WorldWideScience

Sample records for chemically-mediated roostmate recognition

  1. Ignorant hooded crows follow knowledgeable roost-mates to food: support for the information centre hypothesis.

    OpenAIRE

    Sonerud, G. A.; Smedshaug, C. A.; Bråthen, O.

    2001-01-01

    Communal roosting in birds may function to enhance foraging efficiency as explained by the information centre hypothesis, which predicts that successful foragers return from the roost to the rewarding food patch and that birds ignorant of this food follow knowledgeable roost-mates. We tested these predictions by exposing 34 radio-tagged, free-ranging, flock-living hooded crows (Corvus corone cornix) to a novel experimental set-up mimicking a superfluous food patch with maximum temporal and sp...

  2. Chemical Mediators and the Resolution of Airway Inflammation

    OpenAIRE

    Carlo, Troy; Levy, Bruce D.

    2008-01-01

    Asthma pathobiology is remarkable for chronic airway inflammation that fails to spontaneously resolve. No curative therapy is currently available. A growing body of evidence indicates that, in health, inflammation resolution is an active process orchestrated by specific chemical mediators that are elaborated to restore tissue homeostasis. Activated cell membranes release polyunsaturated fatty acids from phospholipids for enzymatic conversion to biologically active mediators with profound regu...

  3. Face Recognition

    OpenAIRE

    Haugen, Liv Merete; Olavsbråten, Inge

    2007-01-01

    Machine based face recognition has been a popular research area for several years, and has numerous applications. This technology has now reached a point where there already exists good algorithms for recognition for standardized still images - which have little variation in e.g. lighting, facial expression and pose. We are however in lack of good algorithms that are able to do recognition from live video. The low quality of most surveillance cameras, together with non-standardized imaging c...

  4. 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...

  5. Speech recognition based on pattern recognition techniques

    Science.gov (United States)

    Rabiner, Lawrence R.

    1990-05-01

    Algorithms for speech recognition can be characterized broadly as pattern recognition approaches and acoustic phonetic approaches. To date, the greatest degree of success in speech recognition has been obtained using pattern recognition paradigms. The use of pattern recognition techniques were applied to the problems of isolated word (or discrete utterance) recognition, connected word recognition, and continuous speech recognition. It is shown that understanding (and consequently the resulting recognizer performance) is best to the simplest recognition tasks and is considerably less well developed for large scale recognition systems.

  6. Customer recognition and competition

    OpenAIRE

    Shy, Oz; Stenbacka , Rune

    2011-01-01

    We introduce three types of consumer recognition: identity recognition, asymmetric preference recognition, and symmetric preference recognition. We characterize price equilibria and compare profits, consumer surplus, and total welfare. Asymmetric preference recognition enhances profits compared with identity recognition, but firms have no incentive to exchange information regarding customer-specific preferences (symmetric preference recognition). Consumers would benefit from a policy panning ...

  7. 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.

  8. Recognition intent and visual word recognition.

    Science.gov (United States)

    Wang, Man-Ying; Ching, Chi-Le

    2009-03-01

    This study adopted a change detection task to investigate whether and how recognition intent affects the construction of orthographic representation in visual word recognition. Chinese readers (Experiment 1-1) and nonreaders (Experiment 1-2) detected color changes in radical components of Chinese characters. Explicit recognition demand was imposed in Experiment 2 by an additional recognition task. When the recognition was implicit, a bias favoring the radical location informative of character identity was found in Chinese readers (Experiment 1-1), but not nonreaders (Experiment 1-2). With explicit recognition demands, the effect of radical location interacted with radical function and word frequency (Experiment 2). An estimate of identification performance under implicit recognition was derived in Experiment 3. These findings reflect the joint influence of recognition intent and orthographic regularity in shaping readers' orthographic representation. The implication for the role of visual attention in word recognition was also discussed. PMID:19036609

  9. Speaker recognition by voice

    OpenAIRE

    Kamarauskas, Juozas

    2009-01-01

    Questions of speaker’s recognition by voice are investigated in this dissertation. Speaker recognition systems, their evolution, problems of recognition, systems of features, questions of speaker modeling and matching used in text-independent and text-dependent speaker recognition are considered too. The text-independent speaker recognition system has been developed during this work. The Gaussian mixture model approach was used for speaker modeling and pattern matching. The automatic m...

  10. 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.

  11. Recognition of Problem Drinkers

    OpenAIRE

    Cornel, Michiel; van Zutphen, Wim M.

    1989-01-01

    General practitioners often see patients with problems related to drinking behaviour, but recognize only a small proportion of these problem drinkers. The authors discuss some mechanisms of this non-recognition phenomenon and suggest ways to enhance early recognition.

  12. Speech recognition and understanding

    Energy Technology Data Exchange (ETDEWEB)

    Vintsyuk, T.K.

    1983-05-01

    This article discusses the automatic processing of speech signals with the aim of finding a sequence of works (speech recognition) or a concept (speech understanding) being transmitted by the speech signal. The goal of the research is to develop an automatic typewriter that will automatically edit and type text under voice control. A dynamic programming method is proposed in which all possible class signals are stored, after which the presented signal is compared to all the stored signals during the recognition phase. Topics considered include element-by-element recognition of words of speech, learning speech recognition, phoneme-by-phoneme speech recognition, the recognition of connected speech, understanding connected speech, and prospects for designing speech recognition and understanding systems. An application of the composition dynamic programming method for the solution of basic problems in the recognition and understanding of speech is presented.

  13. RECOGNITION OF CONTESTED STATES

    OpenAIRE

    Ali, Nanna; Ben-Ahmed, Michele; Bom, Thomas Falk; Ching, Rune Kieran; Steffensen, Lars Schmidt; Funningsstovu, Janus Hanusarson í

    2012-01-01

    Contested states have existed in many decades and been on the political agenda worldwide. A small group of entities in the world are aspiring for recognition and independence, while some entities gained recognition relatively smoothly. This project accounts for UN’s recognition process and investigates entities prospects of influencing the process for obtaining recognition. Based on theories of liberalism and constructivism as well as the opposing theories of international relations, re...

  14. Recognition and Teleportation

    OpenAIRE

    Fichtner, K. -H.; Freudenberg, W.; Ohya, M.

    2004-01-01

    We study a possible function of brain, in particular, we try to describe several aspects of the process of recognition. In order to understand the fundamental parts of the recognition process, the quantum teleportation scheme seems to be useful. We consider a channel expression of the teleportation process that serves for a simplified description of the recognition process in brain.

  15. Phloroglucinols inhibit chemical mediators and xanthine oxidase, and protect cisplatin-induced cell death by reducing reactive oxygen species in normal human urothelial and bladder cancer cells.

    Science.gov (United States)

    Lin, Kai-Wei; Huang, A-Mei; Tu, Huang-Yao; Weng, Jing-Ru; Hour, Tzyh-Chyuan; Wei, Bai-Luh; Yang, Shyh-Chyun; Wang, Jih-Pyang; Pu, Yeong-Shiau; Lin, Chun-Nan

    2009-10-14

    Phloroglucinols, garcinielliptones HA-HE (1-5), and C (6) were studied in vitro for their inhibitory effects on chemical mediators released from mast cells, neutrophils, and macrophages. Compound 6 revealed significant inhibitory effect on release of lysozyme from rat neutrophils stimulated with formyl-Met-Leu-Phe (fMLP)/cytochalasin B (CB). Compounds 3, 4, and 6 showed significant inhibitory effects on superoxide anion generation in rat neutrophils stimulated with (fMLP)/(CB), while compounds 1 and 5 revealed inhibitory effects on tumor necrosis factor-alpha (TNF-alpha) formation in macrophages stimulated with lipopolysaccharide (LPS). Compounds 1 and 3-6 showed inhibitory effects on xanthine oxidase (XO) and could inhibit the DNA breakage caused by O2(-*). Treatment of NTUB1 with 2 to 60 microM compound 3 and 5 microM cisplatin and SV-HUC1 with 9 to 60 microM 3 and 5 microM cisplatin, respectively, resulted in an increase of viability of cells. These results indicated that compounds 1 and 3-6 showed anti-inflammatory effects and antioxidant activities. Compound 3 mediates through the suppression of XO activity and reduction of reactive oxygen species (ROS), and protection of subsequent cell death. PMID:19754119

  16. Optical Pattern Recognition

    Science.gov (United States)

    Yu, Francis T. S.; Jutamulia, Suganda

    2008-10-01

    Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

  17. 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.

  18. ANATOMY ON PATTERN RECOGNITION

    OpenAIRE

    MAYANK PARASHER; SHRUTI SHARMA; A .K. SHARMA,; J.P.Gupta

    2011-01-01

    Pattern Recognition is the science of recognizing patterns by machines. This is very wide research area as of today, because every newresearch tries to make machine as intelligent as human for recognizing patterns. Pattern recognition is an active research and an importanttrait of ‘artificial intelligence’. This review paper introduces pattern recognition, its fundamental definitions, and provides understanding of related research work. This paper presents different types of algorithms, their...

  19. Context dependent speech recognition

    OpenAIRE

    Andersson, Sebastian

    2006-01-01

    Poor speech recognition is a problem when developing spoken dialogue systems, but several studies has showed that speech recognition can be improved by post-processing of recognition output that use the dialogue context, acoustic properties of a user utterance and other available resources to train a statistical model to use as a filter between the speech recogniser and dialogue manager. In this thesis a corpus of logged interactions between users and a dialogue system was used...

  20. 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,

  1. Paradigms in object recognition

    International Nuclear Information System (INIS)

    A broad range of approaches has been proposed and applied for the complex and rather difficult task of object recognition that involves the determination of object characteristics and object classification into one of many a priori object types. Our paper revises briefly the three main different paradigms in pattern recognition, namely Bayesian statistics, neural networks, and expert systems. (author)

  2. Recognition as care

    DEFF Research Database (Denmark)

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

    2014-01-01

    -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...

  3. 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

  4. 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

  5. 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.

  6. 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

  7. Work and Recognition

    DEFF Research Database (Denmark)

    Willig, Rasmus

    2004-01-01

    -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......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...... 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...

  8. 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....

  9. Towards Open World Recognition

    OpenAIRE

    Bendale, Abhijit; Boult, Terrance

    2014-01-01

    With the of advent rich classification models and high computational power visual recognition systems have found many operational applications. Recognition in the real world poses multiple challenges that are not apparent in controlled lab environments. The datasets are dynamic and novel categories must be continuously detected and then added. At prediction time, a trained system has to deal with myriad unseen categories. Operational systems require minimum down time, even to learn. To handle...

  10. Automatic Licenses Plate Recognition

    OpenAIRE

    Ronak P Patel; Narendra M Patel; Keyur Brahmbhatt

    2013-01-01

    This paper describes the Smart Vehicle Screening System, which can be installed into a tollboothfor automated recognition of vehicle license plate information using a photograph of a vehicle. An automatedsystem could then be implemented to control the payment of fees, parking areas, highways, bridges ortunnels, etc. This paper contains new algorithm for recognition number plate using Morphological operation,Thresholding operation, Edge detection, Bounding box analysis for number plate extract...

  11. Human Emotion Recognition System

    OpenAIRE

    Dilbag Singh

    2012-01-01

    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 hav...

  12. Fingerprint Recognition System

    OpenAIRE

    Bhawna Negi; Varun Sharma

    2012-01-01

    The popular Biometric used to authenticate a person is Fingerprint which is unique and permanent throughout a person’s life. A minutia matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. In this paper we projected Fingerprint Recognition using Minutia Score Matching method (FRMSM). For Fingerprint thinning, the Block Filter is used, which scans the image at the boundary to preserves the quality of the image and extract the minutiae ...

  13. Android object recognition framework

    OpenAIRE

    Karlsen, Mats-Gøran

    2012-01-01

    This thesis is a continuation of the author’s specialization project where the ultimate goal is to build an object recognition framework suitable for mobile devices in real world environments, where control over parameters such as illumination, distance, noise and availability of consistent network architectures are limited. Based on shortcomings related to object recognition performance and architectural issues the author’s goal was to increase the flexibility, usability and perfor...

  14. 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...

  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. Probabilistic Open Set Recognition

    Science.gov (United States)

    Jain, Lalit Prithviraj

    Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary

  17. 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

  18. Wavelets and Face Recognition

    OpenAIRE

    Dai, Dao-Qing; Yan, Hong

    2007-01-01

    Wavelets have been successfully used in image processing. Their ability to capture localized spatial-frequency information of image motivates their use for feature extraction. We give an overview of using wavelets in the face recognition technology. Due to limit of space the use of Gabor wavelets is not covered in this survey. Interested readers are referred to section 8.3 for references.

  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. FINGERPRINT RECOGNITION SYSTEM DESIGN

    OpenAIRE

    SONMEZ, Öznur Sinem; OZTAS, Oguzhan

    2010-01-01

    In this study, a minutiae-based fingerprint recognition system is implemented which includes normalization, enhancement, thinning, extraction of minutiae, elimination of false minutiae, orientation estimation, core point detection, finding reference points and matching processes. Accordingly, the effects of enhancement and elimination of false minutiae processes, methods of reference point determination and low quality fingerprint images on system performance are analyzed using two different ...

  1. 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.

  2. 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...

  3. 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.

  4. 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

  5. 3D modelling and recognition

    OpenAIRE

    Rodrigues, Marcos; Robinson, Alan; Alboul, Lyuba; Brink, Willie

    2006-01-01

    3D face recognition is an open field. In this paper we present a method for 3D facial recognition based on Principal Components Analysis. The method uses a relatively large number of facial measurements and ratios and yields reliable recognition. We also highlight our approach to sensor development for fast 3D model acquisition and automatic facial feature extraction.

  6. Projective Methods of Image Recognition

    OpenAIRE

    Putyatin, Yevgeniy; Gorohovatsky, Vladimir; Gorohovatsky, Alexey; Peredriy, Elena

    2008-01-01

    We propose a method for image recognition on the base of projections. Radon transform gives an opportunity to map image into space of its projections. Projection properties allow constructing informative features on the base of moments that can be successfully used for invariant recognition. Offered approach gives about 91-97% of correct recognition.

  7. IRIS Based Human Recognition System

    Directory of Open Access Journals (Sweden)

    Mansi Jhamb, Vinod Kumar Khera

    2011-04-01

    Full Text Available The paper explores iris recognition for personal identification and verification. In this paper a newiris recognition technique is proposed using (Scale Invariant Feature Transform SIFT. Imageprocessingalgorithms have been validated on noised real iris image database. The proposedinnovative technique is computationally effective as well as reliable in terms of recognition rates.

  8. 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.

  9. Audio-visual gender recognition

    Science.gov (United States)

    Liu, Ming; Xu, Xun; Huang, Thomas S.

    2007-11-01

    Combining different modalities for pattern recognition task is a very promising field. Basically, human always fuse information from different modalities to recognize object and perform inference, etc. Audio-Visual gender recognition is one of the most common task in human social communication. Human can identify the gender by facial appearance, by speech and also by body gait. Indeed, human gender recognition is a multi-modal data acquisition and processing procedure. However, computational multimodal gender recognition has not been extensively investigated in the literature. In this paper, speech and facial image are fused to perform a mutli-modal gender recognition for exploring the improvement of combining different modalities.

  10. Vehicle License Plate Recognition System

    Directory of Open Access Journals (Sweden)

    Meenakshi

    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.

  11. DWT BASED IRIS RECOGNITION

    Directory of Open Access Journals (Sweden)

    MAYURI MEMANE

    2012-08-01

    Full Text Available The iris recognition is an emerging technology widely used due to various characteristics such as uniqueness,universal, stable, independent of genetics, acceptable etc. The recognition is carried out using discrete wavelet transform (DWT. It includes collection of iris database, carrying out preprocessing (includes separation ofpupil, normalization and feature extraction. Normalization includes polar to rectangular conversion. After this area of interest is selected from which features are extracted using DWT. It generates approximate, horizontal, vertical and diagonal coefficients. These are compared with the stored templates using hamming distance. If thetemplate is match with the stored one than the match ID is displayed. The unauthorized person is indicated by displaying ID equal to ‘00’

  12. Iris Recognition Using Wavelet

    OpenAIRE

    Khaliq Masood; Muhammad Younus Javed; Abdul Basit

    2013-01-01

    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 t...

  13. Automatic pattern recognition

    OpenAIRE

    Petheram, R.J.

    1989-01-01

    In this thesis the author presents a new method for the location, extraction and normalisation of discrete objects found in digital images. The extraction is by means of sub-pixcel contour following around the object. The normalisation obtains and removes the information concerning size, orientation and location of the object within an image. Analyses of the results are carried out to determine the confidence in recognition of patterns, and methods of cross correlation of object descriptions ...

  14. Infrared face recognition

    OpenAIRE

    Lee, Colin K.

    2004-01-01

    Approved for public release, distribution is unlimited This study continues a previous face recognition investigation using uncooled infrared technology. The database developed in an earlier study is further expanded to include 50 volunteers with 30 facial images from each subject. The automatic image reduction method reduces the pixel size of each image from 160 120 to 60 45 . The study reexamines two linear classification methods: the Principal Component Analysis (PCA) and Fisher ...

  15. Facial Expression Recognition

    OpenAIRE

    Neeta Sarode; Prof. Shalini Bhatia

    2010-01-01

    Facial expression analysis is rapidly becoming an area of intense interest in computer science and human-computer interaction design communities. The most expressive way humans display emotions is through facial expressions. In this paper a method is implemented using 2D appearance-based local approach for the extraction of intransient facial features and recognition of four facial expressions. The algorithm implements Radial Symmetry Transform and further uses edge projection analysis for fe...

  16. Recognition of Teaching Excellence*

    OpenAIRE

    Hammer, Dana; Piascik, Peggy; Medina, Melissa; Pittenger, Amy; Rose, Renee; Creekmore, Freddy; Soltis, Robert; Bouldin, Alicia; Schwarz, Lindsay; Scott, Steven

    2010-01-01

    The 2008-2009 Task Force for the Recognition of Teaching Excellence was charged by the AACP Council of Faculties Leadership to examine teaching excellence by collecting best practices from colleges and schools of pharmacy, evaluating the literature to identify evidence-based criteria for excellent teaching, and recommending appropriate means to acknowledge and reward teaching excellence. This report defines teaching excellence and discusses a variety of ways to assess it, including student, a...

  17. HUMAN SPEECH EMOTION RECOGNITION

    Directory of Open Access Journals (Sweden)

    Maheshwari Selvaraj

    2016-02-01

    Full Text Available Emotions play an extremely important role in human mental life. It is a medium of expression of one’s perspective or one’s mental state to others. Speech Emotion Recognition (SER can be defined as extraction of the emotional state of the speaker from his or her speech signal. There are few universal emotions- including Neutral, Anger, Happiness, Sadness in which any intelligent system with finite computational resources can be trained to identify or synthesize as required. In this work spectral and prosodic features are used for speech emotion recognition because both of these features contain the emotional information. Mel-frequency cepstral coefficients (MFCC is one of the spectral features. Fundamental frequency, loudness, pitch and speech intensity and glottal parameters are the prosodic features which are used to model different emotions. The potential features are extracted from each utterance for the computational mapping between emotions and speech patterns. Pitch can be detected from the selected features, using which gender can be classified. Support Vector Machine (SVM, is used to classify the gender in this work. Radial Basis Function and Back Propagation Network is used to recognize the emotions based on the selected features, and proved that radial basis function produce more accurate results for emotion recognition than the back propagation network.

  18. Techniques for automatic speech recognition

    Science.gov (United States)

    Moore, R. K.

    1983-05-01

    A brief insight into some of the algorithms that lie behind current automatic speech recognition system is provided. Early phonetically based approaches were not particularly successful, due mainly to a lack of appreciation of the problems involved. These problems are summarized, and various recognition techniques are reviewed in the contect of the solutions that they provide. It is pointed out that the majority of currently available speech recognition equipments employ a "whole-word' pattern matching approach which, although relatively simple, has proved particularly successful in its ability to recognize speech. The concepts of time-normalizing plays a central role in this type of recognition process and a family of such algorithms is described in detail. The technique of dynamic time warping is not only capable of providing good performance for isolated word recognition, but how it is also extended to the recognition of connected speech (thereby removing one of the most severe limitations of early speech recognition equipment).

