vary, by more than two pixels with the training or learning input vector. A good classification of the brain scans were performed using the integrated imaging system. Identification of various organs in the abdominal region was also successful, within 90% recognition rate, depending on the noise in the image.

  3. Normal transmitting boundary conditions

    Institute of Scientific and Technical Information of China (English)

    廖振鹏

    1996-01-01

    The multi-transmitting formula (MTF) governed by a single artificial speed is analytically developed into a generalized MTF governed by a few artificial speeds to improve its capacity in simultaneous simulation of several one-way waves propagating at different speeds.The generalized MTF is then discretized and further generalized using the space extrapolation to improve its accuracies in numerical simulation of transient waves at large angles of incidence.The above two successive generalizitions of MTF based on the notion of normal transmission lead to a compact formula of local non-reflecting boundary condition.The formula not only provides a general representation of the major schemes of existing local boundary conditions but can be used to generate new schemes,which combine advantages of different schemes.

  4. Evaluating the Normal Distribution

    Directory of Open Access Journals (Sweden)

    George Marsaglia

    2004-07-01

    Full Text Available This article provides a little table-free C function that evaluates the normal distribution with absolute error less than 8 x 10 -16 . A small extension provides relative error near the limit available in double precision: 14 to 16 digits, the limits determined mainly by the computer's ability to evaluate exp(-t for large t. Results are compared with those provided by calls to erf or erfc functions, the best of which compare favorably, others do not, and all appear to be much more complicated than need be to get either absolute accuracy less than 10-15 or relative accuracy to the exp(-limited 14 to 16 digits. Also provided: A short history of the error function erf and its intended use, as well as, in the "browse files" attachment, various erf or erfc versions used for comparison.

  5. Face Recognition using Curvelet Transform

    CERN Document Server

    Cohen, Rami

    2011-01-01

    Face recognition has been studied extensively for more than 20 years now. Since the beginning of 90s the subject has became a major issue. This technology is used in many important real-world applications, such as video surveillance, smart cards, database security, internet and intranet access. This report reviews recent two algorithms for face recognition which take advantage of a relatively new multiscale geometric analysis tool - Curvelet transform, for facial processing and feature extraction. This transform proves to be efficient especially due to its good ability to detect curves and lines, which characterize the human's face. An algorithm which is based on the two algorithms mentioned above is proposed, and its performance is evaluated on three data bases of faces: AT&T (ORL), Essex Grimace and Georgia-Tech. k-nearest neighbour (k-NN) and Support vector machine (SVM) classifiers are used, along with Principal Component Analysis (PCA) for dimensionality reduction. This algorithm shows good results, ...

  6. Motion Primitives for Action Recognition

    DEFF Research Database (Denmark)

    Fihl, Preben; Holte, Michael Boelstoft; Moeslund, Thomas B.

    2007-01-01

    The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent...... the actions as a sequence of temporal isolated instances, denoted primitives. These primitives are each defined by four features extracted from motion images. The primitives are recognized in each frame based on a trained classifier resulting in a sequence of primitives. From this sequence we recognize...... different temporal actions using a probabilistic Edit Distance method. The method is tested on different actions with and without noise and the results show recognition rates of 88.7% and 85.5%, respectively....

  7. Emotion Recognition using Speech Features

    CERN Document Server

    Rao, K Sreenivasa

    2013-01-01

    “Emotion Recognition Using Speech Features” covers emotion-specific features present in speech and discussion of suitable models for capturing emotion-specific information for distinguishing different emotions.  The content of this book is important for designing and developing  natural and sophisticated speech systems. Drs. Rao and Koolagudi lead a discussion of how emotion-specific information is embedded in speech and how to acquire emotion-specific knowledge using appropriate statistical models. Additionally, the authors provide information about using evidence derived from various features and models. The acquired emotion-specific knowledge is useful for synthesizing emotions. Discussion includes global and local prosodic features at syllable, word and phrase levels, helpful for capturing emotion-discriminative information; use of complementary evidences obtained from excitation sources, vocal tract systems and prosodic features in order to enhance the emotion recognition performance;  and pro...

  8. Gesture Recognition Based Mouse Events

    Directory of Open Access Journals (Sweden)

    Rachit Puri

    2013-12-01

    Full Text Available This paper presents the maneuver of mouse pointer a nd performs various mouse operations such as left click, right click, double click, drag etc using ge stures recognition technique. Recognizing gestures is a complex task which involves many aspects such as mo tion modeling, motion analysis, pattern recognition and machine learning. Keeping all the essential factors in mind a system has been created which recognizes the movement of fingers and various patterns formed by them. Color caps have been used for fingers to distinguish it f rom the background color such as skin color. Thus recog nizing the gestures various mouse events have been performed. The application has been created on MATL AB environment with operating system as windows 7.

  9. FINGER-VEIN RECOGNITION SYSTEMS

    Directory of Open Access Journals (Sweden)

    A.Haritha Deepthi

    2015-10-01

    Full Text Available As the Person‟s/Organization‟s Private information‟s are becoming very easy to access, the demand for a Simple, Convenient, Efficient, and a highly Securable Authentication System has been increased. In considering these requirements for data Protection, Biometrics, which uses human physiological or behavioral system for personal Identification has been found as a solution for these difficulties. However most of the biometric systems have high complexity in both time and space. So we are going to use a Real time Finger-Vein recognition System for authentication purposes. In this paper we had implemented the Finger Vein Recognition concept using MATLAB R2013a. The features used are Lacunarity Distance, Blanket Dimension distance. This has more accuracy when compared to conventional methods.

  10. Phoneme Recognition Using Acoustic Events

    CERN Document Server

    Huebener, K; Huebener, Kai; Carson-Berndsen, Julie

    1994-01-01

    This paper presents a new approach to phoneme recognition using nonsequential sub--phoneme units. These units are called acoustic events and are phonologically meaningful as well as recognizable from speech signals. Acoustic events form a phonologically incomplete representation as compared to distinctive features. This problem may partly be overcome by incorporating phonological constraints. Currently, 24 binary events describing manner and place of articulation, vowel quality and voicing are used to recognize all German phonemes. Phoneme recognition in this paradigm consists of two steps: After the acoustic events have been determined from the speech signal, a phonological parser is used to generate syllable and phoneme hypotheses from the event lattice. Results obtained on a speaker--dependent corpus are presented.

  11. Offline Handwritten Devanagari Script Recognition

    Directory of Open Access Journals (Sweden)

    Ved Prakash Agnihotri

    2012-07-01

    Full Text Available Handwritten Devanagari script recognition system using neural network is presented in this paper. Diagonal based feature extraction is used for extracting features of the handwritten Devanagari script. After that these feature of each character image is converted into chromosome bit string of length 378. More than 1000 sample is used for training and testing purpose in this proposed work. It is attempted to use the power of genetic algorithm to recognize the character. In step-I preprocessing on the character image, then image suitable for feature extraction as here is used. Diagonal based feature extraction method to extract 54 features to each character. In the next step character recognize image in which extracted feature in converted into Chromosome bit string of size 378. In recognition step using fitness function in which find the Chromosome difference between unknown character and Chromosome which are store in data base.

  12. Molecular Recognition and Ligand Association

    Science.gov (United States)

    Baron, Riccardo; McCammon, J. Andrew

    2013-04-01

    We review recent developments in our understanding of molecular recognition and ligand association, focusing on two major viewpoints: (a) studies that highlight new physical insight into the molecular recognition process and the driving forces determining thermodynamic signatures of binding and (b) recent methodological advances in applications to protein-ligand binding. In particular, we highlight the challenges posed by compensating enthalpic and entropic terms, competing solute and solvent contributions, and the relevance of complex configurational ensembles comprising multiple protein, ligand, and solvent intermediate states. As more complete physics is taken into account, computational approaches increase their ability to complement experimental measurements, by providing a microscopic, dynamic view of ensemble-averaged experimental observables. Physics-based approaches are increasingly expanding their power in pharmacology applications.

  13. Physics of Automatic Target Recognition

    CERN Document Server

    Sadjadi, Firooz

    2007-01-01

    Physics of Automatic Target Recognition addresses the fundamental physical bases of sensing, and information extraction in the state-of-the art automatic target recognition field. It explores both passive and active multispectral sensing, polarimetric diversity, complex signature exploitation, sensor and processing adaptation, transformation of electromagnetic and acoustic waves in their interactions with targets, background clutter, transmission media, and sensing elements. The general inverse scattering, and advanced signal processing techniques and scientific evaluation methodologies being used in this multi disciplinary field will be part of this exposition. The issues of modeling of target signatures in various spectral modalities, LADAR, IR, SAR, high resolution radar, acoustic, seismic, visible, hyperspectral, in diverse geometric aspects will be addressed. The methods for signal processing and classification will cover concepts such as sensor adaptive and artificial neural networks, time reversal filt...

  14. EMOTIONAL SPEECH RECOGNITION BASED ON SVM WITH GMM SUPERVECTOR

    Institute of Scientific and Technical Information of China (English)

    Chen Yanxiang; Xie Jian

    2012-01-01

    Emotion recognition from speech is an important field of research in human computer interaction.In this letter the framework of Support Vector Machines (SVM) with Gaussian Mixture Model (GMM) supervector is introduced for emotional speech recognition.Because of the importance of variance in reflecting the distribution of speech,the normalized mean vectors potential to exploit the information from the variance are adopted to form the GMM supervector.Comparative experiments from five aspects are conducted to study their corresponding effect to system performance.The experiment results,which indicate that the influence of number of mixtures is strong as well as influence of duration is weak,provide basis for the train set selection of Universal Background Model (UBM).

  15. Discriminative tonal feature extraction method in mandarin speech recognition

    Institute of Scientific and Technical Information of China (English)

    HUANG Hao; ZHU Jie

    2007-01-01

    To utilize the supra-segmental nature of Mandarin tones, this article proposes a feature extraction method for hidden markov model (HMM) based tone modeling. The method uses linear transforms to project F0 (fundamental frequency) features of neighboring syllables as compensations, and adds them to the original F0 features of the current syllable. The transforms are discriminatively trained by using an objective function termed as "minimum tone error", which is a smooth approximation of tone recognition accuracy. Experiments show that the new tonal features achieve 3.82% tone recognition rate improvement, compared with the baseline, using maximum likelihood trained HMM on the normal F0 features. Further experiments show that discriminative HMM training on the new features is 8.78% better than the baseline.

  16. Connected digit speech recognition system for Malayalam language

    Indian Academy of Sciences (India)

    Cini Kurian; Kannan Balakrishnan

    2013-12-01

    A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer for Malayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization and continuous density Hidden Markov Model (HMM) in the recognition process. Viterbi algorithm is used for decoding. The training data base has the utterance of 21 speakers from the age group of 20 to 40 years and the sound is recorded in the normal office environment where each speaker is asked to read 20 set of continuous digits. The system obtained an accuracy of 99.5 % with the unseen data.

  17. Palmprint Recognition by Applying Wavelet-Based Kernel PCA

    Institute of Scientific and Technical Information of China (English)

    Murat Ekinci; Murat Aykut

    2008-01-01

    This paper presents a wavelet-based kernel Principal Component Analysis (PCA) method by integrating the Daubechies wavelet representation of palm images and the kernel PCA method for palmprint recognition. Kernel PCA is a technique for nonlinear dimension reduction of data with an underlying nonlinear spatial structure. The intensity values of the palmprint image are first normalized by using mean and standard deviation. The palmprint is then transformed into the wavelet domain to decompose palm images and the lowest resolution subband coefficients are chosen for palm representation.The kernel PCA method is then applied to extract non-linear features from the subband coefficients. Finally, similarity measurement is accomplished by using weighted Euclidean linear distance-based nearest neighbor classifier. Experimental results on PolyU Palmprint Databases demonstrate that the proposed approach achieves highly competitive performance with respect to the published palmprint recognition approaches.

  18. Speech emotion recognition based on statistical pitch model

    Institute of Scientific and Technical Information of China (English)

    WANG Zhiping; ZHAO Li; ZOU Cairong

    2006-01-01

    A modified Parzen-window method, which keep high resolution in low frequencies and keep smoothness in high frequencies, is proposed to obtain statistical model. Then, a gender classification method utilizing the statistical model is proposed, which have a 98% accuracy of gender classification while long sentence is dealt with. By separation the male voice and female voice, the mean and standard deviation of speech training samples with different emotion are used to create the corresponding emotion models. Then the Bhattacharyya distance between the test sample and statistical models of pitch, are utilized for emotion recognition in speech.The normalization of pitch for the male voice and female voice are also considered, in order to illustrate them into a uniform space. Finally, the speech emotion recognition experiment based on K Nearest Neighbor shows that, the correct rate of 81% is achieved, where it is only 73.85%if the traditional parameters are utilized.

  19. Research on Radar Emitter Attribute Recognition Method

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    In order to solve emitter recognition problems in a practical reconnaissance environment, attribute mathematics is introduced. The basic concepts and theory of attribute set and attribute measure are described in detail. A new attribute recognition method based on attribute measure is presented in this paper. Application example is given, which demonstrates this new method is accurate and effective. Moreover, computer simulation for recognizing the emitter purpose is selected, and compared with classical statistical pattern recognition through simulation. The excellent experimental results demonstrate that this is a brand-new attribute recognition method as compared to existing statistical pattern recognition techniques.

  20. Famous face recognition, face matching, and extraversion.

    Science.gov (United States)

    Lander, Karen; Poyarekar, Siddhi

    2015-01-01

    It has been previously established that extraverts who are skilled at interpersonal interaction perform significantly better than introverts on a face-specific recognition memory task. In our experiment we further investigate the relationship between extraversion and face recognition, focusing on famous face recognition and face matching. Results indicate that more extraverted individuals perform significantly better on an upright famous face recognition task and show significantly larger face inversion effects. However, our results did not find an effect of extraversion on face matching or inverted famous face recognition.

  1. Pattern Recognition Using Associative Memories

    OpenAIRE

    Burles, Nathan John

    2014-01-01

    The human brain is extremely effective at performing pattern recognition, even in the presence of noisy or distorted inputs. Artificial neural networks attempt to imitate the structure of the brain, often with a view to mimicking its success. The binary correlation matrix memory (CMM) is a particular type of neural network that is capable of learning and recalling associations extremely quickly, as well as displaying a high storage capacity and having the ability to generalise from patterns a...

  2. Named Entity Recognition for IDEAL

    OpenAIRE

    Du, Qianzhou; Zhang, Xuan

    2015-01-01

    This project explored how to apply Named Entity Recognition to large Twitter and web page datasets to extract useful entities such as people, organization, location, and date. In addition, this NER utility has been scaled to the MapReduce framework on the Hadoop cluster. A schema and software allow this to be integrated with IDEAL. The term “Named Entity”, which was first introduced by Grishman and Sundheim, is widely used in Natural Language Processing (NLP). The researchers were focusing...

  3. Attentional Selection in Object Recognition

    Science.gov (United States)

    1993-02-01

    understanding of a scene is important for robots to deal effectively with their environment. This may involve determining which objects are present in a...image color texture edge parallel parallel age&’ segatentatio line agorithas detector detector line rasp eser"Of color texture edge repow parallel...generic so that it could possibly be used for other tasks that do not necessarily involve recognition. Thus using this se- lection mechanism, a robot

  4. WHEEL CHAIR USING VOICE RECOGNITION

    OpenAIRE

    Manish Kumar Yadav*; Rajat Kumar; Santosh Yadav; Ravindra Prajapati; Prof. Kshirsagar

    2016-01-01

    The wide spread prevalence of lost limbs and sensing system is of major concern in present day due to wars, accident, age and health problems. This Omni-directional wheelchair was designed for the less able elderly to move more flexibly in narrow spaces, such as elevators or small aisle. The wheelchair is developed to help disabled patients by using speech recognition system to control the movement of wheelchair in different directions by using voice commands and also the simple movement of t...

  5. Activity Recognition in Social Media

    Science.gov (United States)

    2015-12-29

    activity is splitting. 6 Crowd video classification Ability to identify crowd behavior enables crowd management systems to design and manage public...characterize group activities . We then showed the effectiveness of group level features in crowd video classification . 9 List of Publications 1. N. Bhargava, S...AFRL-AFOSR-JP-TR-2016-0044 Activity Recognition in Social Media Subhasis Chaudhuri INDIAN INSTITUTE OF TECHNOLOGY BOMBAY Final Report 05/09/2016

  6. Speech Recognition in 7 Languages

    Science.gov (United States)

    2000-08-01

    best monolingual cross-lingual [10] F. Weng, H. Bratt, L. Neumeyer, and A. Stol- recognizers could not always be tested. cke. A Study of Multilingual ...are r the same tm the proaches, namely portation, cross-lingual and simul- two languages are recognized at the same time, the taneous multilingual ...in cross-lingual will present experiments and results for different ap- recognition for different baseline systems and found proaches of multilingual

  7. Object Recognition Using Range Images.

    Science.gov (United States)

    1985-12-01

    with a multiplexed filter which contains a number of rotated and scaled filters (Leib and others, 1978:2892-2899) and (Mendelsohn and Wohlers , 1980...Butler, Steve. "Three Dimensional Pattern Recognition." Unpublished report . Electro-Optical Terminal Guidance Branch, Eglin AFB FL, 1985. Casasent, David...Correlation:Final Report , June 1982-January 1984. Electro-Optical Terminal Guidance Branch, Eglin AFB FL, August 1985. 136 rv Fujil, H. and Y. Ohtsuba

  8. Feature Recognition for Virtual Machining

    OpenAIRE

    Xú, Shixin; Anwer, Nabil; Qiao, Lihong

    2014-01-01

    International audience; Virtual machining uses software tools to simulate machining processes in virtual environments ahead of actual production. This paper proposes that feature recognition techniques can be applied in the course of virtual machining, such as identifying some process problems, and presenting corresponding correcting advices. By comparing with the original CAD model, form errors of the machining features can be found. And then corrections are suggested to process designers. T...

  9. Offline arabic character recognition system

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Several languages use the Arabic alphabets and arabic scripts present challenges because the letter shape is context sensitive. For the past three decades, there has been a mounting interest among researchers in this problem. In this paper we present an Arabic Character Recognition system and quence steps of recognizing Arabic text. These steps are separately discussed, and previous research work on each step is reviewed. Also in this paper we give some samples of Arabic fonts.

  10. Symbol Recognition using Spatial Relations

    OpenAIRE

    K.C., Santosh; Lamiroy, Bart; Wendling, Laurent

    2012-01-01

    International audience; In this paper, we present a method for symbol recognition based on the spatio-structural description of a 'vocabulary' of extracted visual elementary parts. It is applied to symbols in electrical wiring diagrams. The method consists of first identifying vocabulary elements into different groups based on their types (e.g., circle, corner ). We then compute spatial relations between the possible pairs of labelled vocabulary types which are further used as a basis for bui...

  11. Impairments in negative emotion recognition and empathy for pain in Huntington's disease families.

    Science.gov (United States)

    Baez, Sandra; Herrera, Eduar; Gershanik, Oscar; Garcia, Adolfo M; Bocanegra, Yamile; Kargieman, Lucila; Manes, Facundo; Ibanez, Agustin

    2015-02-01

    Lack of empathy and emotional disturbances are prominent clinical features of Huntington's disease (HD). While emotion recognition impairments in HD patients are well established, there are no experimental designs assessing empathy in this population. The present study seeks to cover such a gap in the literature. Eighteen manifest HD patients, 19 first-degree asymptomatic relatives, and 36 healthy control participants completed two emotion-recognition tasks with different levels of contextual dependence. They were also evaluated with an empathy-for-pain task tapping the perception of intentional and accidental harm. Moreover, we explored potential associations among empathy, emotion recognition, and other relevant factors - e.g., executive functions (EF). The results showed that both HD patients and asymptomatic relatives are impaired in the recognition of negative emotions from isolated faces. However, their performance in emotion recognition was normal in the presence of contextual cues. HD patients also showed subtle empathy impairments. There were no significant correlations between EF, empathy, and emotion recognition measures in either HD patients or relatives. In controls, EF was positively correlated with emotion recognition. Furthermore, emotion recognition was positively correlated with the performance in the empathy task. Our findings highlight the preserved cognitive abilities in HD families when using more ecological tasks displaying emotional expressions in the context in which they typically appear. Moreover, our results suggest that emotion recognition impairments may constitute a potential biomarker of HD onset and progression. These results contribute to the understanding of emotion recognition and empathy deficits observed in HD and have important theoretical and clinical implications.