  19. 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

  20. Recognition Using Regions

    OpenAIRE

    Gu, Chunhui

    2012-01-01

    Multi-scale window scanning has been popular in object detection but it generalizes poorly to complex features (e.g. nonlinear SVM kernel), deformable objects (e.g. animals), and finer-grained tasks (e.g. segmentation). In contrast to that, regions are appealing as image primitives for recognition because: (1) they encode object shape and scale naturally; (2) they are only mildly affected by background clutter; and (3) they significantly reduce the set of possible object locations in images.I...

  1. Visual affect recognition

    CERN Document Server

    Stathopoulou, I-O

    2010-01-01

    It is generally known that human faces, as well as body motions and gestures, provide a wealth of information about a person, such as age, race, sex and emotional state. This monograph primarily studies the perception of facial expression of emotion, and secondarily of motion and gestures, with the purpose of developing a fully automated visual affect recognition system for use in modes of human/computer interaction. The book begins with a survey of the literature on emotion perception, followed by a description of empirical studies conducted with human participants and the construction of a '

  2. 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. .

  3. 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.

  4. Monocular SLAM Supported Object Recognition

    OpenAIRE

    Pillai, Sudeep; Leonard, John,

    2015-01-01

    In this work, we develop a monocular SLAM-aware object recognition system that is able to achieve considerably stronger recognition performance, as compared to classical object recognition systems that function on a frame-by-frame basis. By incorporating several key ideas including multi-view object proposals and efficient feature encoding methods, our proposed system is able to detect and robustly recognize objects in its environment using a single RGB camera in near-constant time. Through e...

  5. Embedded Systems for Iris Recognition

    OpenAIRE

    Anushree S. Patil; Sushil M. Rajbhoj

    2015-01-01

    Iris Recognition increasingly used method of biometric authentication that involves pattern-recognition techniques of images of irides to uniquely identify a person. In this paper, IRIS biometrics has been chosen for implementation due to the reduced error rates and the robustness their algorithms provide. The goal of this paper is to design a detached system, to implement a working prototype of the techniques and methods used for iris recognition. A powerful ARM7TDMI-S core based...

  6. 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...

  7. Forensic Face Recognition: A Survey

    OpenAIRE

    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 the forensic experts‟ way of manual facial comparison. Then we review famous works in the domain of forensic face recognition. Some of these papers describe general trends in forensics [1], guidelin...

  8. Innovative Technique for Character Recognition

    OpenAIRE

    Sumant Raj Chauhan; Punit Soni

    2010-01-01

    Development of OCRs for Indian script is an active area of activity today. Optical character recognition (OCR) is the mechanical or electronic translation of images of handwritten, typewritten or printed text (usually captured by a scanner) into machine-editable text. In simple words OCR is a visual recognition process that turns printed or written text into an electronic character based file. OCR is a field of research in pattern recognition, artificial intelligence and machine vision. India...

  9. Information theory and pattern recognition

    OpenAIRE

    Daemi, M.F.

    1990-01-01

    This thesis presents an account of an investigation into the use of information theory measures in pattern recognition problems. The objectives were firstly to determine the information content of the set of representations of an input image which are found at the output of an array of sensors; secondly to assess the information which may be used to allocate different patterns to appropriate classes in order to provide a means of recognition; and thirdly to assess the recognition capability o...

  10. Techniques in Facial Expression Recognition

    OpenAIRE

    Avinash Prakash Pandhare; Umesh Balkrishna Chavan

    2016-01-01

    Facial expression recognition is gaining widespread importance as the applications related to Human – Computer interactions are increasing. This paper mentions various techniques and approaches that have been used in the field of facial expression recognition. Facial expression recognition takes place in various stages and these stages have been implemented by various approaches. Viola and Jones for face detection, Gabor filters for feature extraction, SVM classifiers for classifi...

  11. 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

  12. 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.

  13. A SURVEY ON FACE RECOGNITION

    Directory of Open Access Journals (Sweden)

    R.VINODINI

    2014-02-01

    Full Text Available Face recognition is one of the most emerging and popular biometric authentication of a person, it presents a challenging problem in the field of image analysis and computer vision. Though there are various biometric traits such as iris, fingerprint and palm print etc., we focused on face recognition as it is socially acceptable and reliable. Here user identity plays a very important role to uniquely verify or authenticate the individual person. Many techniques were implemented in face recognition all having their respective pros and cons. In this paper, we presented an overview of face recognition techniques and its applications.

  14. Retina vascular network recognition

    Science.gov (United States)

    Tascini, Guido; Passerini, Giorgio; Puliti, Paolo; Zingaretti, Primo

    1993-09-01

    The analysis of morphological and structural modifications of the retina vascular network is an interesting investigation method in the study of diabetes and hypertension. Normally this analysis is carried out by qualitative evaluations, according to standardized criteria, though medical research attaches great importance to quantitative analysis of vessel color, shape and dimensions. The paper describes a system which automatically segments and recognizes the ocular fundus circulation and micro circulation network, and extracts a set of features related to morphometric aspects of vessels. For this class of images the classical segmentation methods seem weak. We propose a computer vision system in which segmentation and recognition phases are strictly connected. The system is hierarchically organized in four modules. Firstly the Image Enhancement Module (IEM) operates a set of custom image enhancements to remove blur and to prepare data for subsequent segmentation and recognition processes. Secondly the Papilla Border Analysis Module (PBAM) automatically recognizes number, position and local diameter of blood vessels departing from optical papilla. Then the Vessel Tracking Module (VTM) analyses vessels comparing the results of body and edge tracking and detects branches and crossings. Finally the Feature Extraction Module evaluates PBAM and VTM output data and extracts some numerical indexes. Used algorithms appear to be robust and have been successfully tested on various ocular fundus images.

  15. 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.

  16. Technical trend of OCR and recognition technology

    International Nuclear Information System (INIS)

    This book is comprised of nine chapters, which are introduction of optical character reader, the history and development of OCR, foundation of character recognition technology, print letter recognition, script character recognition with stroke matching method, On-line character recognition on summary of character recognition of on-line script, the ways of on-line script and on-line Hangeul recognition with syntactic analysis, construction of character recognition system and formation of Hangeul for character recognition. This book describes character recognition technology with various technique of optical character reader.

  17. 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…

  18. 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.

  19. Recognition Using Hybrid Classifiers.

    Science.gov (United States)

    Osadchy, Margarita; Keren, Daniel; Raviv, Dolev

    2016-04-01

    A canonical problem in computer vision is category recognition (e.g., find all instances of human faces, cars etc., in an image). Typically, the input for training a binary classifier is a relatively small sample of positive examples, and a huge sample of negative examples, which can be very diverse, consisting of images from a large number of categories. The difficulty of the problem sharply increases with the dimension and size of the negative example set. We propose to alleviate this problem by applying a "hybrid" classifier, which replaces the negative samples by a prior, and then finds a hyperplane which separates the positive samples from this prior. The method is extended to kernel space and to an ensemble-based approach. The resulting binary classifiers achieve an identical or better classification rate than SVM, while requiring far smaller memory and lower computational complexity to train and apply. PMID:26959677

  20. 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.

  1. 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.

  2. Automatic Speaker Recognition System

    Directory of Open Access Journals (Sweden)

    Parul,R. B. Dubey

    2012-12-01

    Full Text Available Spoken language is used by human to convey many types of information. Primarily, speech convey message via words. Owing to advanced speech technologies, people's interactions with remote machines, such as phone banking, internet browsing, and secured information retrieval by voice, is becoming popular today. Speaker verification and speaker identification are important for authentication and verification in security purpose. Speaker identification methods can be divided into text independent and text-dependent. Speaker recognition is the process of automatically recognizing speaker voice on the basis of individual information included in the input speech waves. It consists of comparing a speech signal from an unknown speaker to a set of stored data of known speakers. This process recognizes who has spoken by matching input signal with pre- stored samples. The work is focussed to improve the performance of the speaker verification under noisy conditions.

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. Side-View Face Recognition

    OpenAIRE

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

    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 the use of side-view face recognition in house safety applications. Our goal is to recognize people as they pass through doors in order to estimate their location in the house. In order to preserve p...

  8. Side-View Face Recognition

    OpenAIRE

    Santemiz, Pinar; Spreeuwers, Luuk J.; Veldhuis, Raymond N. J.

    2010-01-01

    Side-view face recognition is a challenging problem with many applications. Especially in real-life scenarios where the environment is uncontrolled, coping with pose variations up to side-view positions is an important task for face recognition. In this paper we discuss the use of side view face recognition techniques to be used in house safety applications. Our aim is to recognize people as they pass through a door, and estimate their location in the house. Here, we compare available databas...

  9. 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

  10. Macromolecular recognition: Recognition of polymer side chains by cyclodextrin

    Science.gov (United States)

    Hashidzume, Akihito; Harada, Akira

    2015-12-01

    The interaction of cyclodextrins (CD) with water soluble polymers possessing guest residues has been investigated as model systems in biological molecular recognition. The selectivity of interaction of CD with polymer-carrying guest residues is controlled by polymer chains, i.e., the steric effect of polymer main chain, the conformational effect of polymer main chain, and multi-site interaction. Macroscopic assemblies have been also realized based on molecular recognition using polyacrylamide-based gels possessing CD and guest residues.

  11. Post Stamp Perforation Recognition

    OpenAIRE

    Koníček, Vladimír

    2008-01-01

    Rozpoznávání zoubkování poštovních známek je důležitým faktorem při posuzování pravosti poštovní známky. Typ a rozměr zoubkování mají výrazný vliv na cenu poštovní známky. Tato práce se zabývá navrhem detektoru zoubkování poštovních známek. Cílem práce je vytvořit aplikaci, která z fotografie určí zoubkování zobrazené poštovní známky. Aplikace pro práci s obrazy využívá knihovnu OpenCV. Post stamp perforation recognition is important factor in authentication of post stamps. Type and perfor...

  12. 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.

  13. 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.

  14. 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...

  15. Moment Invariants for Object Recognition

    Czech Academy of Sciences Publication Activity Database

    Flusser, Jan

    Boca Raton: Wiley&Sons, 2015. ISBN 9780471346081 Institutional support: RVO:67985556 Keywords : invariants * object recognition * moments Subject RIV: JC - Computer Hardware ; Software http://library.utia.cas.cz/separaty/2015/ZOI/flusser-0442976.pdf

  16. A Survey: Face Recognition Techniques

    OpenAIRE

    Muhammad Sharif; Sajjad Mohsin; Muhammad Younas Javed

    2012-01-01

    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 proce...

  17. A SURVEY ON FACE RECOGNITION

    OpenAIRE

    R.VINODINI; DR.M.KARNAN

    2014-01-01

    Face recognition is one of the most emerging and popular biometric authentication of a person, it presents a challenging problem in the field of image analysis and computer vision. Though there are various biometric traits such as iris, fingerprint and palm print etc., we focused on face recognition as it is socially acceptable and reliable. Here user identity plays a very important role to uniquely verify or authenticate the individual person. Many techniques were implemented in face recogni...

  18. Theoretical Aspects of Molecular Recognition

    OpenAIRE

    Harmat, Veronika; Náray-Szabó, Gábor

    2009-01-01

    Molecular recognition is a key process in non-covalent interactions, which determines, among others, host-guest complexation, drug action and protein-protein interaction. A simple and attractive formulation is the lock-and-key analogy defining the host as a lock accommodating the guest as a key. We stress three major aspects of molecular recognition, determining both complementarity between host and guest and similarity within a group of guest molecules. These aspects are: steric, i.e. maximi...

  19. Pattern Recognition Theory of Mind

    OpenAIRE

    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 definiti...

  20. Educational perspectives on recognition theory

    OpenAIRE

    Hanhela, T. (Teemu)

    2014-01-01

    Abstract The starting point for the research is to examine the educational perspectives of Axel Honneth’s recognition theory to find useful contents for educational institutions. The method of the thesis is conceptual analysis which gets a dual role: chapters two and three of the treatise define and analyse Honneth’s concept of recognition and its historic-philosophical context and with help of critical analyses, the articles (I, II and III) and chapter four of the dissertation connects t...

  1. Object Recognition Using Spatiotemporal Signatures

    OpenAIRE

    James V Stone

    1998-01-01

    The sequence of images generated by motion between observer and object specifies a spatiotemporal signature for that object. Evidence is presented that such spatiotemporal signatures are used in object recognition. Subjects learned novel, three-dimensional, rotating objects from image sequences in a continuous recognition task. During learning, the temporal order of images of a given object was constant. During testing, the order of images in each sequence was reversed, relative to its order ...

  2. Automatic Number Plate Recognition System

    OpenAIRE

    Rajshree Dhruw; Dharmendra Roy

    2014-01-01

    Automatic Number Plate Recognition (ANPR) is a mass surveillance system that captures the image of vehicles and recognizes their license number. The objective is to design an efficient automatic authorized vehicle identification system by using the Indian vehicle number plate. In this paper we discus different methodology for number plate localization, character segmentation & recognition of the number plate. The system is mainly applicable for non standard Indian number plates by recognizing...

  3. Facial Expressions Recognition Using Eigenspaces

    OpenAIRE

    Senthil Ragavan Valayapalayam Kittusamy; Venkatesh Chakrapani

    2012-01-01

    A challenging research topic is to make the Computer Systems to recognize facial expressions from the face image. A method of facial expression recognition, based on Eigenspaces is presented in this study. Here, the authors recognize the userâs facial expressions from the input images, using a method that was customized from eigenface recognition. Evaluation was done for this method in terms of identification correctness using two different Facial Expressions databases, Cohn-Kanade facial exp...

  4. Combinatorial approaches to gene recognition.

    Science.gov (United States)

    Roytberg, M A; Astakhova, T V; Gelfand, M S

    1997-01-01

    Recognition of genes via exon assembly approaches leads naturally to the use of dynamic programming. We consider the general graph-theoretical formulation of the exon assembly problem and analyze in detail some specific variants: multicriterial optimization in the case of non-linear gene-scoring functions; context-dependent schemes for scoring exons and related procedures for exon filtering; and highly specific recognition of arbitrary gene segments, oligonucleotide probes and polymerase chain reaction (PCR) primers. PMID:9440930

  5. Speech Recognition Technology: Applications & Future

    OpenAIRE

    Pankaj Pathak

    2010-01-01

    Voice or speech recognition is "the technology by which sounds, words or phrases spoken by humans are converted into electrical signals, and these signals are transformed into coding patterns to which meaning has been assigned", .It is the technology needs a combination of improved artificial intelligence technology and a more sophisticated speech-recognition engine . Initially a primitive device is developed which could recognize speech, by AT & T Bell Laboratories in the 1940s. According to...

  6. Recognition Memory in Psychotic Patients

    Directory of Open Access Journals (Sweden)

    H. Ellis

    1992-01-01

    Full Text Available Preliminary data are reported from experiments in which Warrington's (1984 Recognition Memory Tests were given to patients with misidentification delusions including the Capgras type and to psychotic patients. The results showed a profound impairment on face recognition for most groups, especially those with the Capgras delusion. It was rare to find a patent whose score on the word test was anything but normal.

  7. Success with voice recognition.

    Science.gov (United States)

    Sferrella, Sheila M

    2003-01-01

    You need a compelling reason to implement voice recognition technology. At my institution, the compelling reason was a turnaround time for Radiology results of more than two days. Only 41 percent of our reports were transcribed and signed within 24 hours. In November 1998, a team from Lehigh Valley Hospital went to RSNA and reviewed every voice system on the market. The evaluation was done with the radiologist workflow in mind, and we came back from the meeting with the vendor selection completed. The next steps included developing a business plan, approval of funds, reference calls to more than 15 sites and contract negotiation, all of which took about six months. The department of Radiology at Lehigh Valley Hospital and Health Network (LVHHN) is a multi-site center that performs over 360,000 procedures annually. The department handles all modalities of radiology: general diagnosis, neuroradiology, ultrasound, CT Scan, MRI, interventional radiology, arthography, myelography, bone densitometry, nuclear medicine, PET imaging, vascular lab and other advanced procedures. The department consists of 200 FTEs and a medical staff of more than 40 radiologists. The budget is in the $10.3 million range. There are three hospital sites and four outpatient imaging center sites where services are provided. At Lehigh Valley Hospital, radiologists are not dedicated to one subspecialty, so implementing a voice system by modality was not an option. Because transcription was so far behind, we needed to eliminate that part of the process. As a result, we decided to deploy the system all at once and with the radiologists as editors. The planning and testing phase took about four months, and the implementation took two weeks. We deployed over 40 workstations and trained close to 50 physicians. The radiologists brought in an extra radiologist from our group for the two weeks of training. That allowed us to train without taking a radiologist out of the department. We trained three to six

  8. 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.

  9. Micro-Recognition - Erving Goffman as Recognition Thinker

    DEFF Research Database (Denmark)

    Jacobsen, Michael Hviid; Kristiansen, Søren

    2009-01-01

      The purpose of this article is to present, develop and exemplify the argument that Erving Goffman can be regarded as an important yet somewhat overlooked contributor to recognition theory in contemporary sociology. Despite often being neglected in this respect, this article provides an interpre......  The purpose of this article is to present, develop and exemplify the argument that Erving Goffman can be regarded as an important yet somewhat overlooked contributor to recognition theory in contemporary sociology. Despite often being neglected in this respect, this article provides an...... interpretation of Goffman as a major recognition theorist on the micro-level of social analysis by way of his ritual metaphor. Erving Goffman's sociology is conventionally approached and appreciated primarily through his famous dramaturgical metaphor that describes and comprehends social life through the......-structural or macro-sociological recognition claims and all contain a certain political or moral edge - Goffman rather provides a much more descriptive and micro-sociological account of the workings and necessity of recognition. In his ritual metaphorical perspective, social interaction to a large extent...

  10. Oracle Complexity and Nontransitivity in Pattern Recognition

    OpenAIRE

    Bulitko, Vadim

    2000-01-01

    Different mathematical models of recognition processes are known. In the present paper we consider a pattern recognition algorithm as an oracle computation on a Turing machine. Such point of view seems to be useful in pattern recognition as well as in recursion theory. Use of recursion theory in pattern recognition shows connection between a recognition algorithm comparison problem and complexity problems of oracle computation. That is because in many cases we can take into account only the n...

  11. 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.

  12. Embedded Systems for Iris Recognition

    Directory of Open Access Journals (Sweden)

    Anushree S. Patil

    2015-09-01

    Full Text Available Iris Recognition increasingly used method of biometric authentication that involves pattern-recognition techniques of images of irides to uniquely identify a person. In this paper, IRIS biometrics has been chosen for implementation due to the reduced error rates and the robustness their algorithms provide. The goal of this paper is to design a detached system, to implement a working prototype of the techniques and methods used for iris recognition. A powerful ARM7TDMI-S core based micro controller LPC2148 is used to demonstrate the algorithms required for generating biometric templates from IRIS database for matching. The results from this device is compared to Matlab run PC which will give the insight required to compare the performance analysis of the algorithms in use proceedings.

  13. 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.