  12. Visual abilities are important for auditory-only speech recognition: evidence from autism spectrum disorder.

    Science.gov (United States)

    Schelinski, Stefanie; Riedel, Philipp; von Kriegstein, Katharina

    2014-12-01

    In auditory-only conditions, for example when we listen to someone on the phone, it is essential to fast and accurately recognize what is said (speech recognition). Previous studies have shown that speech recognition performance in auditory-only conditions is better if the speaker is known not only by voice, but also by face. Here, we tested the hypothesis that such an improvement in auditory-only speech recognition depends on the ability to lip-read. To test this we recruited a group of adults with autism spectrum disorder (ASD), a condition associated with difficulties in lip-reading, and typically developed controls. All participants were trained to identify six speakers by name and voice. Three speakers were learned by a video showing their face and three others were learned in a matched control condition without face. After training, participants performed an auditory-only speech recognition test that consisted of sentences spoken by the trained speakers. As a control condition, the test also included speaker identity recognition on the same auditory material. The results showed that, in the control group, performance in speech recognition was improved for speakers known by face in comparison to speakers learned in the matched control condition without face. The ASD group lacked such a performance benefit. For the ASD group auditory-only speech recognition was even worse for speakers known by face compared to speakers not known by face. In speaker identity recognition, the ASD group performed worse than the control group independent of whether the speakers were learned with or without face. Two additional visual experiments showed that the ASD group performed worse in lip-reading whereas face identity recognition was within the normal range. The findings support the view that auditory-only communication involves specific visual mechanisms. Further, they indicate that in ASD, speaker-specific dynamic visual information is not available to optimize auditory

  13. Human Emotion Recognition From Speech

    Directory of Open Access Journals (Sweden)

    Miss. Aparna P. Wanare

    2014-07-01

    Full Text Available Speech Emotion Recognition is a recent research topic in the Human Computer Interaction (HCI field. The need has risen for a more natural communication interface between humans and computer, as computers have become an integral part of our lives. A lot of work currently going on to improve the interaction between humans and computers. To achieve this goal, a computer would have to be able to distinguish its present situation and respond differently depending on that observation. Part of this process involves understanding a user‟s emotional state. To make the human computer interaction more natural, the objective is that computer should be able to recognize emotional states in the same as human does. The efficiency of emotion recognition system depends on type of features extracted and classifier used for detection of emotions. The proposed system aims at identification of basic emotional states such as anger, joy, neutral and sadness from human speech. While classifying different emotions, features like MFCC (Mel Frequency Cepstral Coefficient and Energy is used. In this paper, Standard Emotional Database i.e. English Database is used which gives the satisfactory detection of emotions than recorded samples of emotions. This methodology describes and compares the performances of Learning Vector Quantization Neural Network (LVQ NN, Multiclass Support Vector Machine (SVM and their combination for emotion recognition.

  14. Gesture Recognition Technology: A Review

    Directory of Open Access Journals (Sweden)

    PALLAVI HALARNKAR

    2012-11-01

    Full Text Available Gesture Recognition Technology has evolved greatly over the years. The past has seen the contemporary Human – Computer Interface techniques and their drawbacks, which limit the speed and naturalness of the human brain and body. As a result gesture recognition technology has developed since the early 1900s with a view to achieving ease and lessening the dependence on devices like keyboards, mice and touchscreens. Attempts have been made to combine natural gestures to operate with the technology around us to enable us to make optimum use of our body gestures making our work faster and more human friendly. The present has seen huge development in this field ranging from devices like virtual keyboards, video game controllers to advanced security systems which work on face, hand and body recognition techniques. The goal is to make full use of themovements of the body and every angle made by the parts of the body in order to supplement technology to become human friendly and understand natural human behavior and gestures. The future of this technology is very bright with prototypes of amazing devices in research and development to make the world equipped with digital information at hand whenever and wherever required.

  15. Fingerprint recognition using image processing

    Science.gov (United States)

    Dholay, Surekha; Mishra, Akassh A.

    2011-06-01

    Finger Print Recognition is concerned with the difficult task of matching the images of finger print of a person with the finger print present in the database efficiently. Finger print Recognition is used in forensic science which helps in finding the criminals and also used in authentication of a particular person. Since, Finger print is the only thing which is unique among the people and changes from person to person. The present paper describes finger print recognition methods using various edge detection techniques and also how to detect correct finger print using a camera images. The present paper describes the method that does not require a special device but a simple camera can be used for its processes. Hence, the describe technique can also be using in a simple camera mobile phone. The various factors affecting the process will be poor illumination, noise disturbance, viewpoint-dependence, Climate factors, and Imaging conditions. The described factor has to be considered so we have to perform various image enhancement techniques so as to increase the quality and remove noise disturbance of image. The present paper describe the technique of using contour tracking on the finger print image then using edge detection on the contour and after that matching the edges inside the contour.

  16. Additive attacks on speaker recognition

    Science.gov (United States)

    Farrokh Baroughi, Alireza; Craver, Scott

    2014-02-01

    Speaker recognition is used to identify a speaker's voice from among a group of known speakers. A common method of speaker recognition is a classification based on cepstral coefficients of the speaker's voice, using a Gaussian mixture model (GMM) to model each speaker. In this paper we try to fool a speaker recognition system using additive noise such that an intruder is recognized as a target user. Our attack uses a mixture selected from a target user's GMM model, inverting the cepstral transformation to produce noise samples. In our 5 speaker data base, we achieve an attack success rate of 50% with a noise signal at 10dB SNR, and 95% by increasing noise power to 0dB SNR. The importance of this attack is its simplicity and flexibility: it can be employed in real time with no processing of an attacker's voice, and little computation is needed at the moment of detection, allowing the attack to be performed by a small portable device. For any target user, knowing that user's model or voice sample is sufficient to compute the attack signal, and it is enough that the intruder plays it while he/she is uttering to be classiffed as the victim.

  17. Multithread Face Recognition in Cloud

    Directory of Open Access Journals (Sweden)

    Dakshina Ranjan Kisku

    2016-01-01

    Full Text Available Faces are highly challenging and dynamic objects that are employed as biometrics evidence in identity verification. Recently, biometrics systems have proven to be an essential security tools, in which bulk matching of enrolled people and watch lists is performed every day. To facilitate this process, organizations with large computing facilities need to maintain these facilities. To minimize the burden of maintaining these costly facilities for enrollment and recognition, multinational companies can transfer this responsibility to third-party vendors who can maintain cloud computing infrastructures for recognition. In this paper, we showcase cloud computing-enabled face recognition, which utilizes PCA-characterized face instances and reduces the number of invariant SIFT points that are extracted from each face. To achieve high interclass and low intraclass variances, a set of six PCA-characterized face instances is computed on columns of each face image by varying the number of principal components. Extracted SIFT keypoints are fused using sum and max fusion rules. A novel cohort selection technique is applied to increase the total performance. The proposed protomodel is tested on BioID and FEI face databases, and the efficacy of the system is proven based on the obtained results. We also compare the proposed method with other well-known methods.

  18. Relative Contributions of Spectral and Temporal Cues for Speech Recognition in Patients with Sensorineural Hearing Loss

    Institute of Scientific and Technical Information of China (English)

    XU Li; ZHOU Ning; Rebecca Brashears; Katherine Rife

    2008-01-01

    The present study was designed to examine speech recognition in patients with sensorineural hearing loss when the temporal and spectral information in the speech signals were co-varied. Four subjects with mild to moderate sensorineural hearing loss were recruited to participate in consonant and vowel recognition tests that used speech stimuli processed through a noise-excited voeoder. The number of channels was varied between 2 and 32, which defined spectral information. The lowpass cutoff frequency of the temporal envelope extractor was varied from 1 to 512 Hz, which defined temporal information. Results indicate that performance of subjects with sensorineural heating loss varied tremendously among the subjects. For consonant recognition, patterns of relative contributions of spectral and temporal information were similar to those in normal-hearing subjects. The utility of temporal envelope information appeared to be normal in the hearing-impaired listeners. For vowel recognition, which depended predominately on spectral information, the performance plateau was achieved with numbers of channels as high as 16-24, much higher than expected, given that the frequency selectivity in patients with sensorineural hearing loss might be compromised. In order to understand the mechanisms on how hearing-impaired listeners utilize spectral and temporal cues for speech recognition, future studies that involve a large sample of patients with sensorineural hearing loss will be necessary to elucidate the relationship between frequency selectivity as well as central processing capability and speech recognition performance using vocoded signals.

  19. Infant visual attention and object recognition.

    Science.gov (United States)

    Reynolds, Greg D

    2015-05-15

    This paper explores the role visual attention plays in the recognition of objects in infancy. Research and theory on the development of infant attention and recognition memory are reviewed in three major sections. The first section reviews some of the major findings and theory emerging from a rich tradition of behavioral research utilizing preferential looking tasks to examine visual attention and recognition memory in infancy. The second section examines research utilizing neural measures of attention and object recognition in infancy as well as research on brain-behavior relations in the early development of attention and recognition memory. The third section addresses potential areas of the brain involved in infant object recognition and visual attention. An integrated synthesis of some of the existing models of the development of visual attention is presented which may account for the observed changes in behavioral and neural measures of visual attention and object recognition that occur across infancy.

  20. Optical pattern recognition for printed music notation

    Science.gov (United States)

    Homenda, Wladyslaw

    1995-03-01

    The paper presents problems related to automated recognition of printed music notation. Music notation recognition is a challenging problem in both fields: pattern recognition and knowledge representation. Music notation symbols, though well characterized by their features, are arranged in elaborated way in real music notation, which makes recognition task very difficult and still open for new ideas. On the other hand, the aim of the system, i.e. application of acquired printed music into further processing requires special representation of music data. Due to complexity of music nature and music notation, music representation is one of the key issue in music notation recognition and music processing. The problems of pattern recognition and knowledge representation in context or music processing are discussed in this paper. MIDISCAN, the computer system for music notation recognition and music processing, is presented.

  1. Normal labour: a concept analysis.

    Science.gov (United States)

    Gould, D

    2000-02-01

    Midwives practice within the normal childbirth paradigm. It is argued that midwives failure to define normality has allowed increasing technicalization and medicalization of the normal physiological process of birth because doctors so closely define abnormality. A concept analysis model is used to clarify what is meant by the term 'normal labour'; the emphasis being on understanding what normal labour is as it applies to midwifery practice today. This analysis highlights the importance of movement and the sequential nature of normal labour, and reveals how this is implicit within the other uses of both the words normal and labour. The final definition of normal labour offered is intended to be complimentary to existing medical determinants of progress of normal labour, because as the body of the text stresses, medical knowledge is fundamentally enmeshed in midwifery care.

  2. Acquired prosopagnosia without word recognition deficits.

    Science.gov (United States)

    Susilo, Tirta; Wright, Victoria; Tree, Jeremy J; Duchaine, Bradley

    2015-01-01

    It has long been suggested that face recognition relies on specialized mechanisms that are not involved in visual recognition of other object categories, including those that require expert, fine-grained discrimination at the exemplar level such as written words. But according to the recently proposed many-to-many theory of object recognition (MTMT), visual recognition of faces and words are carried out by common mechanisms [Behrmann, M., & Plaut, D. C. ( 2013 ). Distributed circuits, not circumscribed centers, mediate visual recognition. Trends in Cognitive Sciences, 17, 210-219]. MTMT acknowledges that face and word recognition are lateralized, but posits that the mechanisms that predominantly carry out face recognition still contribute to word recognition and vice versa. MTMT makes a key prediction, namely that acquired prosopagnosics should exhibit some measure of word recognition deficits. We tested this prediction by assessing written word recognition in five acquired prosopagnosic patients. Four patients had lesions limited to the right hemisphere while one had bilateral lesions with more pronounced lesions in the right hemisphere. The patients completed a total of seven word recognition tasks: two lexical decision tasks and five reading aloud tasks totalling more than 1200 trials. The performances of the four older patients (3 female, age range 50-64 years) were compared to those of 12 older controls (8 female, age range 56-66 years), while the performances of the younger prosopagnosic (male, 31 years) were compared to those of 14 younger controls (9 female, age range 20-33 years). We analysed all results at the single-patient level using Crawford's t-test. Across seven tasks, four prosopagnosics performed as quickly and accurately as controls. Our results demonstrate that acquired prosopagnosia can exist without word recognition deficits. These findings are inconsistent with a key prediction of MTMT. They instead support the hypothesis that face

  3. Spectrum warping based on sub-glottal resonances in speaker-independent speech recognition

    Institute of Scientific and Technical Information of China (English)

    HOU Limin; HUANG Zhenhua; XIE Juanmin

    2011-01-01

    To reduce degradation in speech recognition due to varied characteristics of different speakers, a method of perceptual frequency warping based on subglottal resonances for speaker normalization is proposed. The warping factor is extracted from the second subglottal resonance using acoustic coupling between subglottis and vocal tract. The second subglottal resonance is independent of the speech content, which reflects the speaker characteristics more than the third formant. The perceptual minimum variation distortionless response (PMVDR) coefficient is normalized, which is more robust and has better anti-noise capability than MFCC. The normalized coefficients are used in the speech-mode training and speech recognition. Experiments show that the word error rate, as compared with MFCC and the spectrum warping by the third formant, decreases by 4% and 3% respectively in clean speech recognition, and by 9% and 5% respectively in a noisy environment. The results indicate that the proposed method can improve the word recognition accuracy in a speaker-independent recognition system.

  4. USE OF IMAGE ENHANCEMENT TECHNIQUES FOR IMPROVING REAL TIME FACE RECOGNITION EFFICIENCY ON WEARABLE GADGETS

    Directory of Open Access Journals (Sweden)

    MUHAMMAD EHSAN RANA

    2017-01-01

    Full Text Available The objective of this research is to study the effects of image enhancement techniques on face recognition performance of wearable gadgets with an emphasis on recognition rate.In this research, a number of image enhancement techniques are selected that include brightness normalization, contrast normalization, sharpening, smoothing, and various combinations of these. Subsequently test images are obtained from AT&T database and Yale Face Database B to investigate the effect of these image enhancement techniques under various conditions such as change of illumination and face orientation and expression.The evaluation of data, collected during this research, revealed that the effect of image pre-processing techniques on face recognition highly depends on the illumination condition under which these images are taken. It is revealed that the benefit of applying image enhancement techniques on face images is best seen when there is high variation of illumination among images. Results also indicate that highest recognition rate is achieved when images are taken under low light condition and image contrast is enhanced using histogram equalization technique and then image noise is reduced using median smoothing filter. Additionally combination of contrast normalization and mean smoothing filter shows good result in all scenarios. Results obtained from test cases illustrate up to 75% improvement in face recognition rate when image enhancement is applied to images in given scenarios.

  5. Localization and Recognition of Dynamic Hand Gestures Based on Hierarchy of Manifold Classifiers

    Science.gov (United States)

    Favorskaya, M.; Nosov, A.; Popov, A.

    2015-05-01

    Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin detector, normalized skeleton representation of one or two hands, and motion history representing by motion vectors normalized through predetermined directions (8 and 16 in our case). Each dynamic gesture is separated into a set of sub-gestures in order to predict a trajectory and remove those samples of gestures, which do not satisfy to current trajectory. The posture classifiers involve the normalized skeleton representation of palm and fingers and relative finger positions using fingertips. The min-max criterion is used for trajectory recognition, and the decision tree technique was applied for posture recognition of sub-gestures. For experiments, a dataset "Multi-modal Gesture Recognition Challenge 2013: Dataset and Results" including 393 dynamic hand-gestures was chosen. The proposed method yielded 84-91% recognition accuracy, in average, for restricted set of dynamic gestures.

  6. LOCALIZATION AND RECOGNITION OF DYNAMIC HAND GESTURES BASED ON HIERARCHY OF MANIFOLD CLASSIFIERS

    Directory of Open Access Journals (Sweden)

    M. Favorskaya

    2015-05-01

    Full Text Available Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin detector, normalized skeleton representation of one or two hands, and motion history representing by motion vectors normalized through predetermined directions (8 and 16 in our case. Each dynamic gesture is separated into a set of sub-gestures in order to predict a trajectory and remove those samples of gestures, which do not satisfy to current trajectory. The posture classifiers involve the normalized skeleton representation of palm and fingers and relative finger positions using fingertips. The min-max criterion is used for trajectory recognition, and the decision tree technique was applied for posture recognition of sub-gestures. For experiments, a dataset “Multi-modal Gesture Recognition Challenge 2013: Dataset and Results” including 393 dynamic hand-gestures was chosen. The proposed method yielded 84–91% recognition accuracy, in average, for restricted set of dynamic gestures.

  7. Developmental prosopagnosia and super-recognition: no special role for surface reflectance processing.

    Science.gov (United States)

    Russell, Richard; Chatterjee, Garga; Nakayama, Ken

    2012-01-01

    Face recognition by normal subjects depends in roughly equal proportions on shape and surface reflectance cues, while object recognition depends predominantly on shape cues. It is possible that developmental prosopagnosics are deficient not in their ability to recognize faces per se, but rather in their ability to use reflectance cues. Similarly, super-recognizers' exceptional ability with face recognition may be a result of superior surface reflectance perception and memory. We tested this possibility by administering tests of face perception and face recognition in which only shape or reflectance cues are available to developmental prosopagnosics, super-recognizers, and control subjects. Face recognition ability and the relative use of shape and pigmentation were unrelated in all the tests. Subjects who were better at using shape or reflectance cues were also better at using the other type of cue. These results do not support the proposal that variation in surface reflectance perception ability is the underlying cause of variation in face recognition ability. Instead, these findings support the idea that face recognition ability is related to neural circuits using representations that integrate shape and pigmentation information.

  8. Study on recognition algorithm for paper currency numbers based on neural network

    Science.gov (United States)

    Li, Xiuyan; Liu, Tiegen; Li, Yuanyao; Zhang, Zhongchuan; Deng, Shichao

    2008-12-01

    Based on the unique characteristic, the paper currency numbers can be put into record and the automatic identification equipment for paper currency numbers is supplied to currency circulation market in order to provide convenience for financial sectors to trace the fiduciary circulation socially and provide effective supervision on paper currency. Simultaneously it is favorable for identifying forged notes, blacklisting the forged notes numbers and solving the major social problems, such as armor cash carrier robbery, money laundering. For the purpose of recognizing the paper currency numbers, a recognition algorithm based on neural network is presented in the paper. Number lines in original paper currency images can be draw out through image processing, such as image de-noising, skew correction, segmentation, and image normalization. According to the different characteristics between digits and letters in serial number, two kinds of classifiers are designed. With the characteristics of associative memory, optimization-compute and rapid convergence, the Discrete Hopfield Neural Network (DHNN) is utilized to recognize the letters; with the characteristics of simple structure, quick learning and global optimum, the Radial-Basis Function Neural Network (RBFNN) is adopted to identify the digits. Then the final recognition results are obtained by combining the two kinds of recognition results in regular sequence. Through the simulation tests, it is confirmed by simulation results that the recognition algorithm of combination of two kinds of recognition methods has such advantages as high recognition rate and faster recognition simultaneously, which is worthy of broad application prospect.

  9. Dynamic detection model and its application for perimeter security, intruder detection, and automated target recognition

    Science.gov (United States)

    Koltunov, Joseph; Koltunov, Alexander

    2003-09-01

    Under unsteady weather conditions (gusty wind and partial cloudiness), the pixel intensities measured by infrared or optical imaging sensors may change considerably within even minutes. This makes a principal obstacle to automated target detection and recognition in real, outdoor settings. Currently existing automated recognition algorithms require strong similarity between the weather conditions of training and recognition. Empirical attempts to normalize image intensities do not lead to reliable detection in practice (e.g. for scenes with a complex relief). Also if the weather is relatively stable (weak wind, rare clouds), as short as 15-20 minutes delay between the training survey and the recognition survey may badly affect target recognition or detection, unless the targets are well separable from background. Thermal IR technologies based on invariants such as emissivity and thermal inertia are expensive and ineffective in making the recognition automated. Our approach to overcoming the problem is to take advantage of multitemporal prior surveying. It exploits the fact, that any new infrared or optical image of a scene can be accurately predicted based on sufficiently many scene images acquired previously. This removes the above severe constraints to variability of the weather conditions, whereas neither meteorological measurement nor radiometric calibration of the sensor are required. The present paper further generalizes the approach and addresses several points that are important for putting the ideas in practice. Two experimental examples: intruder detection and recognition of a suspicious target illustrate the potential of our method.