  14. Sparse representation for vehicle recognition

    Science.gov (United States)

    Monnig, Nathan D.; Sakla, Wesam

    2014-06-01

    The Sparse Representation for Classification (SRC) algorithm has been demonstrated to be a state-of-the-art algorithm for facial recognition applications. Wright et al. demonstrate that under certain conditions, the SRC algorithm classification performance is agnostic to choice of linear feature space and highly resilient to image corruption. In this work, we examined the SRC algorithm performance on the vehicle recognition application, using images from the semi-synthetic vehicle database generated by the Air Force Research Laboratory. To represent modern operating conditions, vehicle images were corrupted with noise, blurring, and occlusion, with representation of varying pose and lighting conditions. Experiments suggest that linear feature space selection is important, particularly in the cases involving corrupted images. Overall, the SRC algorithm consistently outperforms a standard k nearest neighbor classifier on the vehicle recognition task.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. Interstate Recognition and Its Global Overcoming: Extra-territorial Recognition

    Czech Academy of Sciences Publication Activity Database

    Hrubec, Marek

    Praha: Filosofia, 2015 - (Oliveira, N.; Hrubec, M.; Sobottka, E.; Saavedra, G.), s. 287-323 ISBN 978-80-7007-435-0 R&D Projects: GA ČR(CZ) GA14-19416S Institutional support: RVO:67985955 Keywords : recognition * interstate * international * global * extra-territorial * justice * Axel Honneth Subject RIV: AA - Philosophy ; Religion

  20. 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

  1. Non-intrusive appliance recognition

    NARCIS (Netherlands)

    Hoogsteen, G; Krist, J.O.; Bakker, V.; Smit, G.J.M.

    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

  2. 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...

  3. Sphere recognition lies in NP

    OpenAIRE

    Schleimer, Saul

    2004-01-01

    We prove that the three-sphere recognition problem lies in the complexity class NP. Our work relies on Thompson's original proof that the problem is decidable [Math. Res. Let., 1994], Casson's version of her algorithm, and recent results of Agol, Hass, and Thurston [ArXiv, 2002].

  4. Named Entity Recognition for IDEAL

    OpenAIRE

    Du, Qianzhou; Xuan ZHANG

    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.

  5. Sphere Recognition: Heuristics and Examples

    OpenAIRE

    Joswig, Michael; Lutz, Frank H.; Tsuruga, Mimi

    2014-01-01

    Heuristic techniques for recognizing PL spheres using the topological software polymake are presented. These methods have been successful very often despite sphere recognition being known to be hard (for dimensions $d \\ge 3$) or even undecidable (for $d \\ge 5$). A deeper look into the simplicial complexes for which the heuristics failed uncovered a trove of examples having interesting topological and combinatorial properties.

  6. 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

  7. Innovative Technique for Character Recognition

    Directory of Open Access Journals (Sweden)

    Sumant Raj Chauhan

    2010-10-01

    Full Text Available Development of OCRs for Indian script is an active area of activity today. Optical character recognition (OCR is the mechanical or electronic translation of images of handwritten, typewritten or printed text (usually captured by a scanner into machine-editable text. In simple words OCR is a visual recognition process that turns printed or written text into an electronic character based file. OCR is a field of research in pattern recognition, artificial intelligence and machine vision. Indian scripts present great challenges to an OCR designer due to the large number of letters in the alphabet, the sophisticated ways in which they combine, and the complicated graphemes they result in. The problem is compounded by the unstructured manner in which popular fonts are designed. There is a lot of common structure in the different Indian scripts. All existing OCR systems developed for various Indian scripts do not provide sufficient efficiency due to various factors. The objective of this paper is to discuss a more efficient character recognition technique. This paper introduces a new technical approach to recognize Indian script characters which are unpredictable due to different problems in other OCR’s.

  8. Iris Recognition Using Fuzzy System

    OpenAIRE

    Prof.D.D.Patil; Prof.N.A.Nemade; K.M.Attarde

    2013-01-01

    By using biometric system automatic recognition of an individual is provided. Biometric systems include fingerprints, facial features, voice, hand geometry, handwriting, the retina and the one presented inthis thesis, the iris. Working of this system is simple. It captures the image and compare with exiting image. If match is found then access is granted.

  9. Face recognition for uncontrolled environments

    Science.gov (United States)

    Podilchuk, Christine; Hulbert, William; Flachsbart, Ralph; Barinov, Lev

    2010-04-01

    A new face recognition algorithm has been proposed which is robust to variations in pose, expression, illumination and occlusions such as sunglasses. The algorithm is motivated by the Edit Distance used to determine the similarity between strings of one dimensional data such as DNA and text. The key to this approach is how to extend the concept of an Edit Distance on one-dimensional data to two-dimensional image data. The algorithm is based on mapping one image into another and using the characteristics of the mapping to determine a two-dimensional Pictorial-Edit Distance or P-Edit Distance. We show how the properties of the mapping are similar to insertion, deletion and substitution errors defined in an Edit Distance. This algorithm is particularly well suited for face recognition in uncontrolled environments such as stand-off and other surveillance applications. We will describe an entire system designed for face recognition at a distance including face detection, pose estimation, multi-sample fusion of video frames and identification. Here we describe how the algorithm is used for face recognition at a distance, present some initial results and describe future research directions.(

  10. 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.

  11. Simultaneous Tracking and Activity Recognition

    DEFF Research Database (Denmark)

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

    2011-01-01

    recognition, our framework performs these two tasks simultaneously. In particular, we adopt a Bayesian standpoint where the system maintains a joint distribution of the positions, the interactions and the possible activities. This turns out to be advantegeous, as information about the ongoing activities can...

  12. Target recognition by wavelet transform

    International Nuclear Information System (INIS)

    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

  13. Digital Recognition using Neural Network

    Directory of Open Access Journals (Sweden)

    Saleh A.K. Al-Omari

    2009-01-01

    Full Text Available Problem statement: Handwriting number recognition is a challenging problem researchers had been research into this area for so long especially in the recent years. In our study there are many fields concern with numbers, for example, checks in banks or recognizing numbers in car plates, the subject of digit recognition appears. A system for recognizing isolated digits may be as an approach for dealing with such application. In other words, to let the computer understand the Arabic numbers that is written manually by users and views them according to the computer process. Scientists and engineers with interests in image processing and pattern recognition have developed various approaches to deal with handwriting number recognition problems such as, minimum distance, decision tree and statistics. Approach: The main objective for our system was to recognize isolated Arabic digits exist in different applications. For example, different users had their own handwriting styles where here the main challenge falls to let computer system understand these different handwriting styles and recognize them as standard writing. Result: We presented a system for dealing with such problem. The system started by acquiring an image containing digits, this image was digitized using some optical devices and after applying some enhancements and modifications to the digits within the image it can be recognized using feed forward back propagation algorithm. The studies were conducted on the Arabic handwriting digits of 10 independent writers who contributed a total of 1300 isolated Arabic digits these digits divided into two data sets: Training 1000 digits, testing 300 digits. An overall accuracy meet using this system was 95% on the test data set used. Conclusion: We developed a system for Arabic handwritten recognition. And we efficiently choose a segmentation method to fit our demands. Our system successfully designs and implement a neural network which efficiently

  14. Public domain optical character recognition

    Science.gov (United States)

    Garris, Michael D.; Blue, James L.; Candela, Gerald T.; Dimmick, Darrin L.; Geist, Jon C.; Grother, Patrick J.; Janet, Stanley A.; Wilson, Charles L.

    1995-03-01

    A public domain document processing system has been developed by the National Institute of Standards and Technology (NIST). The system is a standard reference form-based handprint recognition system for evaluating optical character recognition (OCR), and it is intended to provide a baseline of performance on an open application. The system's source code, training data, performance assessment tools, and type of forms processed are all publicly available. The system recognizes the handprint entered on handwriting sample forms like the ones distributed with NIST Special Database 1. From these forms, the system reads hand-printed numeric fields, upper and lowercase alphabetic fields, and unconstrained text paragraphs comprised of words from a limited-size dictionary. The modular design of the system makes it useful for component evaluation and comparison, training and testing set validation, and multiple system voting schemes. The system contains a number of significant contributions to OCR technology, including an optimized probabilistic neural network (PNN) classifier that operates a factor of 20 times faster than traditional software implementations of the algorithm. The source code for the recognition system is written in C and is organized into 11 libraries. In all, there are approximately 19,000 lines of code supporting more than 550 subroutines. Source code is provided for form registration, form removal, field isolation, field segmentation, character normalization, feature extraction, character classification, and dictionary-based postprocessing. The recognition system has been successfully compiled and tested on a host of UNIX workstations. This paper gives an overview of the recognition system's software architecture, including descriptions of the various system components along with timing and accuracy statistics.

  15. Ear Recognition Based on Forstner and SIFT

    Directory of Open Access Journals (Sweden)

    Ma Chi

    2013-07-01

    Full Text Available Extraction and expression of features are critical to improving the recognition rate of ear image recognition. This paper proposes a new ear recognition method based on SIFT(Scale-invariant feature transform and Forstner corner detection technology. Firstly, Forstner corner points and SIFT keypoints are detected respectively. Then taking Forstner corner into the SIFT algorithm to calculate their descriptor as the image feature vectors. Finally ear recognition based on these feature is carried out with Euclidean distance as similarity measurement. A bi-directional matching algorithm is utilized for improving recognition rate. Experiments on USTB database show that the recognition rate reaches more 94%. The Experimental results prove the effectiveness of the proposed method in term of recognition accuracy in comparison with previous methods. It is robust to rigid changes of ear image and provides a new approach to the research for ear recognition.

  16. Ear Recognition Based on Forstner and SIFT

    OpenAIRE

    Ma Chi; Zhu Yongyong; Tian Ying

    2013-01-01

    Extraction and expression of features are critical to improving the recognition rate of ear image recognition. This paper proposes a new ear recognition method based on SIFT(Scale-invariant feature transform) and Forstner corner detection technology. Firstly, Forstner corner points and SIFT keypoints are detected respectively. Then taking Forstner corner into the SIFT algorithm to calculate their descriptor as the image feature vectors. Finally ear recognition based on these feature is carrie...

  17. 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

  18. Face Recognition Techniques - An evaluation Study

    OpenAIRE

    Dr.Asmahan M Altaher

    2015-01-01

    Face recognition is the ability of categorize a set of images based on certain discriminatory features. Classification of the recognition patterns can be difficult problem and it is still very active field of research. The paper introduces conceptual framework for descriptive study on techniques of face recognition systems. It aims to describe the previous researches have been study the face recognition system, in order scope on the algorithms, usages, benefits , challenges and problems in th...

  19. 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....

  20. Arabic natural language processing: handwriting recognition

    OpenAIRE

    Belaïd, Abdel

    2008-01-01

    The automatic recognition of Arabic writing is a very young research discipline with very challenging and significant problems. Indeed, with the air of the Internet, of Multimedia, the recognition of Arabic is useful to contributing like its close disciplines, Latin writing recognition, speech recognition and Vision processing, in current applications around digital libraries, document security and in numerical data processing in general. Arabic is a Semitic language spoken and understood in ...

  1. 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 keypoint....... 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....

  2. Computing negentropy based signatures for texture recognition

    OpenAIRE

    Daniela COLTUC; Laurentiu FRANGU; Ana-Elena LUNGU

    2007-01-01

    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.

  3. 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

  4. 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...

  5. 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...

  6. 8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Science.gov (United States)

    2010-01-01

    ... disposal adequate knowledge, information and experience. (b) Requests for recognition. An organization... non-profit religious, charitable, social service, or similar organization established in the United...). Such organization must establish to the satisfaction of the Board that: (1) It makes only...

  7. 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)

  8. 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.

  9. 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

  10. Hand Gesture Recognition: A Literature Review

    Directory of Open Access Journals (Sweden)

    Rafiqul Zaman Khan

    2012-08-01

    Full Text Available Hand gesture recognition system received great attention in the recent few years because of itsmanifoldness applications and the ability to interact with machine efficiently through human computerinteraction. In this paper a survey of recent hand gesture recognition systems is presented. Key issues ofhand gesture recognition system are presented with challenges of gesture system. Review methods of recentpostures and gestures recognition system presented as well. Summary of research results of hand gesturemethods, databases, and comparison between main gesture recognition phases are also given. Advantagesand drawbacks of the discussed systems are explained finally

  11. Optical pattern recognition with holographic filters

    International Nuclear Information System (INIS)

    Holography process differs from photography as it can record information of three dimensional objects. In photography irradiance distribution of light scattered from object is recorded. There are various types of holograms depending upon the recording geometries. The optical pattern recognition is carried out by first making a hologram of an object. In this thesis the task of pattern recognition and introduction of optical pattern recognition with holographic filters as another method for pattern recognition is presented. Optical pattern recognition with the help of fourier transform holographic filter has been elaborated. (A.B.)

  12. Non Audio-Video gesture recognition system

    DEFF Research Database (Denmark)

    Craciunescu, Razvan; Mihovska, Albena Dimitrova; Kyriazakos, Sofoklis;

    2016-01-01

    Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Current research focus includes on the emotion...... recognition from the face and hand gesture recognition. Gesture recognition enables humans to communicate with the machine and interact naturally without any mechanical devices. This paper investigates the possibility to use non-audio/video sensors in order to design a low-cost gesture recognition device that...

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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...

  19. 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, ...

  20. 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.

  1. 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...... individually. Aggression was significantly lower in pairs of queens that had previously interacted than in pairs with similar social history but no experience with one another. Moreover, subordinates discriminated familiar and unfamiliar dominants in choice experiments in which physical contact, but not odor...... 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...

  2. 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.

  3. 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....

  4. 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.

  5. Liveness Detection for Face Recognition

    OpenAIRE

    Pan, Gang; Wu, Zhaohui; Sun, Lin

    2008-01-01

    We investigate eyeblinks as a liveness detection clue against photo spoofing in face recognition. The advantages of eyeblink-based method are non-intrusion, no requirement of extra hardware. Undirected conditional graphical framework, which assumes dependencies among the observations and states, is employed to model eyeblink. A new-defined discriminative measure of eye states, called eye closity, can hasten inference as well as convey most effective discriminative information. Experiments dem...

  6. Hand Gestures Recognition and Tracking

    OpenAIRE

    Gurung, Deepak; Jiang, Cansen; Deray, Jeremie; Sidibé, Désiré

    2013-01-01

    In this project we develop a system that uses low cost web cameras to recognise gestures and track 2D orientations of the hand. This report is organized as such. First in section 2 we introduce various methods we undertook for hand detection. This is the most important step in hand gesture recognition. Results of various skin detection algorithms are discussed in length. This is followed by region extraction step (section 3). In this section approaches like contours and convex hull to extract...

  7. Interfacial metal and antibody recognition

    OpenAIRE

    Zhou, Tongqing; Hamer, Dean H.; Hendrickson, Wayne A.; Sattentau, Quentin J.; Kwong, Peter D.

    2005-01-01

    The unique ligation properties of metal ions are widely exploited by proteins, with approximately one-third of all proteins estimated to be metalloproteins. Although antibodies use various mechanisms for recognition, to our knowledge, none has ever been characterized that uses an interfacial metal. We previously described a family of CD4-reactive antibodies, the archetype being Q425. CD4:Q425 engagement does not interfere with CD4:HIV-1 gp120 envelope glycoprotein binding, but it blocks subse...

  8. Pattern recognition for earthquake detection

    OpenAIRE

    Joswig, Manfred

    1990-01-01

    The detector algorithms in use at date rely on negative decision logic: based on a model of the ambient noise process they detect all deviations, but many of them are false alarms. The principal alternative to this approach is pattern recognition, which tests on positive correlation with some known signal patterns. The Sonogram-detector realizes this scheme for single seismogram traces. Sonograms display spectral energy versus time. Suitably scaled, these images display only information wh...

  9. Biometric Recognition for Pet Animal

    OpenAIRE

    Santosh Kumar; Sanjay Kumar Singh

    2014-01-01

    Missing, swapping, false insurance claims and reallocation of pet animals (dog) are global problems throughout the world and research done to solve this problem is minimal. Traditional biometrics and non-biometrics methods have their own boundaries and they fail to provide competent level of security to pet animal (dog). The work on animal identification based on their phenotype appearance (coat patterns) has been an active research area in recent years and automatic face recognition for...

  10. Lattice Parsing for Speech Recognition

    OpenAIRE

    Chappelier, Jean-Cédric; Rajman, Martin; Aragües, Ramon; Rozenknop, Antoine

    1999-01-01

    A lot of work remains to be done in the domain of a better integration of speech recognition and language processing systems. This paper gives an overview of several strategies for integrating linguistic models into speech understanding systems and investigates several ways of producing sets of hypotheses that include more "semantic" variability than usual language models. The main goal is to present and demonstrate by actual experiments that sequential couplingmay be efficiently achieved byw...

  11. 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.

  12. Introduction to Statistical Pattern Recognition

    Czech Academy of Sciences Publication Activity Database

    Pudil, Pavel; Somol, Petr; Haindl, Michal

    Plzeň : West Bohemian University, Pilsen, 2006 - (Troblova), s. 163-170 ISBN 80-7043-508-9. [MATEO - The European Network of Mechatronics Centres and Industrial Controllers 2006. Železná Ruda (CZ), 14.12.2006-16.12.2006] Grant ostatní: MMR(CZ) MAT-12-C4 Institutional research plan: CEZ:AV0Z10750506 Keywords : Pattern Recognition Subject RIV: BD - Theory of Information

  13. Task specific image text recognition

    OpenAIRE

    Ben-Haim, Nadav

    2008-01-01

    This thesis addresses the problem of reading image text, which we define here as a digital image of machine printed text. Images of license plates, signs, and scanned documents fall into this category, whereas images of handwriting do not. Automatically reading image text is a very well researched problem, which falls into the broader category of Optical Character Recognition (OCR). Virtually all work in this domain begins by segmenting characters from the image and proceeds with a classifica...

  14. Cultural Identities: Transformation and Recognition

    OpenAIRE

    Kostenko, Natalia

    2003-01-01

    Identity legitimacy is regarded as a key issue to understand the current post-communist world and to substantiate the identity recognition policy, that is a legitimate (for society) way of differentiation control. There are presented two ideal models of identity production: 1) based on essentialistic imperatives, and 2) close to constructivism in its various versions, like post-classical one. There are an a lyzed significant practices and figurative representations applied to identities.

  15. Organizing multivalency in carbohydrate recognition.

    Science.gov (United States)

    Müller, Christian; Despras, Guillaume; Lindhorst, Thisbe K

    2016-06-01

    The interactions of cell surface carbohydrates as well as of soluble glycoconjugates with their receptor proteins rule fundamental processes in cell biology. One of the supramolecular principles underlying and regulating carbohydrate recognition is multivalency. Many multivalent glycoconjugates have therefore been synthesized to study multivalency effects operative in glycobiology. This review is focused on smaller multivalent structures such as glycoclusters emphasizing carbohydrate-centered and heteromultivalent glycoconjugates. We are discussing primary, secondary and tertiary structural aspects including approaches to organize multivalency. PMID:27146554

  16. Neural Networks for Fingerprint Recognition

    OpenAIRE

    Baldi, Pierre; Chauvin, Yves

    1993-01-01

    After collecting a data base of fingerprint images, we design a neural network algorithm for fingerprint recognition. When presented with a pair of fingerprint images, the algorithm outputs an estimate of the probability that the two images originate from the same finger. In one experiment, the neural network is trained using a few hundred pairs of images and its performance is subsequently tested using several thousand pairs of images originated from a subset of the database corresponding to...

  17. Longitudinal study of fingerprint recognition

    OpenAIRE

    Yoon, Soweon; Anil K Jain

    2015-01-01

    Fingerprint recognition, which is considered to be a reliable means for human identification, has been used in many applications ranging from law enforcement and forensics to unlocking mobile phones. Despite its successful deployment, the fundamental premise of fingerprint-based identification—persistence and uniqueness of fingerprints—has not yet been well studied, resulting in challenges to the admissibility of friction ridge evidence in courts of law. This study investigates the tendency o...

  18. On speech recognition during anaesthesia

    OpenAIRE

    Alapetite, Alexandre

    2007-01-01

    This PhD thesis in human-computer interfaces (HCI, 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, in particular ergonomic issues and the fact that anaesthesiologists tend to postpone the registration of the medications and other events during b...

  19. Neural mechanisms for voice recognition

    OpenAIRE

    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 explicitly defined a voice-identity space. The predefined centre of the voice category was shifted from the acoustic centre each week in opposite directions, so the same stimuli had different training h...

  20. 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.

  1. Human recognition of familiar voices.

    Science.gov (United States)

    Wenndt, Stanley J

    2016-08-01

    Recognizing familiar voices is something we do every day. In quiet environments, it is usually easy to recognize a familiar voice. In noisier environments, this can become a difficult task. This paper examines how robust listeners are at identifying familiar voices in noisy, changing environments and what factors may affect their recognition rates. While there is previous research addressing familiar speaker recognition, the research is limited due to the difficulty in obtaining appropriate data that eliminates speaker dependent traits, such as word choice, along with having corresponding listeners who are familiar with the speakers. The data used in this study were collected in such a fashion to mimic conversational, free-flow dialogue, but in a way to eliminate many variables such as word choice, intonation, or non-verbal cues. These data provide some of the most realistic test scenarios to-date for familiar speaker identification. A pure-tone hearing test was used to separate listeners into normal hearing and hearing impaired groups. It is hypothesized that the results of the Normal Hearing Group will be statistically better. Additionally, the aspect of familiar speaker recognition is addressed by having each listener rate his or her familiarity with each speaker. Two statistical approaches showed that the more familiar a listener is with a speaker, the more likely the listener will recognize the speaker. PMID:27586746

  2. 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 ...... accuracy. Finally, the last part of the thesis looks at the acceptance and success of a speech recognition system introduced in a Danish hospital to produce patient records.......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...... inaccuracies in the anaesthesia record. Supplementing the electronic anaesthesia record interface with speech input facilities is proposed as one possible solution to a part of the problem. The testing of the various hypotheses has involved the development of a prototype of an electronic anaesthesia record...

  3. Face Recognition Incorporating Ancillary Information

    Directory of Open Access Journals (Sweden)

    Sangyoun Lee

    2007-11-01

    Full Text Available Due to vast variations of extrinsic and intrinsic imaging conditions, face recognition remained to be a challenging computer vision problem even today. This is particularly true when the passive imaging approach is considered for robust applications. To advance existing recognition systems for face, numerous techniques and methods have been proposed to overcome the almost inevitable performance degradation due to external factors such as pose, expression, occlusion, and illumination. In particular, the recent part-based method has provided noticeable room for verification performance improvement based on the localized features which have good tolerance to variation of external conditions. The part-based method, however, does not really stretch the performance without incorporation of global information from the holistic method. In view of the need to fuse the local information and the global information in an adaptive manner for reliable recognition, in this paper we investigate whether such external factors can be explicitly estimated and be used to boost the verification performance during fusion of the holistic and part-based methods. Our empirical evaluations show noticeable performance improvement adopting the proposed method.

  4. Infant Visual Attention and Object Recognition

    Science.gov (United States)

    Reynolds, Greg D.

    2015-01-01

    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. PMID:25596333

  5. 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

  6. The mate recognition protein gene mediates reproductive isolation and speciation in the Brachionus plicatilis cryptic species complex

    Directory of Open Access Journals (Sweden)

    Gribble Kristin E

    2012-08-01

    Full Text Available Abstract Background Chemically mediated prezygotic barriers to reproduction likely play an important role in speciation. In facultatively sexual monogonont rotifers from the Brachionus plicatilis cryptic species complex, mate recognition of females by males is mediated by the Mate Recognition Protein (MRP, a globular glycoprotein on the surface of females, encoded by the mmr-b gene family. In this study, we sequenced mmr-b copies from 27 isolates representing 11 phylotypes of the B. plicatilis species complex, examined the mode of evolution and selection of mmr-b, and determined the relationship between mmr-b genetic distance and mate recognition among isolates. Results Isolates of the B. plicatilis species complex have 1–4 copies of mmr-b, each composed of 2–9 nearly identical tandem repeats. The repeats within a gene copy are generally more similar than are gene copies among phylotypes, suggesting concerted evolution. Compared to housekeeping genes from the same isolates, mmr-b has accumulated only half as many synonymous differences but twice as many non-synonymous differences. Most of the amino acid differences between repeats appear to occur on the outer face of the protein, and these often result in changes in predicted patterns of phosphorylation. However, we found no evidence of positive selection driving these differences. Isolates with the most divergent copies were unable to mate with other isolates and rarely self-crossed. Overall the degree of mate recognition was significantly correlated with the genetic distance of mmr-b. Conclusions Discrimination of compatible mates in the B. plicatilis species complex is determined by proteins encoded by closely related copies of a single gene, mmr-b. While concerted evolution of the tandem repeats in mmr-b may function to maintain identity, it can also lead to the rapid spread of a mutation through all copies in the genome and thus to reproductive isolation. The mmr-b gene is evolving

  7. Iris Recognition Without Iris Normalization

    Directory of Open Access Journals (Sweden)

    Lenina Birgale

    2010-01-01

    Full Text Available Problem statement: In any real time biometric system processing speed and recognition time are crucial parameters. Reducing processing time involves many parameters like normalization, FAR, FRR, management of eyelid and eyelash occlusions, size of signature etc. Normalization consumes substantial amount of time of the system. This study contributes for improved iris recognition system with reduced processing time, False Acceptance Rate (FAR and False Rejection Rate (FRR. Approach: To improve system performance and reliability of a biometric system. It avoided the iris normalization process used traditionally in iris recognition systems. The technique proposed here used different masks to filter out iris image from an eye. Comparative study of different masks was done and optimized mask is proposed. The experiment was carried on CASIA database consisting of 756 iris images of 108 persons. Each person contributes seven images of eye (108×7 = 756 images in the database. Results: In the proposed method: (1 Normalization step is avoided; (2 Computational time is reduced by 0.3342 sec; (3 Iris signature size is reduced; (4 Improved performance parameters. (With reduced feature size, proposed method achieves 99.4866% accuracy, 0.0069% FAR, 1.0198% FRR and significant increase in speed of the system. Conclusion: Iris signature proposed was comparatively small just of 1×24 size. Though Daugman’s method gives best accuracy of 99.90% but the iris signature length used by that algorithm is comparatively very high that is 1×2048 phase vector. Also Daugman has used phase information in signature formation. Our method gives a accuracy of 99.474% with a signature of comparatively very small length. This has definitely contributed to improve the speed.

  8. 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

  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. Face Recognition using Gabor Filters

    Directory of Open Access Journals (Sweden)

    Sajjad MOHSIN

    2011-01-01

    Full Text Available An Elastic Bunch Graph Map (EBGM algorithm is being proposed in this research paper that successfully implements face recognition using Gabor filters. The proposed system applies 40 different Gabor filters on an image. As aresult of which 40 images with different angles and orientation are received. Next, maximum intensity points in each filtered image are calculated and mark them as Fiducial points. The system reduces these points in accordance to distance between them. The next step is calculating the distances between the reduced points using distance formula. At last, the distances are compared with database. If match occurs, it means that the image is recognized.

  11. Face Recognition Techniques - An evaluation Study

    Directory of Open Access Journals (Sweden)

    Dr.Asmahan M Altaher

    2015-01-01

    Full Text Available Face recognition is the ability of categorize a set of images based on certain discriminatory features. Classification of the recognition patterns can be difficult problem and it is still very active field of research. The paper introduces conceptual framework for descriptive study on techniques of face recognition systems. It aims to describe the previous researches have been study the face recognition system, in order scope on the algorithms, usages, benefits , challenges and problems in this felids, the paper proposed the face recognition as sensitive learning task experiments on a large face databases demonstrate of the new feature. The researcher recommends that there's a needs to evaluate the previous studies and researches, especially on face recognition field and 3D, hopeful for advanced techniques and methods in the near future.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Efficient Biometric Iris Recognition Using Hough Transform

    OpenAIRE

    Kriti Sharma*1,; Himanshu Monga2

    2014-01-01

    The demand for an accurate biometric system that provides reliable identification and verification of an individual has increased over the years. A biometric system that provides reliable and accurate identification of an individual is an iris recognition system. Iris recognition systems capture an image of an individual's eye; the iris in the image is then segmented and normalized for feature extraction process. The performance of iris recognition systems highly depends on se...

  17. SURVEY OF BIOMETRIC SYSTEMS USING IRIS RECOGNITION

    OpenAIRE

    S.PON SANGEETHA; DR.M.KARNAN

    2014-01-01

    The security plays an important role in any type of organization in today’s life. Iris recognition is one of the leading automatic biometric systems in the area of security which is used to identify the individual person. Biometric systems include fingerprints, facial features, voice recognition, hand geometry, handwriting, the eye retina and the most secured one presented in this paper, the iris recognition. Biometric systems has become very famous in security systems because it is not possi...

  18. Saliency-based object recognition in video

    OpenAIRE

    González-Díaz, Iván; Boujut, Hugo; Buso, Vincent; Benois-Pineau, Jenny; Domenger, Jean-Philippe

    2013-01-01

    10 pages In this paper we study the problem of object recognition in egocentric video recorded with cameras worn by persons. This task hasgained much attention during the last years, since it has turned tobe a main building block for action recognition systems in applications involving wearable cameras, such as tele-medicine or lifelogging. Under these scenarios, an action can be effectively definedas a sequence of manipulated or observed objects, so that recognition becomes a relevant stag...

  19. Enhanced Asymmetric Bilinear Model for Face Recognition

    OpenAIRE

    Wenjuan Gong; Weishan Zhang; Jordi Gonzàlez; Yan Ren; Zhen Li

    2015-01-01

    Bilinear models have been successfully applied to separate two factors, for example, pose variances and different identities in face recognition problems. Asymmetric model is a type of bilinear model which models a system in the most concise way. But seldom there are works exploring the applications of asymmetric bilinear model on face recognition problem with illumination changes. In this work, we propose enhanced asymmetric model for illumination-robust face recognition. Instead of initiali...

  20. Fingerprint Recognition Using Translation Invariant Scattering Network

    OpenAIRE

    Minaee, Shervin; Wang, Yao

    2015-01-01

    Fingerprint recognition has drawn a lot of attention during last decades. Different features and algorithms have been used for fingerprint recognition in the past. In this paper, a powerful image representation called scattering transform/network, is used for recognition. Scattering network is a convolutional network where its architecture and filters are predefined wavelet transforms. The first layer of scattering representation is similar to sift descriptors and the higher layers capture hi...

  1. Dynamic Programming Algorithms in Speech Recognition

    Directory of Open Access Journals (Sweden)

    Titus Felix FURTUNA

    2008-01-01

    Full Text Available In a system of speech recognition containing words, the recognition requires the comparison between the entry signal of the word and the various words of the dictionary. The problem can be solved efficiently by a dynamic comparison algorithm whose goal is to put in optimal correspondence the temporal scales of the two words. An algorithm of this type is Dynamic Time Warping. This paper presents two alternatives for implementation of the algorithm designed for recognition of the isolated words.

  2. 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.

  3. Online Sketch Recognition with Incremental Fuzzy Models

    OpenAIRE

    Tencer, Lukas; Režnáková, Marta; Cheriet, Mohamed

    2015-01-01

    In this paper, we present a novel method for recognition of handwritten sketches. Unlike previous approaches, we focus on online retrieval and ability to build our model incrementally, thus we do not need to know all the data in advance and we can achieve very good recognition results after as few as 15 samples. The method is composed of two main parts: feature representation and learning and recognition. In feature representation part, we utilize SIFT-like feature descriptors in combination ...

  4. Portable Facial Recognition Jukebox Using Fisherfaces (Frj)

    OpenAIRE

    Richard Mo; Adnan Shaout

    2016-01-01

    A portable real-time facial recognition system that is able to play personalized music based on the identified person’s preferences was developed. The system is called Portable Facial Recognition Jukebox Using Fisherfaces (FRJ). Raspberry Pi was used as the hardware platform for its relatively low cost and ease of use. This system uses the OpenCV open source library to implement the computer vision Fisherfaces facial recognition algorithms, and uses the Simple DirectMedia Layer (SDL) library ...

  5. Multispectral Palmprint Recognition Using a Quaternion Matrix

    OpenAIRE

    Yafeng Li; Changjiang Song; Xingpeng Xu; Zhenhua Guo

    2012-01-01

    Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, ...

  6. Object feature extraction and recognition model

    International Nuclear Information System (INIS)

    The characteristics of objects, especially flying objects, are analyzed, which include characteristics of spectrum, image and motion. Feature extraction is also achieved. To improve the speed of object recognition, a feature database is used to simplify the data in the source database. The feature vs. object relationship maps are stored in the feature database. An object recognition model based on the feature database is presented, and the way to achieve object recognition is also explained

  7. MEMBRAIN NEURAL NETWORK FOR VISUAL PATTERN RECOGNITION

    OpenAIRE

    Artur Popko; Marek Jakubowski; Rafał Wawer

    2013-01-01

    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...

  8. Visual Character Recognition using Artificial Neural Networks

    OpenAIRE

    Araokar, Shashank

    2005-01-01

    The recognition of optical characters is known to be one of the earliest applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In this paper, a simplified neural approach to recognition of optical or visual characters is portrayed and discussed. The document is expected to serve as a resource for learners and amateur investigators in pattern recognition, neural networking and related disciplines.

  9. Fusing Facial Features for Face Recognition

    OpenAIRE

    Jamal Ahmad Dargham; Ali Chekima; Ervin Gubin Moung

    2012-01-01

    Face recognition is an important biometric method because of its potential applications in many fields, such as access control, surveillance, and human-computer interaction. In this paper, a face recognition system that fuses the outputs of three face recognition systems based on Gabor jets is presented. The first system uses the magnitude, the second uses the phase, and the third uses the phase-weighted magnitude of the jets. The jets are generated from facial landmarks selected using three ...

  10. FACIAL EXPRESSION RECOGNITION BASED ON EDGE DETECTION

    OpenAIRE

    Chen, Xiaoming; Cheng, Wushan

    2015-01-01

    Relational Over the last two decades, the advances in computer vision and pattern recognition power have opened the door to new opportunity of automatic facial expression recognition system[1]. This paper use Canny edge detection method for facial expression recognition. Image color space transformation in the first place and then to identify and locate human face .Next pick up the edge of eyes and mouth's features extraction. Last we judge the facial expressions after compared wi...

  11. Biometric Iris Recognition Based on Hybrid Technique

    Directory of Open Access Journals (Sweden)

    Khattab M. Ali Alheeti

    2011-12-01

    Full Text Available Iris Recognition is one of the important biometric recognition systems that identify people based on theireyes and iris. In this paper the iris recognition algorithm is implemented via histogram equalization andwavelet techniques. In this paper the iris recognition approach is implemented via many steps, these stepsare concentrated on image capturing, enhancement and identification. Different types of edge detectionmechanisms; Canny scheme, Prewitt scheme, Roberts scheme and Sobel scheme are used to detect irisboundaries in the eyes digital image. The implemented system gives adequate results via different types ofiris images.

  12. Introduction to pattern recognition a MATLAB approach

    CERN Document Server

    Theodoridis, Sergios; Koutroumbas, Konstantinos; Cavouras, Dionisis

    2010-01-01

    An accompanying manual to Theodoridis/Koutroumbas, Pattern Recognition, that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. *Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition 4e.*Solved examples in Matlab, including real-life data sets in imaging and audio recognition*Available separately or at a special package price with the mai

  13. Man machine interface based on speech recognition

    International Nuclear Information System (INIS)

    This work reports the development of a Man Machine Interface based on speech recognition. The system must recognize spoken commands, and execute the desired tasks, without manual interventions of operators. The range of applications goes from the execution of commands in an industrial plant's control room, to navigation and interaction in virtual environments. Results are reported for isolated word recognition, the isolated words corresponding to the spoken commands. For the pre-processing stage, relevant parameters are extracted from the speech signals, using the cepstral analysis technique, that are used for isolated word recognition, and corresponds to the inputs of an artificial neural network, that performs recognition tasks. (author)

  14. Neural Network Based Hausa Language Speech Recognition

    Directory of Open Access Journals (Sweden)

    Matthew K Luka

    2012-05-01

    Full Text Available Speech recognition is a key element of diverse applications in communication systems, medical transcription systems, security systems etc. However, there has been very little research in the domain of speech processing for African languages, thus, the need to extend the frontier of research in order to port in, the diverse applications based on speech recognition. Hausa language is an important indigenous lingua franca in west and central Africa, spoken as a first or second language by about fifty million people. Speech recognition of Hausa Language is presented in this paper. A pattern recognition neural network was used for developing the system.

  15. Recent Advances in Robust Speech Recognition Technology

    CERN Document Server

    Ramírez, Javier

    2011-01-01

    This E-book is a collection of articles that describe advances in speech recognition technology. Robustness in speech recognition refers to the need to maintain high speech recognition accuracy even when the quality of the input speech is degraded, or when the acoustical, articulate, or phonetic characteristics of speech in the training and testing environments differ. Obstacles to robust recognition include acoustical degradations produced by additive noise, the effects of linear filtering, nonlinearities in transduction or transmission, as well as impulsive interfering sources, and diminishe

  16. End-Stop Exemplar Based Recognition

    DEFF Research Database (Denmark)

    Olsen, Søren I.

    2003-01-01

    An approach to exemplar based recognition of visual shapes is presented. The shape information is described by attributed interest points (keys) detected by an end-stop operator. The attributes describe the statistics of lines and edges local to the interest point, the position of neighboring int...... interest points, and (in the training phase) a list of recognition names. Recognition is made by a simple voting procedure. Preliminary experiments indicate that the recognition is robust to noise, small deformations, background clutter and partial occlusion....

  17. Kin-informative recognition cues in ants

    DEFF Research Database (Denmark)

    Nehring, Volker; Evison, Sophie E F; Santorelli, Lorenzo A;

    2011-01-01

    found little or no kin information in recognition cues. Here, we test the hypothesis that social insects do not have kin-informative recognition cues by investigating the recognition cues and relatedness of workers from four colonies of the ant Acromyrmex octospinosus. Contrary to the theoretical...... prediction, we show that the cuticular hydrocarbons of ant workers in all four colonies are informative enough to allow full-sisters to be distinguished from half-sisters with a high accuracy. These results contradict the hypothesis of non-heritable recognition cues and suggest that there is more potential...

  18. On Multiple Typeface Arabic Script Recognition

    Directory of Open Access Journals (Sweden)

    Abdelmalek Zidouri

    2010-08-01

    Full Text Available In this study, we propose a new sub-word segmentation and recognition scheme, which is independent of font size and font type. D ifferent ways of recognition are attempted namely Neural N et, template matching and principal component analysis. Results show that the real problem in Arabic character recognition remains the challenging separation of sub-words into characters. The system is realized in a modularized way. The combination of the different modules forms the basis of a complete Arabic OCR system. A successful preprocessing stage is reported. Unlike Latin based languages, recognition of printed Arabic characters remains an open field of research.

  19. 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.

  20. Innate immune recognition of cancer.

    Science.gov (United States)

    Woo, Seng-Ryong; Corrales, Leticia; Gajewski, Thomas F

    2015-01-01

    The observation that a subset of cancer patients show evidence for spontaneous CD8+ T cell priming against tumor-associated antigens has generated renewed interest in the innate immune pathways that might serve as a bridge to an adaptive immune response to tumors. Manipulation of this endogenous T cell response with therapeutic intent-for example, using blocking antibodies inhibiting PD-1/PD-L1 (programmed death-1/programmed death ligand 1) interactions-is showing impressive clinical results. As such, understanding the innate immune mechanisms that enable this T cell response has important clinical relevance. Defined innate immune interactions in the cancer context include recognition by innate cell populations (NK cells, NKT cells, and γδ T cells) and also by dendritic cells and macrophages in response to damage-associated molecular patterns (DAMPs). Recent evidence has indicated that the major DAMP driving host antitumor immune responses is tumor-derived DNA, sensed by the stimulator of interferon gene (STING) pathway and driving type I IFN production. A deeper knowledge of the clinically relevant innate immune pathways involved in the recognition of tumors is leading toward new therapeutic strategies for cancer treatment. PMID:25622193

  1. A Motivational Determinant of Facial Emotion Recognition: Regulatory Focus Affects Recognition of Emotions in Faces

    OpenAIRE

    Claudia Sassenrath; Kai Sassenberg; Devin G Ray; Katharina Scheiter; Halszka Jarodzka

    2014-01-01

    Two studies examined an unexplored motivational determinant of facial emotion recognition: observer regulatory focus. It was predicted that a promotion focus would enhance facial emotion recognition relative to a prevention focus because the attentional strategies associated with promotion focus enhance performance on well-learned or innate tasks - such as facial emotion recognition. In Study 1, a promotion or a prevention focus was experimentally induced and better facial emotion recognition...