  10. Combinatorial Maps with Normalized Knot

    CERN Document Server

    Zeps, Dainis

    2010-01-01

    We consider combinatorial maps with fixed combinatorial knot numbered with augmenting numeration called normalized knot. We show that knot's normalization doesn't affect combinatorial map what concerns its generality. Knot's normalization leads to more concise numeration of corners in maps, e.g., odd or even corners allow easy to follow distinguished cycles in map caused by the fixation of the knot. Knot's normalization may be applied to edge structuring knot too. If both are normalized then one is fully and other partially normalized mutually.

  11. ANFIS Based Methodology for Sign Language Recognition and Translating to Number in Kannada Language

    Directory of Open Access Journals (Sweden)

    Ramesh Mahadev kagalkar

    2017-03-01

    Full Text Available In the world of signing and gestures, lots of analysis work has been done over the past three decades. This has led to a gradual transition from isolated to continuous, and static to dynamic gesture recognition for operations on a restricted vocabulary. In gift state of affairs, human machine interactive systems facilitate communication between the deaf, and hearing impaired in universe things. So as to boost the accuracy of recognition, several researchers have deployed strategies like HMM, Artificial Neural Networks, and Kinect platform. Effective algorithms for segmentation, classification, pattern matching and recognition have evolved. The most purpose of this paper is to investigate these strategies and to effectively compare them, which can alter the reader to succeed in associate in nursing optimum resolution. This creates each, challenges and opportunities for signing recognition connected analysis. Normal 0 false false false DE JA X-NONE

  12. Is there a recognition memory deficit in Parkinson's disease? Evidence from estimates of recollection and familiarity.

    Science.gov (United States)

    Weiermann, Brigitte; Stephan, Marianne A; Kaelin-Lang, Alain; Meier, Beat

    2010-03-01

    There is conflicting evidence whether Parkinson's disease (PD) is associated with impaired recognition memory and which of its underlying processes, namely recollection and familiarity, is more affected by the disease. The present study explored the contribution of recollection and familiarity to verbal recognition memory performance in 14 nondemented PD patients and a healthy control group with two different methods: (i) the word-frequency mirror effect, and (ii) Remember/Know judgments. Overall, recognition memory of patients was intact. The word-frequency mirror effect was observed both in patients and controls: Hit rates were higher and false alarm rates were lower for low-frequency compared to high-frequency words. However, Remember/Know judgments indicated normal recollection, but impaired familiarity. Our findings suggest that mild to moderate PD patients are selectively impaired at familiarity whereas recollection and overall recognition memory are intact.

  13. Deep learning and non-negative matrix factorization in recognition of mammograms

    Science.gov (United States)

    Swiderski, Bartosz; Kurek, Jaroslaw; Osowski, Stanislaw; Kruk, Michal; Barhoumi, Walid

    2017-02-01

    This paper presents novel approach to the recognition of mammograms. The analyzed mammograms represent the normal and breast cancer (benign and malignant) cases. The solution applies the deep learning technique in image recognition. To obtain increased accuracy of classification the nonnegative matrix factorization and statistical self-similarity of images are applied. The images reconstructed by using these two approaches enrich the data base and thanks to this improve of quality measures of mammogram recognition (increase of accuracy, sensitivity and specificity). The results of numerical experiments performed on large DDSM data base containing more than 10000 mammograms have confirmed good accuracy of class recognition, exceeding the best results reported in the actual publications for this data base.

  14. The effects of reverberant self- and overlap-masking on speech recognition in cochlear implant listeners.

    Science.gov (United States)

    Desmond, Jill M; Collins, Leslie M; Throckmorton, Chandra S

    2014-06-01

    Many cochlear implant (CI) listeners experience decreased speech recognition in reverberant environments [Kokkinakis et al., J. Acoust. Soc. Am. 129(5), 3221-3232 (2011)], which may be caused by a combination of self- and overlap-masking [Bolt and MacDonald, J. Acoust. Soc. Am. 21(6), 577-580 (1949)]. Determining the extent to which these effects decrease speech recognition for CI listeners may influence reverberation mitigation algorithms. This study compared speech recognition with ideal self-masking mitigation, with ideal overlap-masking mitigation, and with no mitigation. Under these conditions, mitigating either self- or overlap-masking resulted in significant improvements in speech recognition for both normal hearing subjects utilizing an acoustic model and for CI listeners using their own devices.

  15. Institutionalizing Normal: Rethinking Composition's Precedence in Normal Schools

    Science.gov (United States)

    Skinnell, Ryan

    2013-01-01

    Composition historians have recently worked to recover histories of composition in normal schools. This essay argues, however, that historians have inadvertently misconstrued the role of normal schools in American education by inaccurately comparing rhetorical education in normal schools to rhetorical education in colleges and universities.…

  16. Character recognition of Japanese newspaper headlines with graphical designs

    Science.gov (United States)

    Sawaki, Minako; Hagita, Norihiro

    1996-03-01

    Graphical designs are often used in Japanese newspaper headlines to indicate hot articles. However, conventional OCR software seldom recognizes characters in such headlines because of the difficulty of removing the designs. This paper proposes a method that recognizes these characters without needing removal of the graphical designs. First, the number of text-line regions and the averaged character heights are roughly extracted from the local distribution of the black and white runs observed in a rectangular window while the window is shifted pixel- by-pixel along the direction of the text-line. Next, normalized text-line regions are yielded by normalizing their heights to the height of binary reference patterns in a dictionary. Next, displacement matching is applied to the normalized text-line region for character recognition. A square window at each position is matched against binary reference patterns while being shifted pixel-by-pixel along the direction of the text-line. The complementary similarity measure, which is robust against graphical designs, is used as a discriminant function. When the maximum similarity value at each position exceeds the threshold, which is automatically determined from the degree of degradation in the square window, the character category of this similarity value is specified as a recognized category. Experimental results for fifty Japanese newspaper headlines show that the method achieves recognition rates of over 90%, much higher than a conventional method (17%).

  17. Normal and pathological altruism.

    Science.gov (United States)

    Seelig, B J; Rosof, L S

    2001-01-01

    The psychoanalytic literature on altruism is sparse, although much has been written on this topic from a sociobiological perspective. Freud (1917) first described the concept in "Libido Theory and Narcissism." In 1946 Anna Freud coined the term "altruistic surrender" to describe the psychodynamics of altruistic behavior in a group of inhibited individuals who were neurotically driven to do good for others. The usefulness and clinical applicability of this formulation, in conjunction with the frequent coexistence of masochism and altruism, encouraged psychoanalysts to regard all forms of altruism as having masochistic underpinnings. Since then, there has been a conflation of the two concepts in much of the analytic literature. This paper reexamines the psychoanalytic understanding of altruism and proposes an expansion of the concept to include a normal form. Five types of altruism are described: protoaltruism, generative altruism, conflicted altruism, pseudoaltruism, and psychotic altruism. Protoaltruism has biological roots and can be observed in animals. In humans, protoaltruism includes maternal and paternal nurturing and protectiveness. Generative altruism is the nonconflictual pleasure in fostering the success and/or welfare of another. Conflicted altruism is generative altruism that is drawn into conflict, but in which the pleasure and satisfaction of another (a proxy) is actually enjoyed. Pseudoaltruism originates in conflict and serves as a defensive cloak for underlying sadomasochism. Psychotic altruism is defined as the sometimes bizarre forms of caretaking behavior and associated self-denial seen in psychotic individuals, and often based on delusion. We consider Anna Freud's altruistic surrender to combine features of both conflict-laden altruism and pseudoaltruism. Two clinical illustrations are discussed.

  18. An Efficient Face Recognition System Based On the Hybridization of Pose Invariant and Illumination Process

    Directory of Open Access Journals (Sweden)

    S. Muruganantham

    2012-07-01

    Full Text Available In the previous decade, one of the most effectual applications of image analysis and indulgent that attracted significant consideration is the human face recognition. One of the diverse techniques used for identifying an individual is the Face recognition. Normally the image variations for the reason that of the change in face identity are less than the variations between the images of the same face under different illumination and viewing angle. Among several factors that manipulate face recognition, illumination and pose are the two major challenges. Pose and illumination variations harshly affect the performance of face recognition. Considerably less effort has been taken to deal with the problem of mutual variations of pose and illumination in face recognition, while several algorithms have been proposed for face recognition from fixed points. In this paper we intend a face recognition method that is forceful to pose and illumination variations. We first put forward a simple pose estimation method based on 2D images, which uses a proper classification rule and image representation to classify a pose of a face image. After that, the image can be assigned to a pose class by a classification rule in a low-dimensional subspace constructed by a feature extraction method. We offer a shadow compensation method that compensates for illumination variation in a face image so that the image can be predictable by a face recognition system designed for images under normal illumination condition. Starting the accomplishment result, it is obvious that our projected technique based on the hybridization system recognizes the face images effectively.

  19. A review on radio based activity recognition

    Directory of Open Access Journals (Sweden)

    Shuangquan Wang

    2015-02-01

    Full Text Available Recognizing human activities in their daily living enables the development and widely usage of human-centric applications, such as health monitoring, assisted living, etc. Traditional activity recognition methods often rely on physical sensors (camera, accelerometer, gyroscope, etc. to continuously collect sensor readings, and utilize pattern recognition algorithms to identify user׳s activities at an aggregator. Though traditional activity recognition methods have been demonstrated to be effective in previous work, they raise some concerns such as privacy, energy consumption and deployment cost. In recent years, a new activity recognition approach, which takes advantage of body attenuation and/or channel fading of wireless radio, has been proposed. Compared with traditional activity recognition methods, radio based methods utilize wireless transceivers in environments as infrastructure, exploit radio communication characters to achieve high recognition accuracy, reduce energy cost and preserve user׳s privacy. In this paper, we divide radio based methods into four categories: ZigBee radio based activity recognition, WiFi radio based activity recognition, RFID radio based activity recognition, and other radio based activity recognition. Some existing work in each category is introduced and reviewed in detail. Then, we compare some representative methods to show their advantages and disadvantages. At last, we point out some future research directions of this new research topic.