  2. Global methods of pattern recognition

    International Nuclear Information System (INIS)

    Global methods of track finding and of parameter estimation require sufficient information to be available at a certain point on a particle trajectory. Then vector functions can be looked for such that in the space spanned by these functions each track forms a cluster of points which is well separated from the clusters of the other tracks. A clever detector lay-out can simplify this task. However, current wire chamber detectors do not provide either enough, or precise enough, measurements at points on curved trajectories to allow the application of global pattern recognition methods - improved detectors should not only provide precise coordinate measurements but also sufficiently precise measurements of the track direction. (orig.)

  3. 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...... different temporal actions using a probabilistic Edit Distance method. The method is tested on different actions with and without noise and the results show recognizing rates of 88.7% and 85.5%, respectively....

  4. Syllable Transposition Effects in Korean Word Recognition

    Science.gov (United States)

    Lee, Chang H.; Kwon, Youan; Kim, Kyungil; Rastle, Kathleen

    2015-01-01

    Research on the impact of letter transpositions in visual word recognition has yielded important clues about the nature of orthographic representations. This study investigated the impact of syllable transpositions on the recognition of Korean multisyllabic words. Results showed that rejection latencies in visual lexical decision for…

  5. Modeling video evolution for action recognition

    OpenAIRE

    Fernando, Basura; Gavves, Stratis; Oramas Mogrovejo, José Antonio; Ghodrati, Amir; Tuytelaars, Tinne

    2015-01-01

    Fernando B., Gavves E., Oramas Mogrovejo J., Ghodrati A., Tuytelaars T., ''Modeling video evolution for action recognition'', 28th IEEE conference on computer vision and pattern recognition - CVPR 2015, pp. 5378-5387, June 7-12, 2015, Boston, Massachusetts, USA.

  6. On fusion for multispectral iris recognition

    OpenAIRE

    Wild, Peter; Radu, Petru; Ferryman, James

    2015-01-01

    Multispectral iris recognition uses information from multiple bands of the electromagnetic spectrum to better represent certain physiological characteristics of the iris texture and enhance obtained recognition accuracy. This paper addresses the questions of single versus cross spectral performance and compares score-level fusion accuracy for different feature types, combining different wavelengths to overcome limitations in less constrained recording environments. Further it is investigated ...

  7. A Sociocultural Approach to Recognition and Learning

    Directory of Open Access Journals (Sweden)

    Peter Musaeus

    2006-04-01

    Full Text Available This is a case study of goldsmith craft apprenticeship learning and recognition. The study includes 13 participants in a goldsmith's workshop. The theoretical approach to recognition and learning is inspired by sociocultural theory. In this article recognition is defined with reference to Hegel’s understanding of the concept as a transformed struggle of granting acknowledgement to another person plus receiving acknowledgement as a person. It is argued that the notion of recognition can enhance sociocultural notions of learning. In analysing the case study of apprenticeship learning, the article suggests that recognition is expressed in the act of participants staking their lives to prove their autonomy, in work activity in terms of the role of artefacts and in the form of abstract and concrete recognition. Finally recognition is discussed in relation to learning and development. The study concludes that recognition is an important category not only to explain apprenticeship learning but also to give a sociocultural explanation of learning in general.

  8. Recognition hypermnesia: how to get it.

    Science.gov (United States)

    Bergstein, Jacquelyn; Erdelyi, Matthew

    2008-10-01

    Although recall hypermnesia (enhanced recall) over time with repeated testing has by now become an established empirical fact, its recognition counterpart, recognition hypermnesia, has defied clear-cut laboratory confirmation. In four studies, which relied on the retrieval component of recognition memory, it was shown that recognition memory, indexed by d', reliably improved over three successive recognition tests. The stimuli consisted of 140 cartoons, each comprising a picture and a verbal caption. Recognition memory was tested on transforms or part-forms (parts) of the original stimulus material (pictures only, verbal paraphrases of the pictures, the latent content of the cartoons, or the combination of paraphrases and latent contents). The strongest effects were obtained when the originally presented cartoons were tested on their latent (deep semantic) contents. Recognition hypermnesia for part-forms or transforms of earlier presented stimuli has potentially wide-ranging implications since real-world recognition--of faces, texts, visual scenes--usually involves recognising stimuli that are variants, not exact copies, of the originally encountered materials. PMID:18608979

  9. Parametric HMMs for Movement Recognition and Synthesis

    DEFF Research Database (Denmark)

    Herzog, Dennis; Krüger, Volker

    2009-01-01

    A common problem in human movement recognition is the recognition of movements of a particular type (semantic). E.g., grasping movements have a particular semantic (grasping) but the actual movements usually have very different appearances due to, e.g., different grasping directions. In this paper...

  10. Physiological arousal in processing recognition information

    Directory of Open Access Journals (Sweden)

    Guy Hochman

    2010-07-01

    Full Text Available The recognition heuristic (RH; Goldstein and Gigerenzer, 2002 suggests that, when applicable, probabilistic inferences are based on a noncompensatory examination of whether an object is recognized or not. The overall findings on the processes that underlie this fast and frugal heuristic are somewhat mixed, and many studies have expressed the need for considering a more compensatory integration of recognition information. Regardless of the mechanism involved, it is clear that recognition has a strong influence on choices, and this finding might be explained by the fact that recognition cues arouse affect and thus receive more attention than cognitive cues. To test this assumption, we investigated whether recognition results in a direct affective signal by measuring physiological arousal (i.e., peripheral arterial tone in the established city-size task. We found that recognition of cities does not directly result in increased physiological arousal. Moreover, the results show that physiological arousal increased with increasing inconsistency between recognition information and additional cue information. These findings support predictions derived by a compensatory Parallel Constraint Satisfaction model rather than predictions of noncompensatory models. Additional results concerning confidence ratings, response times, and choice proportions further demonstrated that recognition information and other cognitive cues are integrated in a compensatory manner.

  11. Quantum Pattern Recognition of Classical Signal

    OpenAIRE

    Pang, Chao-Yang; Ding, Cong-Bao; Hu, Ben-Qiong

    2007-01-01

    It's the key research topic of signal processing that recognizing genuine targets real time from the disturbed signal which has giant amount of data. A quantum algorithm for pattern recognition of classical signal which has time complexity O(sqrt(N)) is presented in this paper. Key Words: Pattern recognition, Grover's algorithm, Rotation on subspace

  12. Optical Pattern Recognition With Self-Amplification

    Science.gov (United States)

    Liu, Hua-Kuang

    1994-01-01

    In optical pattern recognition system with self-amplification, no reference beam used in addressing mode. Polarization of laser beam and orientation of photorefractive crystal chosen to maximize photorefractive effect. Intensity of recognition signal is orders of magnitude greater than other optical correlators. Apparatus regarded as real-time or quasi-real-time optical pattern recognizer with memory and reprogrammability.

  13. Acoustic Pattern Recognition on Android Devices

    DEFF Research Database (Denmark)

    Møller, Maiken Bjerg; Gaarsdal, Jesper; Steen, Kim Arild;

    2013-01-01

    an Android application developed for acoustic pattern recognition of bird species. The acoustic data is recorded using a built-in microphone, and pattern recognition is performed on the device, requiring no network connection. The algorithm is implemented in C++ as a native Android module and the OpenCV...

  14. Wood Variety Recognition on Mobile Devices

    Czech Academy of Sciences Publication Activity Database

    Vácha, Pavel; Haindl, Michal

    2013-01-01

    Roč. 2013, č. 93 (2013), s. 52-52. ISSN 0926-4981 R&D Projects: GA ČR GA102/08/0593 Institutional support: RVO:67985556 Keywords : wood recognition * Markov random fields Subject RIV: BD - Theory of Information http://library.utia.cas.cz/separaty/2013/RO/vacha-wood variety recognition on mobile devices.pdf

  15. Object Recognition Memory and the Rodent Hippocampus

    Science.gov (United States)

    Broadbent, Nicola J.; Gaskin, Stephane; Squire, Larry R.; Clark, Robert E.

    2010-01-01

    In rodents, the novel object recognition task (NOR) has become a benchmark task for assessing recognition memory. Yet, despite its widespread use, a consensus has not developed about which brain structures are important for task performance. We assessed both the anterograde and retrograde effects of hippocampal lesions on performance in the NOR…

  16. Dynamic recognition from ship-radiated noise

    Institute of Scientific and Technical Information of China (English)

    LI Xungao; FENG Xinxin; GE Yi

    2005-01-01

    On the basis of envelope spectrum analysis of ship-radiated noise, the features and the extracting methods are discussed, and then a new method of dynamic recognition has been proposed. Using this method, accurate recognition rate for different types of ship targets can be effectively improved, and some of the important parameters of target's movement can be obtained at the same time.

  17. Robotic CCD microscope for enhanced crystal recognition

    Science.gov (United States)

    Segelke, Brent W.; Toppani, Dominique

    2007-11-06

    A robotic CCD microscope and procedures to automate crystal recognition. The robotic CCD microscope and procedures enables more accurate crystal recognition, leading to fewer false negative and fewer false positives, and enable detection of smaller crystals compared to other methods available today.

  18. Invariant Face recognition Using Infrared Images

    International Nuclear Information System (INIS)

    Over the past few decades, face recognition has become a rapidly growing research topic due to the increasing demands in many applications of our daily life such as airport surveillance, personal identification in law enforcement, surveillance systems, information safety, securing financial transactions, and computer security. The objective of this thesis is to develop a face recognition system capable of recognizing persons with a high recognition capability, low processing time, and under different illumination conditions, and different facial expressions. The thesis presents a study for the performance of the face recognition system using two techniques; the Principal Component Analysis (PCA), and the Zernike Moments (ZM). The performance of the recognition system is evaluated according to several aspects including the recognition rate, and the processing time. Face recognition systems that use visual images are sensitive to variations in the lighting conditions and facial expressions. The performance of these systems may be degraded under poor illumination conditions or for subjects of various skin colors. Several solutions have been proposed to overcome these limitations. One of these solutions is to work in the Infrared (IR) spectrum. IR images have been suggested as an alternative source of information for detection and recognition of faces, when there is little or no control over lighting conditions. This arises from the fact that these images are formed due to thermal emissions from skin, which is an intrinsic property because these emissions depend on the distribution of blood vessels under the skin. On the other hand IR face recognition systems still have limitations with temperature variations and recognition of persons wearing eye glasses. In this thesis we will fuse IR images with visible images to enhance the performance of face recognition systems. Images are fused using the wavelet transform. Simulation results show that the fusion of visible and

  19. RECOGNITION OF HINDI (ARABIC HANDWRITTEN NUMERALS

    Directory of Open Access Journals (Sweden)

    Rawan I. Zaghloul

    2012-01-01

    Full Text Available Recognition of handwritten numerals has been one of the most challenging topics in image processing. This is due to its contributions in the automation process in several applications. The aim of this study was to build a classifier that can easily recognize offline handwritten Arabic numerals to support those applications that are deal with Hindi (Arabic numerals. A new algorithm for Hindi (Arabic Numeral Recognition is proposed. The proposed algorithm was developed using MATLAB and tested with a large sample of handwritten numeral datasets for different writers in different ages. Pattern recognition techniques are used to identify Hindi (Arabic handwritten numerals. After testing, high recognition rates were achieved, their ranges from 95% for some numerals and up to 99% for others. The proposed algorithm used a powerful set of features which proved to be effective in the recognition of Hindi (Arabic numerals.

  20. A new videotest for measuring emotion recognition ability

    OpenAIRE

    Dmitry Lyusin; Victoria Ovsyannikova

    2014-01-01

    A new measure for emotion recognition abilities, the Videotest of Emotion Recognition, is described. Two aspects in emotion recognition are distinguished, accuracy of recognition of emotion types that constitute the emotional state of the observed person and sensitivity to the intensity of the observed emotions. The Videotest of Emotion Recognition allows obtaining the accuracy and sensitivity indices that reflect these two aspects of emotion recognition. Psychometric analysis showed satisfac...

  1. Apply lightweight recognition algorithms in optical music recognition

    Science.gov (United States)

    Pham, Viet-Khoi; Nguyen, Hai-Dang; Nguyen-Khac, Tung-Anh; Tran, Minh-Triet

    2015-02-01

    The problems of digitalization and transformation of musical scores into machine-readable format are necessary to be solved since they help people to enjoy music, to learn music, to conserve music sheets, and even to assist music composers. However, the results of existing methods still require improvements for higher accuracy. Therefore, the authors propose lightweight algorithms for Optical Music Recognition to help people to recognize and automatically play musical scores. In our proposal, after removing staff lines and extracting symbols, each music symbol is represented as a grid of identical M ∗ N cells, and the features are extracted and classified with multiple lightweight SVM classifiers. Through experiments, the authors find that the size of 10 ∗ 12 cells yields the highest precision value. Experimental results on the dataset consisting of 4929 music symbols taken from 18 modern music sheets in the Synthetic Score Database show that our proposed method is able to classify printed musical scores with accuracy up to 99.56%.

  2. Robust video foreground segmentation and face recognition

    Institute of Scientific and Technical Information of China (English)

    GUAN Ye-peng

    2009-01-01

    Face recognition provides a natural visual interface for human computer interaction (HCI) applications.The process of face recognition,however,is inhibited by variations in the appearance of face images caused by changes in lighting,expression,viewpoint,aging and introduction of occlusion.Although various algorithms have been presented for face recognition,face recognition is still a very challenging topic.A novel approach of real time face recognition for HCI is proposed in the paper.In view of the limits of the popular approaches to foreground segmentation,wavelet multi-scale transform based background subtraction is developed to extract foreground objects.The optimal selection of the threshold is automatically determined,which does not require any complex supervised training or manual experimental calibration.A robust real time face recognition algorithm is presented,which combines the projection matrixes without iteration and kernel Fisher discriminant analysis (KFDA) to overcome some difficulties existing in the real face recognition.Superior performance of the proposed algorithm is demonstrated by comparing with other algorithms through experiments.The proposed algorithm can also be applied to the video image sequences of natural HCI.

  3. Novel acoustic features for speech emotion recognition

    Institute of Scientific and Technical Information of China (English)

    ROH Yong-Wan; KIM Dong-Ju; LEE Woo-Seok; HONG Kwang-Seok

    2009-01-01

    This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech. The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform (FFT) spectral entropy, delta FFT spectral entropy, Mel-frequency filter bank (MFB)spectral entropy, and Delta MFB spectral entropy. Spectral-based entropy features are simple. They reflect frequency characteristic and changing characteristic in frequency of speech. We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance. Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results, respectively.These scores are first obtained from a pattern recognition procedure. The pattern recognition phase uses the Gaussian mixture model (GMM). We classify the four emotional states as anger, sadness,happiness and neutrality. The proposed method is evaluated using 45 sentences in each emotion for 30 subjects, 15 males and 15 females. Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy, Zero Crossing Rate (ZCR),linear prediction coefficient (LPC), and pitch parameters. We demonstrate the effectiveness of the proposed approach. One of the proposed features, combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods. We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

  4. Low SNR Speech Recognition using SMKL

    Directory of Open Access Journals (Sweden)

    Qin Yuan

    2014-05-01

    Full Text Available While traditional speech recognition methods have achieved great success in a number of real word applications, their further applications to some difficult situations, such as Signal-to-Noise Ratio (SNR signal and local languages, are still limited by their shortcomings in adaption ability. In particular, their robustness to pronunciation level noise is not satisfied enough. To overcome these limitations, in this paper, we propose a novel speech recognition approach for low signal-to-noise ratio signal. The general steps for our speech recognition approach are composed of signal preprocessing, feature extraction and recognition with simple multiple kernel learning (SMKL method. Then the application of SMKL in speech recognition with low SNR is presented. We evaluate the proposed approach over a standard data set. The experimental results show that the performance of SMKL method for low SNR speech recognition is significantly higher than that of the method based on other popular approaches. Further, SMKL based method can be straightforwardly applied to recognition problem of large scale dataset, high dimension data, and a large amount of isomerism information.

  5. The coevolution of recognition and social behavior.

    Science.gov (United States)

    Smead, Rory; Forber, Patrick

    2016-01-01

    Recognition of behavioral types can facilitate the evolution of cooperation by enabling altruistic behavior to be directed at other cooperators and withheld from defectors. While much is known about the tendency for recognition to promote cooperation, relatively little is known about whether such a capacity can coevolve with the social behavior it supports. Here we use evolutionary game theory and multi-population dynamics to model the coevolution of social behavior and recognition. We show that conditional harming behavior enables the evolution and stability of social recognition, whereas conditional helping leads to a deterioration of recognition ability. Expanding the model to include a complex game where both helping and harming interactions are possible, we find that conditional harming behavior can stabilize recognition, and thereby lead to the evolution of conditional helping. Our model identifies a novel hypothesis for the evolution of cooperation: conditional harm may have coevolved with recognition first, thereby helping to establish the mechanisms necessary for the evolution of cooperation. PMID:27225673

  6. Textual emotion recognition for enhancing enterprise computing

    Science.gov (United States)

    Quan, Changqin; Ren, Fuji

    2016-05-01

    The growing interest in affective computing (AC) brings a lot of valuable research topics that can meet different application demands in enterprise systems. The present study explores a sub area of AC techniques - textual emotion recognition for enhancing enterprise computing. Multi-label emotion recognition in text is able to provide a more comprehensive understanding of emotions than single label emotion recognition. A representation of 'emotion state in text' is proposed to encompass the multidimensional emotions in text. It ensures the description in a formal way of the configurations of basic emotions as well as of the relations between them. Our method allows recognition of the emotions for the words bear indirect emotions, emotion ambiguity and multiple emotions. We further investigate the effect of word order for emotional expression by comparing the performances of bag-of-words model and sequence model for multi-label sentence emotion recognition. The experiments show that the classification results under sequence model are better than under bag-of-words model. And homogeneous Markov model showed promising results of multi-label sentence emotion recognition. This emotion recognition system is able to provide a convenient way to acquire valuable emotion information and to improve enterprise competitive ability in many aspects.

  7. 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.

  8. Efficient Interaction Recognition through Positive Action Representation

    Directory of Open Access Journals (Sweden)

    Tao Hu

    2013-01-01

    Full Text Available This paper proposes a novel approach to decompose two-person interaction into a Positive Action and a Negative Action for more efficient behavior recognition. A Positive Action plays the decisive role in a two-person exchange. Thus, interaction recognition can be simplified to Positive Action-based recognition, focusing on an action representation of just one person. Recently, a new depth sensor has become widely available, the Microsoft Kinect camera, which provides RGB-D data with 3D spatial information for quantitative analysis. However, there are few publicly accessible test datasets using this camera, to assess two-person interaction recognition approaches. Therefore, we created a new dataset with six types of complex human interactions (i.e., named K3HI, including kicking, pointing, punching, pushing, exchanging an object, and shaking hands. Three types of features were extracted for each Positive Action: joint, plane, and velocity features. We used continuous Hidden Markov Models (HMMs to evaluate the Positive Action-based interaction recognition method and the traditional two-person interaction recognition approach with our test dataset. Experimental results showed that the proposed recognition technique is more accurate than the traditional method, shortens the sample training time, and therefore achieves comprehensive superiority.