  20. Surface normals and barycentric coordinates

    Directory of Open Access Journals (Sweden)

    Mullineux Glen

    1996-01-01

    Full Text Available The normal to a triangular parametric surface is investigated where the parameters used are barycentric coordinates. Formulae for the normal are obtained for non-rational and rational surfaces.

  1. Improving the Recognition of Heart Murmur

    Directory of Open Access Journals (Sweden)

    Magd Ahmed Kotb

    2016-07-01

    Full Text Available Diagnosis of congenital cardiac defects is challenging, with some being diagnosed during pregnancy while others are diagnosed after birth or later on during childhood. Prompt diagnosis allows early intervention and best prognosis. Contemporary diagnosis relies upon the history, clinical examination, pulse oximetery, chest X-ray, electrocardiogram (ECG, echocardiography (ECHO, computed tomography (CT and cardiac catheterization. These diagnostic modalities reliable upon recording electrical activity or sound waves or upon radiation. Yet, congenital heart diseases are still liable to misdiagnosis because of level of operator expertise and other multiple factors. In an attempt to minimize effect of operator expertise this paper built a classification model for heart murmur recognition using Hidden Markov Model (HMM. This paper used Mel Frequency Cepestral coefficient (MFCC as a feature and 13 MFCC coefficients. The machine learning model built by studying 1069 different heart sounds covering normal heart sounds, ventricular septal defect (VSD, mitral regurgitation (MR, aortic stenosis (AS, aortic regurgitation (AR, patent ductus arteriosus (PDA, pulmonary regurgitation (PR, and pulmonary stenosis (PS. MFCC feature used to extract feature matrix for each type of heart sounds after separation according to amplitude threshold. The frequency of normal heart sound (range= 1Hz to 139Hz was specific without overlap with any of the studied defects (ranged= 156-556Hz. The frequency ranges for each of these defects was typical without overlap according to examined heart area (aortic, pulmonary, tricuspid and mitral area. The overall correct classification rate (CCR using this model was 96% and sensitivity 98%. This model has great potential for prompt screening and specific defect detection. Effect of cardiac contractility, cardiomegaly or cardiac electrical activity on this novel detection system needs to be verified in future works.

  2. A comparison of 1D and 2D LSTM architectures for the recognition of handwritten Arabic

    Science.gov (United States)

    Yousefi, Mohammad Reza; Soheili, Mohammad Reza; Breuel, Thomas M.; Stricker, Didier

    2015-01-01

    In this paper, we present an Arabic handwriting recognition method based on recurrent neural network. We use the Long Short Term Memory (LSTM) architecture, that have proven successful in different printed and handwritten OCR tasks. Applications of LSTM for handwriting recognition employ the two-dimensional architecture to deal with the variations in both vertical and horizontal axis. However, we show that using a simple pre-processing step that normalizes the position and baseline of letters, we can make use of 1D LSTM, which is faster in learning and convergence, and yet achieve superior performance. In a series of experiments on IFN/ENIT database for Arabic handwriting recognition, we demonstrate that our proposed pipeline can outperform 2D LSTM networks. Furthermore, we provide comparisons with 1D LSTM networks trained with manually crafted features to show that the automatically learned features in a globally trained 1D LSTM network with our normalization step can even outperform such systems.

  3. Toddlers' recognition of noise-vocoded speech.

    Science.gov (United States)

    Newman, Rochelle; Chatterjee, Monita

    2013-01-01

    Despite their remarkable clinical success, cochlear-implant listeners today still receive spectrally degraded information. Much research has examined normally hearing adult listeners' ability to interpret spectrally degraded signals, primarily using noise-vocoded speech to simulate cochlear implant processing. Far less research has explored infants' and toddlers' ability to interpret spectrally degraded signals, despite the fact that children in this age range are frequently implanted. This study examines 27-month-old typically developing toddlers' recognition of noise-vocoded speech in a language-guided looking study. Children saw two images on each trial and heard a voice instructing them to look at one item ("Find the cat!"). Full-spectrum sentences or their noise-vocoded versions were presented with varying numbers of spectral channels. Toddlers showed equivalent proportions of looking to the target object with full-speech and 24- or 8-channel noise-vocoded speech; they failed to look appropriately with 2-channel noise-vocoded speech and showed variable performance with 4-channel noise-vocoded speech. Despite accurate looking performance for speech with at least eight channels, children were slower to respond appropriately as the number of channels decreased. These results indicate that 2-yr-olds have developed the ability to interpret vocoded speech, even without practice, but that doing so requires additional processing. These findings have important implications for pediatric cochlear implantation.

  4. Short proofs of strong normalization

    OpenAIRE

    Wojdyga, Aleksander

    2008-01-01

    This paper presents simple, syntactic strong normalization proofs for the simply-typed lambda-calculus and the polymorphic lambda-calculus (system F) with the full set of logical connectives, and all the permutative reductions. The normalization proofs use translations of terms and types to systems, for which strong normalization property is known.

  5. Material recognition by using a tagged {sup 252}Cf source

    Energy Technology Data Exchange (ETDEWEB)

    Viesti, G. [Dipartimento di Fisica dell Universita di Padova, Via Marzolo 8, I-35131 Padova (Italy); INFN Sezione di Padova, Via Marzolo 8, I-35131 Padova (Italy)], E-mail: viesti@pd.infn.it; Cossutta, L. [Dipartimento di Fisica dell' Universita di Padova, Via Marzolo 8, I-35131 Padova (Italy); Fabris, D. [INFN Sezione di Padova, Via Marzolo 8, I-35131 Padova (Italy); Lunardon, M.; Moretto, S. [Dipartimento di Fisica dell Universita di Padova, Via Marzolo 8, I-35131 Padova (Italy); INFN Sezione di Padova, Via Marzolo 8, I-35131 Padova (Italy); Nebbia, G.; Pesente, S. [INFN Sezione di Padova, Via Marzolo 8, I-35131 Padova (Italy); Pino, F.; Sajo-Bohus, L. [Universidad Simon-Bolivar, Laboratorio Fisica Nuclear, Apartado 8900, 1080 A. Caracas (Venezuela, Bolivarian Republic of)

    2008-08-11

    Material recognition by measuring simultaneously the transmission of neutron and gamma ray produced by a {sup 252}Cf source has been studied, determining the average atomic number resolving power. In addition, it is demonstrated the possibility to derive direct signatures able to identify light elements (C, N, O) using the measured transmission versus neutron time-of-flight. This allows one to determine the relevant elemental ratios (C/O and C/N) normally used to identify threat organic materials such as explosives and drugs.

  6. On speech recognition during anaesthesia

    DEFF Research Database (Denmark)

    Alapetite, Alexandre

    2007-01-01

    This PhD thesis in human-computer interfaces (informatics) studies the case of the anaesthesia record used during medical operations and the possibility to supplement it with speech recognition facilities. Problems and limitations have been identified with the traditional paper-based anaesthesia...... record, but also with newer electronic versions typically based on touch-screen and keyboard, in particular ergonomic issues and the fact that anaesthesiologists tend to postpone the registration of the medications and other events during busy periods of anaesthesia, which in turn may lead to gaps...

  7. Action Recognition using Motion Primitives

    DEFF Research Database (Denmark)

    Moeslund, Thomas B.; Fihl, Preben; Holte, Michael Boelstoft

    The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent...... the actions as a sequence of temporal isolated instances, denoted primitives. These primitives are each defined by four features extracted from motion images. The primitives are recognized in each frame based on a trained classifier resulting in a sequence of primitives. From this sequence we recognize...

  8. Face Processing: Models For Recognition

    Science.gov (United States)

    Turk, Matthew A.; Pentland, Alexander P.

    1990-03-01

    The human ability to process faces is remarkable. We can identify perhaps thousands of faces learned throughout our lifetime and read facial expression to understand such subtle qualities as emotion. These skills are quite robust, despite sometimes large changes in the visual stimulus due to expression, aging, and distractions such as glasses or changes in hairstyle or facial hair. Computers which model and recognize faces will be useful in a variety of applications, including criminal identification, human-computer interface, and animation. We discuss models for representing faces and their applicability to the task of recognition, and present techniques for identifying faces and detecting eye blinks.

  9. COMMERCIAL FUND, RECOGNITION AND ASSESSMENT

    Directory of Open Access Journals (Sweden)

    VIOREL TRIF

    2010-01-01

    Full Text Available The importance of the immaterial investments within companies nowadays urges the specialists in accounting to find the ways to present more in the elements. In their studies researchers face the controversy reinvestments, as an asset in the balance sheet or an expense in the profit or loss account. The main goal of this paper is to analyze the difficulties in commercial fund. In the first part we will analyze various definitions of the problems concerning the commercial fund’s recognition and assessment. The paper also suggests that investments are really social and economic problems.

  10. Introduction to radar target recognition

    CERN Document Server

    Tait, P

    2006-01-01

    This new text provides an overview of the radar target recognition process and covers the key techniques being developed for operational systems. It is based on the fundamental scientific principles of high resolution radar, and explains how the techniques can be used in real systems, taking into account the characteristics of practical radar system designs and component limitations. It also addresses operational aspects, such as how high resolution modes would fit in with other functions such as detection and tracking. Mathematics is kept to a minimum and the complex techniques and issues are

  11. Face Recognition in Uncontrolled Environment

    Directory of Open Access Journals (Sweden)

    Radhey Shyam

    2016-08-01

    Full Text Available This paper presents a novel method of facial image representation for face recognition in uncontrolled environment. It is named as augmented local binary patterns (A-LBP that works on both, uniform and non-uniform patterns. It replaces the central non-uniform pattern with a majority value of the neighbouring uniform patterns obtained after processing all neighbouring non-uniform patterns. These patterns are finally combined with the neighbouring uniform patterns, in order to extract discriminatory information from the local descriptors. The experimental results indicate the vitality of the proposed method on particular face datasets, where the images are prone to extreme variations of illumination.

  12. Structure of the C-type lectin carbohydrate recognition domain of human tetranectin

    DEFF Research Database (Denmark)

    Kastrup, J S; Nielsen, B B; Rasmussen, H

    1998-01-01

    of certain human carcinomas, whereas none or little is present in the corresponding normal tissue. The crystal structure of full-length trimeric TN (2.8 A resolution) has recently been published [Nielsen et al. (1997). FEBS Lett. 412, 388-396]. The crystal structure of the carbohydrate recognition domain...