  9. Status of pattern recognition with wavelet analysis

    Institute of Scientific and Technical Information of China (English)

    Yuanyan TANG

    2008-01-01

    Pattern recognition has become one of the fastest growing research topics in the fields of computer science and electrical and electronic engineering in the recent years.Advanced research and development in pattern recognition have found numerous applications in such areas as artificial intelligence,information security,biometrics,military science and technology,finance and economics,weather forecast,image processing,communication,biomedical engineering,document processing,robot vision,transportation,and endless other areas,with many encouraging results.The achievement of pattern recognition is most likely to benefit from some new developments of theoretical mathematics including wavelet analysis.This paper aims at a brief survey of pattern recognition with the wavelet theory.It contains the following respects:analysis and detection of singularities with wavelets;wavelet descriptors for shapes of the objects;invariant representation of patterns;handwritten and printed character recognition;texture analysis and classification;image indexing and retrieval;classification and clustering;document analysis with wavelets;iris pattern recognition;face recognition using wavelet transform;hand gestures classification;character processing with B-spline wavelet transform;wavelet-based image fusion,and others.

  10. Recognition in a social symbiosis: chemical phenotypes and nestmate recognition behaviors of neotropical parabiotic ants.

    Directory of Open Access Journals (Sweden)

    Virginia J Emery

    Full Text Available Social organisms rank among the most abundant and ecologically dominant species on Earth, in part due to exclusive recognition systems that allow cooperators to be distinguished from exploiters. Exploiters, such as social parasites, manipulate their hosts' recognition systems, whereas cooperators are expected to minimize interference with their partner's recognition abilities. Despite our wealth of knowledge about recognition in single-species social nests, less is known of the recognition systems in multi-species nests, particularly involving cooperators. One uncommon type of nesting symbiosis, called parabiosis, involves two species of ants sharing a nest and foraging trails in ostensible cooperation. Here, we investigated recognition cues (cuticular hydrocarbons and recognition behaviors in the parabiotic mixed-species ant nests of Camponotus femoratus and Crematogaster levior in North-Eastern Amazonia. We found two sympatric, cryptic Cr. levior chemotypes in the population, with one type in each parabiotic colony. Although they share a nest, very few hydrocarbons were shared between Ca. femoratus and either Cr. levior chemotype. The Ca. femoratus hydrocarbons were also unusually long-chained branched alkenes and dienes, compounds not commonly found amongst ants. Despite minimal overlap in hydrocarbon profile, there was evidence of potential interspecific nestmate recognition -Cr. levior ants were more aggressive toward Ca. femoratus non-nestmates than Ca. femoratus nestmates. In contrast to the prediction that sharing a nest could weaken conspecific recognition, each parabiotic species also maintains its own aggressive recognition behaviors to exclude conspecific non-nestmates. This suggests that, despite cohabitation, parabiotic ants maintain their own species-specific colony odors and recognition mechanisms. It is possible that such social symbioses are enabled by the two species each using their own separate recognition cues, and that

  11. Recognition in a social symbiosis: chemical phenotypes and nestmate recognition behaviors of neotropical parabiotic ants.

    Science.gov (United States)

    Emery, Virginia J; Tsutsui, Neil D

    2013-01-01

    Social organisms rank among the most abundant and ecologically dominant species on Earth, in part due to exclusive recognition systems that allow cooperators to be distinguished from exploiters. Exploiters, such as social parasites, manipulate their hosts' recognition systems, whereas cooperators are expected to minimize interference with their partner's recognition abilities. Despite our wealth of knowledge about recognition in single-species social nests, less is known of the recognition systems in multi-species nests, particularly involving cooperators. One uncommon type of nesting symbiosis, called parabiosis, involves two species of ants sharing a nest and foraging trails in ostensible cooperation. Here, we investigated recognition cues (cuticular hydrocarbons) and recognition behaviors in the parabiotic mixed-species ant nests of Camponotus femoratus and Crematogaster levior in North-Eastern Amazonia. We found two sympatric, cryptic Cr. levior chemotypes in the population, with one type in each parabiotic colony. Although they share a nest, very few hydrocarbons were shared between Ca. femoratus and either Cr. levior chemotype. The Ca. femoratus hydrocarbons were also unusually long-chained branched alkenes and dienes, compounds not commonly found amongst ants. Despite minimal overlap in hydrocarbon profile, there was evidence of potential interspecific nestmate recognition -Cr. levior ants were more aggressive toward Ca. femoratus non-nestmates than Ca. femoratus nestmates. In contrast to the prediction that sharing a nest could weaken conspecific recognition, each parabiotic species also maintains its own aggressive recognition behaviors to exclude conspecific non-nestmates. This suggests that, despite cohabitation, parabiotic ants maintain their own species-specific colony odors and recognition mechanisms. It is possible that such social symbioses are enabled by the two species each using their own separate recognition cues, and that interspecific nestmate

  12. Iris recognition based on subspace analysis

    Directory of Open Access Journals (Sweden)

    Pravin S.Patil

    2014-10-01

    Full Text Available Biometrics deals with the uniqueness of an individual arising from their physiological or behavioral characteristics for the purpose of personal identification. Among many biometrics techniques, iris recognition is one of the most promising approache. This paper presents traditional subspace analysis method for iris recognition. Initially the eye images have been localized in circular form by using Daugman’s grid method and circular Hough transform method. The algorithms for subspace analysis methods namely PCA and LDA are implemented and experimental results are reported. The comparative performance for both the algorithms has been observed in term of recognition rate. The comprehensive experiments completed on UPOL and CASIA V1 iris databases.

  13. Robust speaker recognition in noisy environments

    CERN Document Server

    Rao, K Sreenivasa

    2014-01-01

    This book discusses speaker recognition methods to deal with realistic variable noisy environments. The text covers authentication systems for; robust noisy background environments, functions in real time and incorporated in mobile devices. The book focuses on different approaches to enhance the accuracy of speaker recognition in presence of varying background environments. The authors examine: (a) Feature compensation using multiple background models, (b) Feature mapping using data-driven stochastic models, (c) Design of super vector- based GMM-SVM framework for robust speaker recognition, (d) Total variability modeling (i-vectors) in a discriminative framework and (e) Boosting method to fuse evidences from multiple SVM models.

  14. Face Recognition Using Kernel Discriminant Analysis

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Linear Discrimiant Analysis (LDA) has demonstrated their success in face recognition. But LDA is difficult to handle the high nonlinear problems, such as changes of large viewpoint and illumination in face recognition. In order to overcome these problems, we investigate Kernel Discriminant Analysis (KDA) for face recognition. This approach adopts the kernel functions to replace the dot products of nonlinear mapping in the high dimensional feature space, and then the nonlinear problem can be solved in the input space conveniently without explicit mapping. Two face databases are used to test KDA approach. The results show that our approach outperforms the conventional PCA(Eigenface) and LDA(Fisherface) approaches.

  15. Real Time Implementation Of Face Recognition System

    Directory of Open Access Journals (Sweden)

    Megha Manchanda

    2014-10-01

    Full Text Available This paper proposes face recognition method using PCA for real time implementation. Nowadays security is gaining importance as it is becoming necessary for people to keep passwords in their mind and carry cards. Such implementations however, are becoming less secure and practical, also is becoming more problematic thus leading to an increasing interest in techniques related to biometrics systems. Face recognition system is amongst important subjects in biometrics systems. This system is very useful for security in particular and has been widely used and developed in many countries. This study aims to achieve face recognition successfully by detecting human face in real time, based on Principal Component Analysis (PCA algorithm.

  16. WCTFR : WRAPPING CURVELET TRANSFORM BASED FACE RECOGNITION

    Directory of Open Access Journals (Sweden)

    Arunalatha J S

    2015-03-01

    Full Text Available The recognition of a person based on biological features are efficient compared with traditional knowledge based recognition system. In this paper we propose Wrapping Curvelet Transform based Face Recognition (WCTFR. The Wrapping Curvelet Transform (WCT is applied on face images of database and test images to derive coefficients. The obtained coefficient matrix is rearranged to form WCT features of each image. The test image WCT features are compared with database images using Euclidean Distance (ED to compute Equal Error Rate (EER and True Success Rate (TSR. The proposed algorithm with WCT performs better than Curvelet Transform algorithms used in [1], [10] and [11].

  17. Fingertip Detection for Hand Pose Recognition

    Directory of Open Access Journals (Sweden)

    M.K. Bhuyan

    2012-03-01

    Full Text Available In this paper, a novel algorithm is proposed for fingertip detection and finger type recognition. The algorithm is applied for locating fingertips in hand region extracted by Bayesian rule based skincolor segmentation. Morphological operations are performed in the segmented hand region by observing key geometric features. A probabilistic modeling of the geometric features of finger movement has made the finger type recognition process significantly robust. Proposed method can be employed in a variety of applications like sign language recognition and human robot interactions.

  18. Knowledge Recognition Algorithm enables P = NP

    CERN Document Server

    Wen, Han Xiao

    2010-01-01

    This paper introduces a knowledge recognition algorithm (KRA) that is both a Turing machine algorithm and an Oracle Turing machine algorithm. By definition KRA is a non-deterministic language recognition algorithm. Simultaneously it can be implemented as a deterministic Turing machine algorithm. KRA applies mirrored perceptual-conceptual languages to learn member-class relations between the two languages iteratively and retrieve information through deductive and reductive recognition from one language to another. The novelty of KRA is that the conventional concept of relation is adjusted. The computation therefore becomes efficient bidirectional string mapping.

  19. Cortical networks for visual self-recognition

    International Nuclear Information System (INIS)

    This paper briefly reviews recent developments regarding the brain mechanisms of visual self-recognition. A special cognitive mechanism for visual self-recognition has been postulated based on behavioral and neuropsychological evidence, but its neural substrate remains controversial. Recent functional imaging studies suggest that multiple cortical mechanisms play self-specific roles during visual self-recognition, reconciling the existing controversy. Respective roles for the left occipitotemporal, right parietal, and frontal cortices in symbolic, visuospatial, and conceptual aspects of self-representation have been proposed. (author)

  20. Automatic speech recognition a deep learning approach

    CERN Document Server

    Yu, Dong

    2015-01-01

    This book summarizes the recent advancement in the field of automatic speech recognition with a focus on discriminative and hierarchical models. This will be the first automatic speech recognition book to include a comprehensive coverage of recent developments such as conditional random field and deep learning techniques. It presents insights and theoretical foundation of a series of recent models such as conditional random field, semi-Markov and hidden conditional random field, deep neural network, deep belief network, and deep stacking models for sequential learning. It also discusses practical considerations of using these models in both acoustic and language modeling for continuous speech recognition.

  1. Robust recognition via information theoretic learning

    CERN Document Server

    He, Ran; Yuan, Xiaotong; Wang, Liang

    2014-01-01

    This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy.The?authors?resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency,?the brief?introduces the additive and multip

  2. Hidden neural networks: application to speech recognition

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric

    1998-01-01

    We evaluate the hidden neural network HMM/NN hybrid on two speech recognition benchmark tasks; (1) task independent isolated word recognition on the Phonebook database, and (2) recognition of broad phoneme classes in continuous speech from the TIMIT database. It is shown how hidden neural networks...... (HNNs) with much fewer parameters than conventional HMMs and other hybrids can obtain comparable performance, and for the broad class task it is illustrated how the HNN can be applied as a purely transition based system, where acoustic context dependent transition probabilities are estimated by neural...... networks...

  3. FACE RECOGNITION BASED ON CUCKOO SEARCH ALGORITHM

    Directory of Open Access Journals (Sweden)

    VIPINKUMAR TIWARI

    2012-07-01

    Full Text Available Feature Selection is a optimization technique used in face recognition technology. Feature selection removes the irrelevant, noisy and redundant data thus leading to the more accurate recognition of face from the database.Cuckko Algorithm is one of the recent optimization algorithm in the league of nature based algorithm. Its optimization results are better than the PSO and ACO optimization algorithms. The proposal of applying the Cuckoo algorithm for feature selection in the process of face recognition is presented in this paper.

  4. Pattern recognition and classification an introduction

    CERN Document Server

    Dougherty, Geoff

    2012-01-01

    The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer visi

  5. Possibilistic clustering for shape recognition

    Science.gov (United States)

    Keller, James M.; Krishnapuram, Raghu

    1993-01-01

    Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, the clustering problem was cast into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. An appropriate objective function whose minimum will characterize a good possibilistic partition of the data was constructed, and the membership and prototype update equations from necessary conditions for minimization of our criterion function were derived. The ability of this approach to detect linear and quartic curves in the presence of considerable noise is shown.

  6. PATTER, Pattern Recognition Data Analysis

    International Nuclear Information System (INIS)

    1 - Description of program or function: PATTER is an interactive program with extensive facilities for modeling analytical processes and solving complex data analysis problems using statistical methods, spectral analysis, and pattern recognition techniques. PATTER addresses the type of problem generally stated as follows: given a set of objects and a list of measurements made on these objects, is it possible to find or predict a property of the objects which is not directly measurable but is known to define some unknown relationship? When employed intelligently, PATTER will act upon a data set in such a way it becomes apparent if useful information, beyond that already discerned, is contained in the data. 2 - Method of solution: In order to solve the general problem, PATTER contains preprocessing techniques to produce new variables that are related to the values of the measurements which may reduce the number of variables and/or reveal useful information about the 'obscure' property; display techniques to represent the variable space in some way that can be easily projected onto a two- or three-dimensional plot for human observation to see if any significant clustering of points occurs; and learning techniques based on both unsupervised and supervised methods, to extract as much information from the data as possible so that the optimum solution can be found

  7. Recognition of two great contemporaries

    Directory of Open Access Journals (Sweden)

    Milin Melita

    2015-01-01

    Full Text Available The common denominator in the careers of two contemporaries and great men, citizens of Austria-Hungary - Leoš Janáček and Sigmund Freud - was that, in spite of their status as outsiders, they managed to achieve well-deserved recognition. Both non-Germans, they had to surmount a number of obstacles in order to attain their professional goals. The Slavophile Janáček dreamed for a long time of success in Prague, which came at last in 1916, two years before a triumph in Vienna. Freud had serious difficulties in his academic career because of the strengthening of racial prejudices and national hatred which were especially marked at the end of the 19th century. After the dissolution of the Empire things changed for the better for the composer, whose works got an excellent reception in Austria and Germany, whereas the psychiatrist had to leave Vienna after the Anschluss. [Projekat Ministarstva nauke Republike Srbije, br. ON 177004: Serbian Musical Identities within Local and Global Frameworks: Traditions, Changes, Challenges

  8. Aircraft recognition and pose estimation

    Science.gov (United States)

    Hmam, Hatem; Kim, Jijoong

    2000-05-01

    This work presents a geometry based vision system for aircraft recognition and pose estimation using single images. Pose estimation improves the tracking performance of guided weapons with imaging seekers, and is useful in estimating target manoeuvres and aim-point selection required in the terminal phase of missile engagements. After edge detection and straight-line extraction, a hierarchy of geometric reasoning algorithms is applied to form line clusters (or groupings) for image interpretation. Assuming a scaled orthographic projection and coplanar wings, lateral symmetry inherent in the airframe provides additional constraints to further reject spurious line clusters. Clusters that accidentally pass all previous tests are checked against the original image and are discarded. Valid line clusters are then used to deduce aircraft viewing angles. By observing that the leading edges of wings of a number of aircraft of interest are within 45 to 65 degrees from the symmetry axis, a bounded range of aircraft viewing angles can be found. This generic property offers the advantage of not requiring the storage of complete aircraft models viewed from all aspects, and can handle aircraft with flexible wings (e.g. F111). Several aircraft images associated with various spectral bands (i.e. visible and infra-red) are finally used to evaluate the system's performance.

  9. Deformable templates for circle recognition

    International Nuclear Information System (INIS)

    An algorithm for the circle recognition, using deformable templates, was carried out and its performance was studied. The displacement of the points from circles and the presence of noise that appear in real situations were taken into account. The deformable templates algorithm is initialized by Hough transform, which performs a rough evaluation of parameters. However due to inefficiency of the standard Hough transform, a new fast Hough transform procedure was proposed with an automatic choice of the appropriate cut on histograms and handling of splitting peaks. Having the approximate number of arms and the corresponding initial values of the parameters from the Hough transform as input, a neural network finds circles with high resolution. To avoid getting stuck into local minima we decrease the interaction between the arms and use the simulated annealing procedure where the system is allowed to thermalize for a sequence of temperature according to the Boltzmann distribution. Besides we penalize the case in which an elastic circle stopped its evolution having not enough points on it. Simulated data were used to study the efficiency of the algorithm depending on such factors as the noise level, displacements of the points from circles, the number of points per circle and the distance between the centre of two overlapped circles. Results show the satisfactory robustness of our algorithm to background contaminations. Then this technique was successfully applied to real data obtained in Au-Pb interactions from the RICH detectors used in CERES/NA45 experiment

  10. New Similarity Measure for Shape Recognition

    Directory of Open Access Journals (Sweden)

    Grouche Lakhdar

    2013-03-01

    The first merit of this algorithm is the high-speed image processing, instead of using images it does operate on vectors. The second merit is the precise recognition of known geometries shapes even for arbitrary or complexes ones.

  11. Gabor wavelet associative memory for face recognition.

    Science.gov (United States)

    Zhang, Haihong; Zhang, Bailing; Huang, Weimin; Tian, Qi

    2005-01-01

    This letter describes a high-performance face recognition system by combining two recently proposed neural network models, namely Gabor wavelet network (GWN) and kernel associative memory (KAM), into a unified structure called Gabor wavelet associative memory (GWAM). GWAM has superior representation capability inherited from GWN and consequently demonstrates a much better recognition performance than KAM. Extensive experiments have been conducted to evaluate a GWAM-based recognition scheme using three popular face databases, i.e., FERET database, Olivetti-Oracle Research Lab (ORL) database and AR face database. The experimental results consistently show our scheme's superiority and demonstrate its very high-performance comparing favorably to some recent face recognition methods, achieving 99.3% and 100% accuracy, respectively, on the former two databases, exhibiting very robust performance on the last database against varying illumination conditions. PMID:15732406

  12. Wavelet based approach for facial expression recognition

    Directory of Open Access Journals (Sweden)

    Zaenal Abidin

    2015-03-01

    Full Text Available Facial expression recognition is one of the most active fields of research. Many facial expression recognition methods have been developed and implemented. Neural networks (NNs have capability to undertake such pattern recognition tasks. The key factor of the use of NN is based on its characteristics. It is capable in conducting learning and generalizing, non-linear mapping, and parallel computation. Backpropagation neural networks (BPNNs are the approach methods that mostly used. In this study, BPNNs were used as classifier to categorize facial expression images into seven-class of expressions which are anger, disgust, fear, happiness, sadness, neutral and surprise. For the purpose of feature extraction tasks, three discrete wavelet transforms were used to decompose images, namely Haar wavelet, Daubechies (4 wavelet and Coiflet (1 wavelet. To analyze the proposed method, a facial expression recognition system was built. The proposed method was tested on static images from JAFFE database.

  13. COMPARATIVE STUDY OF HAND GESTURE RECOGNITION SYSTEM

    Directory of Open Access Journals (Sweden)

    Rafiqul Zaman Khan

    2012-07-01

    Full Text Available Human imitation for his surrounding environment makes him interfere in every details of this great environment, hear impaired people are gesturing with each other for delivering a specific message, this method of communication also attracts human imitation attention to cast it on human-computer interaction. The faculty of vision based gesture recognition to be a natural, powerful, and friendly tool for supporting efficient interaction between human and machine. In this paper a review of recent hand gesture recognition systems is presented with description of hand gestures modelling, analysis and recognition. A comparative study included in this paper with focusing on different segmentation, features extraction and recognition tools, research advantages and drawbacks are provided as well.