  13. Facial Expression Recognition: Can Preschoolers with Cochlear Implants and Hearing Aids Catch It?

    Science.gov (United States)

    Wang, Yifang; Su, Yanjie; Fang, Ping; Zhou, Qingxia

    2011-01-01

    Tager-Flusberg and Sullivan (2000) presented a cognitive model of theory of mind (ToM), in which they thought ToM included two components--a social-perceptual component and a social-cognitive component. Facial expression recognition (FER) is an ability tapping the social-perceptual component. Previous findings suggested that normal hearing…

  14. The Effects of Auditory-Visual Vowel Identification Training on Speech Recognition under Difficult Listening Conditions

    Science.gov (United States)

    Richie, Carolyn; Kewley-Port, Diane

    2008-01-01

    Purpose: The effective use of visual cues to speech provides benefit for adults with normal hearing in noisy environments and for adults with hearing loss in everyday communication. The purpose of this study was to examine the effects of a computer-based, auditory-visual vowel identification training program on sentence recognition under difficult…

  15. Facial Expression Recognition: Can Preschoolers with Cochlear Implants and Hearing Aids Catch It?

    Science.gov (United States)

    Wang, Yifang; Su, Yanjie; Fang, Ping; Zhou, Qingxia

    2011-01-01

    Tager-Flusberg and Sullivan (2000) presented a cognitive model of theory of mind (ToM), in which they thought ToM included two components--a social-perceptual component and a social-cognitive component. Facial expression recognition (FER) is an ability tapping the social-perceptual component. Previous findings suggested that normal hearing…

  16. 3D Interest Point Detection using Local Surface Characteristics with Application in Action Recognition

    DEFF Research Database (Denmark)

    Holte, Michael Boelstoft

    2014-01-01

    . The proposed Difference-of-Normals (DoN) 3D IP detector operates on the surface mesh, and evaluates the surface structure (curvature) locally (per vertex) in the mesh data. We present an exam- ple of application in action recognition from a sequence of 3-dimensional geometrical data, where local 3D motion de...

  17. Depth Value Pre-Processing for Accurate Transfer Learning Based RGB-D Object Recognition

    DEFF Research Database (Denmark)

    Aakerberg, Andreas; Nasrollahi, Kamal

    2017-01-01

    of an existing deeplearning based RGB-D object recognition model, namely the FusionNet proposed by Eitel et al. First, we showthat encoding the depth values as colorized surface normals is beneficial, when the model is initialized withweights learned from training on ImageNet data. Additionally, we show...

  18. Differential adaptation of Candida albicans in vivo modulates immune recognition by dectin-1

    NARCIS (Netherlands)

    Marakalala, M.J.; Vautier, S.; Potrykus, J.; Walker, L.A.; Shepardson, K.M.; Hopke, A.; Mora-Montes, H.M.; Kerrigan, A.; Netea, M.G.; Murray, G.I.; MacCallum, D.M.; Wheeler, R.; Munro, C.A.; Gow, N.A.; Cramer, R.A.; Brown, A.J.; Brown, G.D.

    2013-01-01

    The beta-glucan receptor Dectin-1 is a member of the C-type lectin family and functions as an innate pattern recognition receptor in antifungal immunity. In both mouse and man, Dectin-1 has been found to play an essential role in controlling infections with Candida albicans, a normally commensal fun

  19. Acute cortisol effects on immediate free recall and recognition of nouns depend on stimulus valence

    NARCIS (Netherlands)

    Tops, M.; van der Pompe, G.; Baas, D; Mulder, L.J.M.; Den Boer, J.A.; Meijman, T.F.; Korf, J

    The present study investigated the acute effects of cortisol administration in normal healthy male volunteers on immediate free recall and recognition of pleasant, unpleasant, and neutral nouns using a between-subjects double-blind design. Two hours after cortisol (10 mg) or placebo administration,

  20. OFF-LINE CURSIVE SCRIPT RECOGNITION BASED ON CONTINUOUS DENSITY HMM

    NARCIS (Netherlands)

    Vinciarelli, A.; Luettin, J.

    2004-01-01

    A system for off-line cursive script recognition is presented. A new normalization technique (based on statistical methods) to compensate for the variability of writing style is described. The key problem of segmentation is avoided by applying a sliding window on the handwritten words. A feature vec

  1. Using Regression to Measure Holistic Face Processing Reveals a Strong Link with Face Recognition Ability

    Science.gov (United States)

    DeGutis, Joseph; Wilmer, Jeremy; Mercado, Rogelio J.; Cohan, Sarah

    2013-01-01

    Although holistic processing is thought to underlie normal face recognition ability, widely discrepant reports have recently emerged about this link in an individual differences context. Progress in this domain may have been impeded by the widespread use of subtraction scores, which lack validity due to their contamination with control condition…

  2. Studies of human vision recognition: some improvements

    Science.gov (United States)

    Wu, Bo-Wen; Fang, Yi-Chin; Chang, Lin-Song

    2010-01-01

    This paper proposes a new method to improve human recognition by artificial intelligence, specifically of images without the interference of high frequencies. The human eye is the most delicate optical system. Notwithstanding the dramatic progression of its structure and functions through a long evolution, the capability of visual recognition is not yet close to perfection. This paper is a study, based on the limitations of recognition by the human eye, of image recognition through the application of artificial intelligence. Those aspects which have been explored focus on human eye modeling, including aberration analysis, creative models of the human eye, human vision recognition characteristics and various mathematical models for verification. By using images consisting of four black and white bands and modulation transfer function (MTF) curve evaluation recognition capability on all the studied models, the optimum model most compatible with the physiology of the human eye is found.

  3. Kannada character recognition system using neural network

    Science.gov (United States)

    Kumar, Suresh D. S.; Kamalapuram, Srinivasa K.; Kumar, Ajay B. R.

    2013-03-01

    Handwriting recognition has been one of the active and challenging research areas in the field of pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. As there is no sufficient number of works on Indian language character recognition especially Kannada script among 15 major scripts in India. In this paper an attempt is made to recognize handwritten Kannada characters using Feed Forward neural networks. A handwritten Kannada character is resized into 20x30 Pixel. The resized character is used for training the neural network. Once the training process is completed the same character is given as input to the neural network with different set of neurons in hidden layer and their recognition accuracy rate for different Kannada characters has been calculated and compared. The results show that the proposed system yields good recognition accuracy rates comparable to that of other handwritten character recognition systems.

  4. Machine learning techniques in dialogue act recognition

    Directory of Open Access Journals (Sweden)

    Mark Fišel

    2007-05-01

    Full Text Available This report addresses dialogue acts, their existing applications and techniques of automatically recognizing them, in Estonia as well as elsewhere. Three main applications are described: in dialogue systems to determine the intention of the speaker, in dialogue systems with machine translation to resolve ambiguities in the possible translation variants and in speech recognition to reduce word recognition error rate. Several recognition techniques are described on the surface level: how they work and how they are trained. A summary of the corresponding representation methods is provided for each technique. The paper also includes examples of applying the techniques to dialogue act recognition.The author comes to the conclusion that using the current evaluation metric it is impossible to compare dialogue act recognition techniques when these are applied to different dialogue act tag sets. Dialogue acts remain an open research area, with space and need for developing new recognition techniques and methods of evaluation.

  5. Document recognition serving people with disabilities

    Science.gov (United States)

    Fruchterman, James R.

    2007-01-01

    Document recognition advances have improved the lives of people with print disabilities, by providing accessible documents. This invited paper provides perspectives on the author's career progression from document recognition professional to social entrepreneur applying this technology to help people with disabilities. Starting with initial thoughts about optical character recognition in college, it continues with the creation of accurate omnifont character recognition that did not require training. It was difficult to make a reading machine for the blind in a commercial setting, which led to the creation of a nonprofit social enterprise to deliver these devices around the world. This network of people with disabilities scanning books drove the creation of Bookshare.org, an online library of scanned books. Looking forward, the needs for improved document recognition technology to further lower the barriers to reading are discussed. Document recognition professionals should be proud of the positive impact their work has had on some of society's most disadvantaged communities.

  6. Online recognition of the multiphase flow regime

    Institute of Scientific and Technical Information of China (English)

    BAI BoFeng; ZHANG ShaoJun; ZHAO Liang; ZHANG XiMin; GUO LieJin

    2008-01-01

    The key reasons that the present method cannot be used to solve the industrial multi-phase flow pattern recognition are clarified firstly. The prerequisite to realize the online recognition is proposed and recognition rules for partial flow pattern are obtained based on the massive experimental data. The standard templates for every flow regime feature are calculated with self-organization cluster algorithm. The multi-sensor data fusion method is proposed to realize the online recognition of multiphase flow regime with the pressure and differential pressure signals, which overcomes the severe influence of fluid flow velocity and the oil fraction on the recognition. The online recognition method is tested in the practice, which has less than 10 percent measurement error. The method takes advantages of high confidence, good fault tolerance and less requirement of single sensor performance.

  7. Online recognition of the multiphase flow regime

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The key reasons that the present method cannot be used to solve the industrial multi- phase flow pattern recognition are clarified firstly. The prerequisite to realize the online recognition is proposed and recognition rules for partial flow pattern are obtained based on the massive experimental data. The standard templates for every flow regime feature are calculated with self-organization cluster algorithm. The multi-sensor data fusion method is proposed to realize the online recognition of multiphase flow regime with the pressure and differential pressure signals, which overcomes the severe influence of fluid flow velocity and the oil fraction on the recognition. The online recognition method is tested in the practice, which has less than 10 percent measurement error. The method takes advantages of high confidence, good fault tolerance and less requirement of single sensor performance.

  8. Parameters Optimization of Synergetic Recognition Approach

    Institute of Scientific and Technical Information of China (English)

    GAOJun; DONGHuoming; SHAOJing; ZHAOJing

    2005-01-01

    Synergetic pattern recognition is a novel and effective pattern recognition method, and has some advantages in image recognition. Researches have shown that attention parameters λ and parameters B, C directly influence on the recognition results, but there is no general research theory to control these parameters in the recognition process. We abstractly analyze these parameters in this paper, and purpose a novel parameters optimization method based on simulated annealing algorithm. SA algorithm has good optimization performance and is used to search the global optimized solution of these parameters. Theoretic analysis and experimental results both show that the proposed parameters optimization method is effective, which can fully improve the performance of synergetic recognition approach, and the algorithm realization is simple and fast.

  9. Handwritten digits recognition based on immune network

    Science.gov (United States)

    Li, Yangyang; Wu, Yunhui; Jiao, Lc; Wu, Jianshe

    2011-11-01

    With the development of society, handwritten digits recognition technique has been widely applied to production and daily life. It is a very difficult task to solve these problems in the field of pattern recognition. In this paper, a new method is presented for handwritten digit recognition. The digit samples firstly are processed and features extraction. Based on these features, a novel immune network classification algorithm is designed and implemented to the handwritten digits recognition. The proposed algorithm is developed by Jerne's immune network model for feature selection and KNN method for classification. Its characteristic is the novel network with parallel commutating and learning. The performance of the proposed method is experimented to the handwritten number datasets MNIST and compared with some other recognition algorithms-KNN, ANN and SVM algorithm. The result shows that the novel classification algorithm based on immune network gives promising performance and stable behavior for handwritten digits recognition.

  10. Increasing the discrimination of SAR recognition models

    Science.gov (United States)

    Bhanu, Bir; Jones, Grinnell, III

    2001-08-01

    The focus of this paper is optimizing recognition models for Synthetic Aperture Radar signatures of vehicles to improve the performance of a recognition algorithm under the extended operating conditions of target articulation, occlusion and configuration variants. The recognition models are based on quasi-invariant local features, scattering center locations and magnitudes. The approach determines the similarities and differences among the various vehicle models. Methods to penalize similar features or reward dissimilar features are used to increase the distinguishability of the recognition model instances. Extensive experimental recognition results are presented in terms of confusion matrices and receiver operating characteristic curves to show the improvements in recognition performance for MSTAR vehicle targets with articulation, configuration variants and occlusion.

  11. MEMBRAIN NEURAL NETWORK FOR VISUAL PATTERN RECOGNITION

    Directory of Open Access Journals (Sweden)

    Artur Popko

    2013-06-01

    Full Text Available Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related disciplines. The document describes also MemBrain application environment as a powerful and easy to use neural networks’ editor and simulator supporting ANN.

  12. Face Recognition in Real-world Images

    OpenAIRE

    Fontaine, Xavier; Achanta, Radhakrishna; Süsstrunk, Sabine

    2017-01-01

    Face recognition systems are designed to handle well-aligned images captured under controlled situations. However real-world images present varying orientations, expressions, and illumination conditions. Traditional face recognition algorithms perform poorly on such images. In this paper we present a method for face recognition adapted to real-world conditions that can be trained using very few training examples and is computationally efficient. Our method consists of performing a novel align...

  13. Mathematical symbol hypothesis recognition with rejection option

    OpenAIRE

    Julca-Aguilar, Frank; Hirata, Nina,; Viard-Gaudin, Christian; Mouchère, Harold; Medjkoune, Sofiane

    2014-01-01

    International audience; In the context of handwritten mathematical expressions recognition, a first step consist on grouping strokes (segmentation) to form symbol hypotheses: groups of strokes that might represent a symbol. Then, the symbol recognition step needs to cope with the identification of wrong segmented symbols (false hypotheses). However, previous works on symbol recognition consider only correctly segmented symbols. In this work, we focus on the problem of mathematical symbol reco...

  14. A Bayesian classifier for symbol recognition

    OpenAIRE

    Barrat, Sabine; Tabbone, Salvatore; Nourrissier, Patrick

    2007-01-01

    URL : http://www.buyans.com/POL/UploadedFile/134_9977.pdf; International audience; We present in this paper an original adaptation of Bayesian networks to symbol recognition problem. More precisely, a descriptor combination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor, is presented. In this perspective, we use a simple Bayesian classifier, called naive Bayes. In fact, probabilistic graphical models, more spec...

  15. Automated leukocyte recognition using fuzzy divergence.

    Science.gov (United States)

    Ghosh, Madhumala; Das, Devkumar; Chakraborty, Chandan; Ray, Ajoy K

    2010-10-01

    This paper aims at introducing an automated approach to leukocyte recognition using fuzzy divergence and modified thresholding techniques. The recognition is done through the segmentation of nuclei where Gamma, Gaussian and Cauchy type of fuzzy membership functions are studied for the image pixels. It is in fact found that Cauchy leads better segmentation as compared to others. In addition, image thresholding is modified for better recognition. Results are studied and discussed.

  16. Effects of steep high-frequency hearing loss on speech recognition using temporal fine structure in low-frequency region.

    Science.gov (United States)

    Li, Bei; Hou, Limin; Xu, Li; Wang, Hui; Yang, Guang; Yin, Shankai; Feng, Yanmei

    2015-08-01

    The present study examined the effects of steep high-frequency sensorineural hearing loss (SHF-SNHL) on speech recognition using acoustic temporal fine structure (TFS) in the low-frequency region where the absolute thresholds appeared to be normal. In total, 28 participants with SHF-SNHL were assigned to 3 groups according to the cut-off frequency (1, 2, and 4 kHz, respectively) of their pure-tone absolute thresholds. Fourteen age-matched normal-hearing (NH) individuals were enrolled as controls. For each Mandarin sentence, the acoustic TFS in 10 frequency bands (each 3-ERB wide) was extracted using the Hilbert transform and was further lowpass filtered at 1, 2, and 4 kHz. Speech recognition scores were compared among the NH and 1-, 2-, and 4-kHz SHF-SNHL groups using stimuli with varying bandwidths. Results showed that speech recognition with the same TFS-speech stimulus bandwidth differed significantly in groups and filtering conditions. Sentence recognition in quiet conditions was better than that in noise. Compared with the NH participants, nearly all the SHF-SNHL participants showed significantly poorer sentence recognition within their frequency regions with "normal hearing" (defined clinically by normal absolute thresholds) in both quiet and noisy conditions. These may result from disrupted auditory nerve function in the "normal hearing" low-frequency regions. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. Rank Pooling for Action Recognition.

    Science.gov (United States)

    Fernando, Basura; Gavves, Efstratios; Oramas M, Jose Oramas; Ghodrati, Amir; Tuytelaars, Tinne

    2017-04-01

    We propose a function-based temporal pooling method that captures the latent structure of the video sequence data - e.g., how frame-level features evolve over time in a video. We show how the parameters of a function that has been fit to the video data can serve as a robust new video representation. As a specific example, we learn a pooling function via ranking machines. By learning to rank the frame-level features of a video in chronological order, we obtain a new representation that captures the video-wide temporal dynamics of a video, suitable for action recognition. Other than ranking functions, we explore different parametric models that could also explain the temporal changes in videos. The proposed functional pooling methods, and rank pooling in particular, is easy to interpret and implement, fast to compute and effective in recognizing a wide variety of actions. We evaluate our method on various benchmarks for generic action, fine-grained action and gesture recognition. Results show that rank pooling brings an absolute improvement of 7-10 average pooling baseline. At the same time, rank pooling is compatible with and complementary to several appearance and local motion based methods and features, such as improved trajectories and deep learning features.

  18. Speech recognition from spectral dynamics

    Indian Academy of Sciences (India)

    Hynek Hermansky

    2011-10-01

    Information is carried in changes of a signal. The paper starts with revisiting Dudley’s concept of the carrier nature of speech. It points to its close connection to modulation spectra of speech and argues against short-term spectral envelopes as dominant carriers of the linguistic information in speech. The history of spectral representations of speech is briefly discussed. Some of the history of gradual infusion of the modulation spectrum concept into Automatic recognition of speech (ASR) comes next, pointing to the relationship of modulation spectrum processing to wellaccepted ASR techniques such as dynamic speech features or RelAtive SpecTrAl (RASTA) filtering. Next, the frequency domain perceptual linear prediction technique for deriving autoregressive models of temporal trajectories of spectral power in individual frequency bands is reviewed. Finally, posterior-based features, which allow for straightforward application of modulation frequency domain information, are described. The paper is tutorial in nature, aims at a historical global overview of attempts for using spectral dynamics in machine recognition of speech, and does not always provide enough detail of the described techniques. However, extensive references to earlier work are provided to compensate for the lack of detail in the paper.

  19. Shape Recognition Using A CMAC Based Learning System

    Science.gov (United States)

    Glanz, F. H.; Miller, W. T.

    1988-02-01

    This paper discusses pattern recognition using a learning system which can learn an arbitrary function of the input and which has built-in generalization with the characteristic that similar inputs lead to similar outputs even for untrained inputs. The amount of similarity is controlled by a parameter of the program at compile time. Inputs and/or outputs may be vectors. The system is trained in a way similar to other pattern recognition systems using an LMS rule. Patterns in the input space are not separated by hyperplanes in the way they normally are using adaptive linear elements. As a result, linear separability is not the problem it is when using Perceptron or Adaline type elements. In fact, almost any shape category region is possible, and a region need not be simply connected nor convex. An example is given of geometric shape recognition using as features autoregressive model parameters representing the shape boundaries. These features are approximately independent of translation, rotation, and size of the shape. Results in the form of percent correct on test sets are given for eight different combinations of training and test sets derived from two groups of shapes.

  20. 3D Face Compression and Recognition using Spherical Wavelet Parametrization

    Directory of Open Access Journals (Sweden)

    Rabab M. Ramadan

    2012-09-01

    Full Text Available In this research an innovative fully automated 3D face compression and recognition system is presented. Several novelties are introduced to make the system performance robust and efficient. These novelties include: First, an automatic pose correction and normalization process by using curvature analysis for nose tip detection and iterative closest point (ICP image registration. Second, the use of spherical based wavelet coefficients for efficient representation of the 3D face. The spherical wavelet transformation is used to decompose the face image into multi-resolution sub images characterizing the underlying functions in a local fashion in both spacial and frequency domains. Two representation features based on spherical wavelet parameterization of the face image were proposed for the 3D face compression and recognition. Principle component analysis (PCA is used to project to a low resolution sub-band. To evaluate the performance of the proposed approach, experiments were performed on the GAVAB face database. Experimental results show that the spherical wavelet coefficients yield excellent compression capabilities with minimal set of features. Haar wavelet coefficients extracted from the face geometry image was found to generate good recognition results that outperform other methods working on the GAVAB database.