  14. Support vector machine for automatic pain recognition

    Science.gov (United States)

    Monwar, Md Maruf; Rezaei, Siamak

    2009-02-01

    Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

  15. RGB-D-T based Face Recognition

    DEFF Research Database (Denmark)

    Nikisins, Olegs; Nasrollahi, Kamal; Greitans, Modris;

    2014-01-01

    Facial images are of critical importance in many real-world applications from gaming to surveillance. The current literature on facial image analysis, from face detection to face and facial expression recognition, are mainly performed in either RGB, Depth (D), or both of these modalities. But, such...... analyzes have rarely included Thermal (T) modality. This paper paves the way for performing such facial analyzes using synchronized RGB-D-T facial images by introducing a database of 51 persons including facial images of different rotations, illuminations, and expressions. Furthermore, a face recognition...... algorithm has been developed to use these images. The experimental results show that face recognition using such three modalities provides better results compared to face recognition in any of such modalities in most of the cases....

  16. BIOMETRIC RECOGNITION: A MODERN ERA FOR SECURITY

    Directory of Open Access Journals (Sweden)

    VIJAY DHIR,

    2010-08-01

    Full Text Available Many varieties of systems require some reliable recognition system that gives the identity of a person. There are many applications that need the identity of a person to operate such as ATM, Laptops, Access to buildings, cellular Phones & some sensitive security locations. In the absence of robust personal recognition schemes, these systems are vulnerable to the wiles of an impostor. Biometric recognition, or simply biometrics, refers to the automatic recognition of individuals based on their physiological and/or behavioral characteristics. By using biometrics it is possible to confirm or establish an ndividual’s identity based on “who she is”, rather than by “what she possesses” (e.g., an ID card or “what she remembers” (e.g., a password. In this paper, we give a brief overview of the field of biometrics and summarize some of its advantages, disadvantages, strengths, limitations, and related privacy concerns.

  17. History of Maternal Recognition of Pregnancy.

    Science.gov (United States)

    Bazer, Fuller W

    2015-01-01

    The mechanism for signaling pregnancy recognition is highly variable among species, and the signaling molecule itself varies between estrogens in pigs to chorionic gonadotrophin in primates. This chapter provides insight into the menstrual cycle of women and estrous cycles of rodents, dog, cat, pigs, sheep, rabbits, and marsupials, as well as the hormones required for pregnancy recognition. Pregnancy recognition involves specific hormones such as prolactin in rodents or interferons in ruminants and estrogens in pigs that in their own way ensure the maintenance of the corpus luteum and its secretion of progesterone which is the hormone of pregnancy. However, these pregnancy recognition signals may also modify gene expression in a cell-specific and temporal manner to ensure the growth and development of the conceptus. This chapter provides some historical aspects of the development of understanding of mechanisms for the establishment and maintenance of pregnancy in several species of mammals. PMID:26450492

  18. Modulation of pathogen recognition by autophagy

    Directory of Open Access Journals (Sweden)

    Ji Eun eOh

    2012-03-01

    Full Text Available Autophagy is an ancient biological process for maintaining cellular homeostasis by degradation of long-lived cytosolic proteins and organelles. Recent studies demonstrated that autophagy is availed by immune cells to regulate innate immunity. On the one hand, cells exert direct effector function by degrading intracellular pathogens; on the other hand, autophagy modulates pathogen recognition and downstream signaling for innate immune responses. Pathogen recognition via pattern recognition receptors induces autophagy. The function of phagocytic cells is enhanced by recruitment of autophagy-related proteins. Moreover, autophagy acts as a delivery system for viral replication complexes to migrate to the endosomal compartments where virus sensing occurs. In another case, key molecules of the autophagic pathway have been found to negatively regulate immune signaling, thus preventing aberrant activation of cytokine production and consequent immune responses. In this review, we focus on the recent advances in the role of autophagy in pathogen recognition and modulation of innate immune responses.

  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. Fuzzy Neural Model for Flatness Pattern Recognition

    Institute of Scientific and Technical Information of China (English)

    JIA Chun-yu; SHAN Xiu-ying; LIU Hong-min; NIU Zhao-ping

    2008-01-01

    For the problems occurring in a least square method model,a fuzzy model,and a neural network model for flatness pattern recognition,a fuzzy neural network model for flatness pattern recognition with only three-input and three-output signals was proposed with Legendre orthodoxy polynomial as basic pattern,based on fuzzy logic expert experiential knowledge and genetic-BP hybrid optimization algorithm.The model not only had definite physical meanings in its inner nodes,but also had strong self-adaptability,anti-interference ability,high recognition precision,and high velocity,thereby meeting the demand of high-precision flatness control for cold strip mill and providing a convenient,practical,and novel method for flatness pattern recognition.

  1. Gesture Recognition for an Exergame Prototype

    OpenAIRE

    Gacem, Brahim; Vergouw, Robert; Verbiest, Harm; Cicek, Emrullah; Van Oosterhout, Tim; Bakkes, Sander; Kröse, Ben

    2011-01-01

    We will demonstrate a prototype exergame aimed at the serious domain of elderly fitness. The exergame incorporates straightforward means to gesture recognition, and utilises a Kinect camera to obtain 2.5D sensory data of the human user.

  2. Temporal visual cues aid speech recognition

    DEFF Research Database (Denmark)

    Zhou, Xiang; Ross, Lars; Lehn-Schiøler, Tue;

    2006-01-01

    temporal synchronicity of the visual input that aids parsing of the auditory stream. More specifically, we expected that purely temporal information, which does not convey information such as place of articulation may facility word recognition. METHODS: To test this prediction we used temporal features of......BACKGROUND: It is well known that under noisy conditions, viewing a speaker's articulatory movement aids the recognition of spoken words. Conventionally it is thought that the visual input disambiguates otherwise confusing auditory input. HYPOTHESIS: In contrast we hypothesize that it is the...... audio to generate an artificial talking-face video and measured word recognition performance on simple monosyllabic words. RESULTS: When presenting words together with the artificial video we find that word recognition is improved over purely auditory presentation. The effect is significant (p...

  3. 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...

  4. Automatic modulation recognition of communication signals

    CERN Document Server

    Azzouz, Elsayed Elsayed

    1996-01-01

    Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent years, interest from the academic and military research institutes has focused around the research and development of modulation recognition algorithms. Any communication intelligence (COMINT) system comprises three main blocks: receiver front-end, modulation recogniser and output stage. Considerable work has been done in the area of receiver front-ends. The work at the output stage is concerned with information extraction, recording and exploitation and begins with signal demodulation, that requires accurate knowledge about the signal modulation type. There are, however, two main reasons for knowing the current modulation type of a signal; to preserve the signal information content and to decide upon the suitable counter action, such as jamming. Automatic Modulation Recognition of Communications Signals describes in depth this modulation recognition process. Drawing on several years of research, the authors provide a cr...

  5. Kannada Character Recognition System A Review

    CERN Document Server

    Indira, K

    2010-01-01

    Intensive research has been done on optical character recognition ocr and a large number of articles have been published on this topic during the last few decades. Many commercial OCR systems are now available in the market, but most of these systems work for Roman, Chinese, Japanese and Arabic characters. There are no sufficient number of works on Indian language character recognition especially Kannada script among 12 major scripts in India. This paper presents a review of existing work on printed Kannada script and their results. The characteristics of Kannada script and Kannada Character Recognition System kcr are discussed in detail. Finally fusion at the classifier level is proposed to increase the recognition accuracy.

  6. An Efficient Gait Recognition with Backpack Removal

    Science.gov (United States)

    Lee, Heesung; Hong, Sungjun; Kim, Euntai

    2009-12-01

    Gait-based human identification is a paradigm to recognize individuals using visual cues that characterize their walking motion. An important requirement for successful gait recognition is robustness to variations including different lighting conditions, poses, and walking speed. Deformation of the gait silhouette caused by objects carried by subjects also has a significant effect on the performance of gait recognition systems; a backpack is the most common of these objects. This paper proposes methods for eliminating the effect of a carried backpack for efficient gait recognition. We apply simple, recursive principal component analysis (PCA) reconstructions and error compensation to remove the backpack from the gait representation and then conduct gait recognition. Experiments performed with the CASIA database illustrate the performance of the proposed algorithm.

  7. HMM based Korean Named Entity Recognition

    Directory of Open Access Journals (Sweden)

    Yi-Gyu Hwang

    2003-02-01

    Full Text Available In this paper, we present a named entity recognition model for Korean Language. Named entity recognition is an essential and important process of Question Answering and Information Extraction system. This paper proposes a HMM based named entity recognition using compound word construction principles. In Korean, above 60% of NE (Named-Entity is a compound word. This compound word may be consisted of proper noun, common noun, or bound noun, etc. There is an intercontextual relationship among nouns which consists NE. NE and surrounding words of NE have a contextual relationship. For considering these relationships, we classified nouns into 4 word classes (Independent Entity, Constituent Entity, Adjacent Entity, Not an Entity. With this classification, our system gets contextual and lexical information by stochastic based machine leaning method from a NE labeled training data. Experimental result shows that this approach is better approach than rulebased in the Korean named-entity recognition.

  8. 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

  9. Real object recognition using moment invariants

    Indian Academy of Sciences (India)

    Muharrem Mercimek; Kayhan Gulez; Tarik Veli Mumcu

    2005-12-01

    Moments and functions of moments have been extensively employed as invariant global features of images in pattern recognition. In this study, a flexible recognition system that can compute the good features for high classification of 3-D real objects is investigated. For object recognition, regardless of orientation, size and position, feature vectors are computed with the help of nonlinear moment invariant functions. Representations of objects using two-dimensional images that are taken from different angles of view are the main features leading us to our objective. After efficient feature extraction, the main focus of this study, the recognition performance of classifiers in conjunction with moment–based feature sets, is introduced.

  10. When Face Recognition Meets with Deep Learning: an Evaluation of Convolutional Neural Networks for Face Recognition

    OpenAIRE

    Hu, G.; Yang, Y.; Yi, D.; Kittler, J.; Christmas, WJ; S. Li; Hospedales, T

    2015-01-01

    Deep learning, in particular Convolutional Neural Network (CNN), has achieved promising results in face recognition recently. However, it remains an open question: why CNNs work well and how to design a ‘good’ architecture. The existing works tend to focus on reporting CNN architectures that work well for face recognition rather than investigate the reason. In this work, we conduct an extensive evaluation of CNN-based face recognition systems (CNN-FRS) on a common ground to make our work easi...

  11. RECIPE RECOGNITION WITH LARGE MULTIMODAL FOOD DATASET

    OpenAIRE

    Wang, Xin; Kumar, Devinder; Thome, Nicolas; Cord, Matthieu; Precioso, Frederic

    2015-01-01

    This paper deals with automatic systems for image recipe recognition. For this purpose, we compare and evaluate leading vision-based and text-based technologies on a new very large multimodal dataset (UPMC Food-101) containing about 100,000 recipes for a total of 101 food categories. Each item in this dataset is represented by one image plus textual information. We present deep experiments of recipe recognition on our dataset using visual, textual information and fusion. Additionally, we pres...

  12. Iris recognition based on subspace analysis

    OpenAIRE

    Pravin S.Patil

    2014-01-01

    Biometrics deals with the uniqueness of an individual arising from their physiological or behavioral characteristics for the purpose of personal identification. Among many biometrics techniques, iris recognition is one of the most promising approache. This paper presents traditional subspace analysis method for iris recognition. Initially the eye images have been localized in circular form by using Daugman’s grid method and circular Hough transform method. The algorithms for subspace analy...

  13. IRIS Biometric Recognition System Employing Canny Operator

    OpenAIRE

    Binsu C. Kovoor; Supriya M.H.; K Poulose Jacob

    2013-01-01

    Biometrics has become important in security applica tions. In comparison with many other biometric features, iris recognition has very high recognition accuracy because it depends on iris which is located in a place that still stable throughout human life and the probability to find two identical iris's is close to zero. The identifi cation system consists of several stages including segmentation stage which is the most serious and ...

  14. Structured Occlusion Coding for Robust Face Recognition

    OpenAIRE

    Wen, Yandong; Liu, Weiyang; Yang, Meng; Fu, Yuli; Xiang, Youjun; Hu, Rui

    2015-01-01

    Occlusion in face recognition is a common yet challenging problem. While sparse representation based classification (SRC) has been shown promising performance in laboratory conditions (i.e. noiseless or random pixel corrupted), it performs much worse in practical scenarios. In this paper, we consider the practical face recognition problem, where the occlusions are predictable and available for sampling. We propose the structured occlusion coding (SOC) to address occlusion problems. The struct...

  15. Fuzzy rule-based hand gesture recognition

    OpenAIRE

    Bedregal, Benjamín C.; Costa, Antônio Carlos da Rocha; Dimuro, Graçaliz P.

    2006-01-01

    This paper introduces a fuzzy rule-based method for the recognition of hand gestures acquired from a data glove, with an application to the recognition of some sample hand gestures of LIBRAS, the Brazilian Sign Language. The method uses the set of angles of finger joints for the classification of hand configurations, and classifications of segments of hand gestures for recognizing gestures. The segmentation of gestures is based on the concept of monotonic gesture segment, sequences of hand co...

  16. Parallel Application Library for Object Recognition

    OpenAIRE

    Su, Bor-Yiing

    2012-01-01

    Computer vision research enables machines to understand the world. Humans usually interpret and analyze the world through what they see - the objects they capture with their eyes. Similarly, machines can better understand the world by recognizing objects in images. Object recognition is therefore a major branch of computer vision. To achieve the highest accuracy, state-of-the-art object recognition systems must extract features from hundreds to millions of images, train models with enormous d...

  17. Edge Detection for Pattern Recognition: A Survey

    OpenAIRE

    James, Alex Pappachen

    2016-01-01

    This review provides an overview of the literature on the edge detection methods for pattern recognition that inspire from the understanding of human vision. We note that edge detection is one of the most fundamental process within the low level vision and provides the basis for the higher level visual intelligence in primates. The recognition of the patterns within the images relate closely to the spatiotemporal processes of edge formations, and its implementation needs a crossdisciplanry ap...

  18. Recognition from collections of local features

    OpenAIRE

    Babaryka, Anna

    2012-01-01

    An image matching system for object recognition in scenes of varying complexity was constructed in Matlab for evaluating the recognition quality of two types of image features: SURF (Speeded-Up Robust Features) and SIFT (Scale Invariant Feature Transform) using the affine Hough matching algorithm for finding matches between training and test images. In the experimental part of the thesis, the matching was algorithm tested for varying number of image features extracted from the train and test ...

  19. Robust Facial Expression Recognition via Compressive Sensing

    OpenAIRE

    Shiqing Zhang; Xiaoming Zhao; Bicheng Lei

    2012-01-01

    Recently, compressive sensing (CS) has attracted increasing attention in the areas of signal processing, computer vision and pattern recognition. In this paper, a new method based on the CS theory is presented for robust facial expression recognition. The CS theory is used to construct a sparse representation classifier (SRC). The effectiveness and robustness of the SRC method is investigated on clean and occluded facial expression images. Three typical facial features, i.e., the raw pixels, ...

  20. AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION

    OpenAIRE

    K.Meena; A. Suruliandi; R. Reena Rose

    2013-01-01

    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 Filteri...

  1. Biologically inspired emotion recognition from speech

    OpenAIRE

    Buscicchio Cosimo; Caponetti Laura; Castellano Giovanna

    2011-01-01

    Abstract Emotion recognition has become a fundamental task in human-computer interaction systems. In this article, we propose an emotion recognition approach based on biologically inspired methods. Specifically, emotion classification is performed using a long short-term memory (LSTM) recurrent neural network which is able to recognize long-range dependencies between successive temporal patterns. We propose to represent data using features derived from two different models: mel-frequency ceps...

  2. A Survey on Human Ear Recognition

    OpenAIRE

    Suvarnsing Bhable; Sangramsing Kayte,

    2015-01-01

    This paper presents an efficient ear recognition technique which derives benefits from the local features of the ear and attempt to handle the problems due to pose, poor contrast, change in illumination and lack of registration. Recognizing humans by their ear have recently received significant attention in the field of research. Ear is the rich in characteristics. This paper provides a detailed survey of research done in ear detection and recognition. This survey paper is very us...

  3. RECOGNITION OF PROFESSIONAL QUALIFICATIONS FROM LEARNING ONLINE

    OpenAIRE

    Alfredo Soeiro

    2014-01-01

    A methodology is proposed to address the recognition of competences acquired online. It is derived from the project VIRQUAL (http://virqual.up.pt) outputs. It addresses current issues of the working world like Virtual Mobility, Learning Outcomes, e-Assessment, Qualification Frameworks and Recognition of Prior Learning. The approach is based on the application of proper methods of assessment for each type of learning outcomes. A matrix is proposed to align the different types of competences (b...

  4. Real Time Implementation Of Face Recognition System

    OpenAIRE

    Megha Manchanda

    2014-01-01

    This paper proposes face recognition method using PCA for real time implementation. Nowadays security is gaining importance as it is becoming necessary for people to keep passwords in their mind and carry cards. Such implementations however, are becoming less secure and practical, also is becoming more problematic thus leading to an increasing interest in techniques related to biometrics systems. Face recognition system is amongst important subjects in biometrics systems. This ...

  5. Effect of Face Tampering on Face Recognition

    OpenAIRE

    Aruni Singh; Sanjay Kumar Singh

    2013-01-01

    Modern face recognition systems are vulnerable to spoofing attack. Spoofing attack occurs when a persontries to cheat the system by presenting fake biometric data gaining unlawful access. A lot of researchershave originated novel techniques to fascinate these types of face tampering attack. It seems that nocomparative studies of different face recognition algorithms on same protocols and fake data have beenincorporated. The motivation behind this paper is to present the effect of face tamperi...

  6. DWT BASED HMM FOR FACE RECOGNITION

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A novel Discrete Wavelet Transform (DWT) based Hidden Markov Module (HMM) for face recognition is presented in this letter. To improve the accuracy of HMM based face recognition algorithm, DWT is used to replace Discrete Cosine Transform (DCT) for observation sequence extraction. Extensive experiments are conducted on two public databases and the results show that the proposed method can improve the accuracy significantly, especially when the face database is large and only few training images are available.

  7. Pattern recognition in interdisciplinary perception and intelligence

    OpenAIRE

    Fernández-Caballero, Antonio; Sanfeliu, Alberto; Shirai, Yoshiaki

    2008-01-01

    At present, Pattern Recognition is in almost all the areas of Perception, where vision systems are probably the most known, and they are used in biometrics, industry, medicine, space, robotics, natural science, etc. Although that, speech recognition systems have also became very popular for interactive helping systems in telephonic systems. During the last years, multimodal human interaction has increased attention due to the necessity of tools for human-robot interaction in dynamic and chang...

  8. SWIVEL AND WET FINGERPRINT RECOGNITION TECHNIQUE

    OpenAIRE

    Dr. Raman Chadha; Iram Shah; Priya Thakur

    2016-01-01

    This paper assesses the effects of prolonged exposure of fingers to water on the performance of existing fingerprint recognition systems.Many fingers wrinkle or dwindle when immersed in water .When used for biometric identification; recognition rate for wrinkled fingers degrades. Apart from this the existing techniques used are not rotation invariant and fail when enrolled image of a person is matched with a rotated test image .The influence of wrinkling and rotated finger prints has so far n...

  9. Dynamic Automatic Noisy Speech Recognition System (DANSR)

    OpenAIRE

    Paul, Sheuli

    2014-01-01

    In this thesis we studied and investigated a very common but a long existing noise problem and we provided a solution to this problem. The task is to deal with different types of noise that occur simultaneously and which we call hybrid. Although there are individual solutions for specific types one cannot simply combine them because each solution affects the whole speech. We developed an automatic speech recognition system DANSR ( Dynamic Automatic Noisy Speech Recognition System) for hybri...

  10. Pattern recognition using linguistic fuzzy logic predictors

    Science.gov (United States)

    Habiballa, Hashim

    2016-06-01

    The problem of pattern recognition has been solved with numerous methods in the Artificial Intelligence field. We present an unconventional method based on Lingustic Fuzzy Logic Forecaster which is primarily used for the task of time series analysis and prediction through logical deduction wtih linguistic variables. This method should be used not only to the time series prediction itself, but also for recognition of patterns in a signal with seasonal component.

  11. Perceptual Recognition of Arabic Literal Amounts

    OpenAIRE

    Labiba Souici Meslati; Mokhtar Sellami

    2012-01-01

    Since humans are the best readers, one of the most promising trends in automatic handwriting recognition is to get inspiration from psychological reading models. The underlying idea is to derive benefits from studies of human reading, in order to build efficient automatic reading systems. In this context, we propose a human reading inspired system for the recognition of Arabic handwritten literalamounts. Our approach is based on the McClelland and Rumelhart's neural model called IAM, which is...

  12. Recognition Inventories in Governmental Sector Accounting

    OpenAIRE

    Nataliya Pryadka

    2013-01-01

    The Study covers the research of conditions for recognition of inventories in the governmental sector accounting. The comparative analysis has been performed as to the inventories recognition criteria provided by the National Accounting Provisions (Standards) 123 in the public sector - 'Inventories', Accounting Provision (Standard) 9 - 'Inventories', International Accounting Standard 16 - 'Inventories' in the public sector. It has been found that the common characteristic, in accordance with ...

  13. A New Database for Speaker Recognition

    OpenAIRE

    Feng, Ling; Hansen, Lars Kai

    2005-01-01

    In this paper we discuss properties of speech databases used for speaker recognition research and evaluation, and we characterize some popular standard databases. The paper presents a new database called ELSDSR dedicated to speaker recognition applications. The main characteristics of this database are: English spoken by non-native speakers, a single session of sentence reading and relatively extensive speech samples suitable for learning person specific speech characteristics.

  14. A New Database for Speaker Recognition

    DEFF Research Database (Denmark)

    Feng, Ling; Hansen, Lars Kai

    2005-01-01

    In this paper we discuss properties of speech databases used for speaker recognition research and evaluation, and we characterize some popular standard databases. The paper presents a new database called ELSDSR dedicated to speaker recognition applications. The main characteristics of this database...... are: English spoken by non-native speakers, a single session of sentence reading and relatively extensive speech samples suitable for learning person specific speech characteristics....

  15. Building planning action models using activity recognition

    OpenAIRE

    Ortiz Laguna, Javier

    2014-01-01

    Activity recognition is receiving a special attention because it can be used in many areas. This field of artificial intelligence has been widely investigated lately for tasks such as following the behavior of people with some kind of cognitive impairment. For instance, elderly people with dementia. The recognition of the activities that these people carry on permits to offer assistance in case they need it while they are performing the activities. Currently, there are many systems capable of...

  16. Survey on Human Face Expression Recognition

    OpenAIRE

    Atul Chinchamalatpure; Prof. Anurag Jain

    2014-01-01

    Facial expression recognition plays an important and effective role in the interaction in Human. There are seven basic facial expressions namely fear, surprise, happy, sad, disgust, Neutral and anger. Facial Expression Recognition is process performed by computers which consist of detect the face in the image and pre-process the face region, extracting facial expression features from image by analyzing the motion of facial features or change in the appearance of facial features and classifyin...

  17. Facial Expression Recognition Using SVM Classifier

    OpenAIRE

    Vasanth P.C.; Nataraj. K. R

    2015-01-01

    Facial feature tracking and facial actions recognition from image sequence attracted great attention in computer vision field. Computational facial expression analysis is a challenging research topic in computer vision. It is required by many applications such as human-computer interaction, computer graphic animation and automatic facial expression recognition. In recent years, plenty of computer vision techniques have been developed to track or recognize the facial activities in three levels...

  18. Configural processing in face recognition in schizophrenia

    OpenAIRE

    Schwartz, Barbara L.; Marvel, Cherie L.; Drapalski, Amy; Rosse, Richard B.; Deutsch, Stephen I.

    2002-01-01

    Introduction. There is currently substantial literature to suggest that patients with schizophrenia are impaired on many face-processing tasks. This study investigated the specific effects of configural changes on face recognition in groups of schizophrenia patients. Methods. In Experiment 1, participants identified facial expressions in upright faces and in faces inverted from their upright orientation. Experiments 2 and 3 examined recognition memory for faces and other non-face objects pres...

  19. Face Behavior Recognition Through Support Vector Machines

    OpenAIRE

    Haval A. Ahmed; Tarik A. Rashid; Ahmed T. Sadiq

    2016-01-01

    Communication between computers and humans has grown to be a major field of research. Facial Behavior Recognition through computer algorithms is a motivating and difficult field of research for establishing emotional interactions between humans and computers. Although researchers have suggested numerous methods of emotion recognition within the literature of this field, as yet, these research works have mainly focused on one method for their system output i.e. used one facial database for ass...

  20. Robust Palm Vein Recognition Using LMKNCN Classification

    OpenAIRE

    M. Senthil Kumar,; Gayathri, R.

    2014-01-01

    This paper presents a novel approach to improve the recognition percentage of palm-vascular-based authentication systems presented in the literature. The proposed method efficiently accommodates the rotational, translational changes and potential deformations by encoding the orientation preserving features. The proposed palm-vein approach is compared with other existing methods and obtained an improved performance in both verification and recognition scenarios. The experimenta...

  1. Fingerprint Recognition Using Minutia Score Matching

    OpenAIRE

    Ravi. J; K B Raja; Venugopal K R2

    2010-01-01

    The popular Biometric used to authenticate a person is Fingerprint which is unique and permanent throughout a person’s life. A minutia matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. In this paper we projected Fingerprint Recognition using Minutia Score Matching method (FRMSM). For Fingerprint thinning, the Block Filter is used, which scans the image at the boundary to preserves the quality of the image and extract the minutiae ...

  2. Fingerprint recognition using standardized fingerprint model

    OpenAIRE

    Le Hoang Thai; Ha Nhat Tam

    2011-01-01

    Fingerprint recognition is one of most popular and accuracy Biometric technologies. Nowadays, it is used in many real applications. However, recognizing fingerprints in poor quality images is still a very complex problem. In recent years, many algorithms, models are given to improve the accuracy of recognition system. This paper discusses on the standardized fingerprint model which is used to synthesize the template of fingerprints. In this model, after pre-processing step, we find the transf...

  3. Emotion recognition (sometimes) depends on horizontal orientations

    OpenAIRE

    Huynh, Carol M; Balas, Benjamin

    2014-01-01

    Face recognition depends critically on horizontal orientations (Goffaux & Dakin, 2010). Face images that lack horizontal features are harder to recognize than those that have that information preserved. Presently, we asked if facial emotional recognition also exhibits this dependency by asking observers to categorize orientation-filtered happy and sad expressions. Furthermore, we aimed to dissociate image-based orientation energy from object-based orientation by rotating images 90-degrees in ...

  4. Face recognition in controlled access points

    OpenAIRE

    Mur Escartín, Olga

    2009-01-01

    The thesis consist in the study and evaluation of different methods for face recognition. The final objective is to select the most suitable techniques for face detection and recognition. Some of these techniques will be intergrated in a real time demontrator which will be a preliminary prototype that will have to work in controlled conditions (for ilumination and pose) and with reduced databases. The demonstrator will be done in Matlab and the main image acquisition rotines and face detectio...

  5. Recognition of tennis strokes using key postures

    OpenAIRE

    Connaghan, Damien; Ó Conaire, Ciarán; Kelly, Philip; O''Connor, Noel E.

    2010-01-01

    In this paper we describe an approach for automatic recognition of tennis strokes using a single low cost camera. Professional tennis is played at high speed so the ability to classify tennis strokes on camera is hindered by the rapid movement of the players. We have developed an accurate recognition system which can automatically index tennis strokes from video footage. We aim to evolve this system so that meta data, such as time codes and descriptions of the strokes played, can be automatic...

  6. Iris analysis for biometric recognition systems

    CERN Document Server

    Bodade, Rajesh M

    2014-01-01

    The book presents three most significant areas in Biometrics and Pattern Recognition. A step-by-step approach for design and implementation of Dual Tree Complex Wavelet Transform (DTCWT) plus Rotated Complex Wavelet Filters (RCWF) is discussed in detail. In addition to the above, the book provides detailed analysis of iris images and two methods of iris segmentation. It also discusses simplified study of some subspace-based methods and distance measures for iris recognition backed by empirical studies and statistical success verifications.

  7. Analysis of Human Electrocardiogram for Biometric Recognition

    OpenAIRE

    Konstantinos N. Plataniotis; Dimitrios Hatzinakos; Foteini Agrafioti; Yongjin Wang

    2007-01-01

    Security concerns increase as the technology for falsification advances. There are strong evidences that a difficult to falsify biometric trait, the human heartbeat, can be used for identity recognition. Existing solutions for biometric recognition from electrocardiogram (ECG) signals are based on temporal and amplitude distances between detected fiducial points. Such methods rely heavily on the accuracy of fiducial detection, which is still an open problem due to the difficulty in exact loca...

  8. FACE RECOGNITION BASED ON CUCKOO SEARCH ALGORITHM

    OpenAIRE

    VIPINKUMAR TIWARI

    2012-01-01

    Feature Selection is a optimization technique used in face recognition technology. Feature selection removes the irrelevant, noisy and redundant data thus leading to the more accurate recognition of face from the database.Cuckko Algorithm is one of the recent optimization algorithm in the league of nature based algorithm. Its optimization results are better than the PSO and ACO optimization algorithms. The proposal of applying the Cuckoo algorithm for feature selection in the process of face ...

  9. Recognition and social behaviour in Formica ants

    OpenAIRE

    Chernenko, Anton

    2012-01-01

    Communication is probably one of the major means of life maintenance. Communication involves the use of signals, which can be visual, audial, olfactory etc. Organisms communicate in many different contexts, ranging from establishing own identity, foraging for food, finding a mate, protecting their territory, to more sophisticated ones such as engaging in social behaviour. Recognition is the action or process of recognizing or being recognized. Recognition based on olfactory cues is perhaps be...

  10. Feature Sampling Strategies for Action Recognition

    OpenAIRE

    Zhou, Youjie; Yu, Hongkai; Wang, Song

    2015-01-01

    Although dense local spatial-temporal features with bag-of-features representation achieve state-of-the-art performance for action recognition, the huge feature number and feature size prevent current methods from scaling up to real size problems. In this work, we investigate different types of feature sampling strategies for action recognition, namely dense sampling, uniformly random sampling and selective sampling. We propose two effective selective sampling methods using object proposal te...

  11. Early recognition of chemical dependence.

    Science.gov (United States)

    Maly, R C

    1993-03-01

    Chemical dependence is a leading cause of morbidity and death in the United States. At least 20% of patients seen by primary care physicians in both the outpatient and inpatient setting are chemically dependent. Up to 90% of these patients go undiagnosed by their primary physicians. Chemical dependence is defined as a chronic, progressive illness characterized by the repeated and persistent use of alcohol or drugs despite negative health, family, work, financial, or legal consequences. Primary care physicians are in an ideal position to detect chemical dependence at its earliest stages, when irreversible medical consequences and death are most likely preventable. Alcohol is the most common drug of abuse. Improving the rate of recognition of chemical dependence depends on being familiar with the constellation of physical, mental, and social indicators. Early medical manifestations of alcoholism common in the primary care setting include: gastric complaints, elevated blood pressure, palpitations, traumatic injuries, headaches, impotence, and gout. Early psychosocial manifestations common in both alcohol and drug dependence include anxiety, depression, insomnia, persistent relationship conflicts, work or school problems, and financial or legal problems. Particularly useful laboratory indicators of alcoholism include elevated levels of GGT and MCV, both displaying high specificity, with the GGT level being the most sensitive. Similarly specific laboratory tests for drug dependence are not available. Any patient presenting with any of the above medical, psychosocial, or laboratory manifestations should be screened for chemical dependence. The CAGE questionnaire for alcoholism, a four-question test, is particularly well suited to the primary care setting, where it can be administered in fewer than 60 seconds. The CAGE has demonstrated high sensitivity (in the 80% range) and specificity (approximately 85%) for alcoholism. Comparably convenient instruments do not yet exist

  12. Oxytocin improves emotion recognition for older males.

    Science.gov (United States)

    Campbell, Anna; Ruffman, Ted; Murray, Janice E; Glue, Paul

    2014-10-01

    Older adults (≥60 years) perform worse than young adults (18-30 years) when recognizing facial expressions of emotion. The hypothesized cause of these changes might be declines in neurotransmitters that could affect information processing within the brain. In the present study, we examined the neuropeptide oxytocin that functions to increase neurotransmission. Research suggests that oxytocin benefits the emotion recognition of less socially able individuals. Men tend to have lower levels of oxytocin and older men tend to have worse emotion recognition than older women; therefore, there is reason to think that older men will be particularly likely to benefit from oxytocin. We examined this idea using a double-blind design, testing 68 older and 68 young adults randomly allocated to receive oxytocin nasal spray (20 international units) or placebo. Forty-five minutes afterward they completed an emotion recognition task assessing labeling accuracy for angry, disgusted, fearful, happy, neutral, and sad faces. Older males receiving oxytocin showed improved emotion recognition relative to those taking placebo. No differences were found for older females or young adults. We hypothesize that oxytocin facilitates emotion recognition by improving neurotransmission in the group with the worst emotion recognition. PMID:24856057

  13. Age Dependent Face Recognition using Eigenface

    Directory of Open Access Journals (Sweden)

    Hlaing Htake Khaung Tin

    2013-10-01

    Full Text Available 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 computer interaction and multimedia communication. In this paper proposes an Eigen based age estimation algorithm for estimate an image from the database. Eigenface has proven to be a useful and robust cue for age prediction, age simulation, face recognition, localization and tracking. The scheme is based on an information theory approach that decomposes face images into a small set of characteristic feature images called eigenfaces, which may be thought of as the principal components of the initial training set of face images. The eigenface approach used in this scheme has advantages over other face recognition methods in its speed, simplicity, learning capability and robustness to small changes in the face image.

  14. An Introduction to Face Recognition Technology

    Directory of Open Access Journals (Sweden)

    Shang-Hung Lin

    2000-01-01

    Full Text Available Recently face recognition is attracting much attention in the society of network multimedia information access.  Areas such as network security, content indexing and retrieval, and video compression benefits from face recognition technology because "people" are the center of attention in a lot of video.  Network access control via face recognition not only makes hackers virtually impossible to steal one's "password", but also increases the user-friendliness in human-computer interaction.  Indexing and/or retrieving video data based on the appearances of particular persons will be useful for users such as news reporters, political scientists, and moviegoers.  For the applications of videophone and teleconferencing, the assistance of face recognition also provides a more efficient coding scheme.  In this paper, we give an introductory course of this new information processing technology.  The paper shows the readers the generic framework for the face recognition system, and the variants that are frequently encountered by the face recognizer.  Several famous face recognition algorithms, such as eigenfaces and neural networks, will also be explained.

  15. A Survey of Protein Fold Recognition Algorithms

    Directory of Open Access Journals (Sweden)

    M. S. Abual-Rub

    2008-01-01

    Full Text Available Problem statement: Predicting the tertiary structure of proteins from their linear sequence is really a big challenge in biology. This challenge is related to the fact that the traditional computational methods are not powerful enough to search for the correct structure in the huge conformational space. This inadequate capability of the computational methods, however, is a major obstacle in facing this problem. Trying to solve the problem of the protein fold recognition, most of the researchers have examined the use of the protein threading technique. This problem is known as NP-hard; researchers have used various methods such as neural networks, Monte Carlo, support vector machine and genetic algorithms to solve it. Some researchers tried the use of the parallel evolutionary methods for protein fold recognition but it is less well known. Approach: We reviewed various algorithms that have been developed for protein structure prediction by threading and fold recognition. Moreover, we provided a survey of parallel evolutionary methods for protein fold recognition. Results: The findings of this survey showed that evolutionary methods can be used to resolve the protein fold recognition problem. Conclusion: There are two aspects of protein fold recognition problem: First is the computational difficulty and second is that current energy functions are still not accurate enough to calculate the free energy of a given conformation.

  16. Automatic Arabic Hand Written Text Recognition System

    Directory of Open Access Journals (Sweden)

    I. A. Jannoud

    2007-01-01

    Full Text Available Despite of the decent development of the pattern recognition science applications in the last decade of the twentieth century and this century, text recognition remains one of the most important problems in pattern recognition. To the best of our knowledge, little work has been done in the area of Arabic text recognition compared with those for Latin, Chins and Japanese text. The main difficulty encountered when dealing with Arabic text is the cursive nature of Arabic writing in both printed and handwritten forms. An Automatic Arabic Hand-Written Text Recognition (AHTR System is proposed. An efficient segmentation stage is required in order to divide a cursive word or sub-word into its constituting characters. After a word has been extracted from the scanned image, it is thinned and its base line is calculated by analysis of horizontal density histogram. The pattern is then followed through the base line and the segmentation points are detected. Thus after the segmentation stage, the cursive word is represented by a sequence of isolated characters. The recognition problem thus reduces to that of classifying each character. A set of features extracted from each individual characters. A minimum distance classifier is used. Some approaches are used for processing the characters and post processing added to enhance the results. Recognized characters will be appended directly to a word file which is editable form.

  17. Implicit Recognition Based on Lateralized Perceptual Fluency

    Directory of Open Access Journals (Sweden)

    Iliana M. Vargas

    2012-02-01

    Full Text Available In some circumstances, accurate recognition of repeated images in an explicit memory test is driven by implicit memory. We propose that this “implicit recognition” results from perceptual fluency that influences responding without awareness of memory retrieval. Here we examined whether recognition would vary if images appeared in the same or different visual hemifield during learning and testing. Kaleidoscope images were briefly presented left or right of fixation during divided-attention encoding. Presentation in the same visual hemifield at test produced higher recognition accuracy than presentation in the opposite visual hemifield, but only for guess responses. These correct guesses likely reflect a contribution from implicit recognition, given that when the stimulated visual hemifield was the same at study and test, recognition accuracy was higher for guess responses than for responses with any level of confidence. The dramatic difference in guessing accuracy as a function of lateralized perceptual overlap between study and test suggests that implicit recognition arises from memory storage in visual cortical networks that mediate repetition-induced fluency increments.

  18. Multispectral palmprint recognition using a quaternion matrix.

    Science.gov (United States)

    Xu, Xingpeng; Guo, Zhenhua; Song, Changjiang; Li, Yafeng

    2012-01-01

    Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%. PMID:22666049

  19. Color pattern recognition with CIELAB coordinates

    Science.gov (United States)

    Corbalan-Fuertes, Montserrat; Millan Garcia-Verela, Maria S.; Yzuel, Maria J.

    2002-01-01

    A color pattern recognition system must identify a target by its shape and color distribution. In real situations, however, the color information is affected by changes of the light source (e.g., from indoor illumination to outdoor daylight), often making recognition impossible. In this work, we propose a color pattern recognition technique with tolerance for illumination changes within the common sources of white light. This can be accomplished using the coordinates of the CIELAB system, luminance (L*), chroma (C*), and hue (h*) instead of the conventional RGB system. The proposal has some additional advantages: there is no need to store a matched filters base to analyze scenes captured under different light sources (one set of filters for each illuminant light source) and therefore the recognition process can be simplified; and in most cases, the contribution of only two channels (C* and h*) is enough to avoid false alarms in color pattern recognition. From the results, we show that the recognition system is improved when CIELAB coordinates are used.

  20. Multispectral Palmprint Recognition Using a Quaternion Matrix

    Directory of Open Access Journals (Sweden)

    Yafeng Li

    2012-04-01

    Full Text Available Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR illuminations were represented by a quaternion matrix, then principal component analysis (PCA and discrete wavelet transform (DWT were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%.

  1. Robust coarticulatory modeling for continuous speech recognition

    Science.gov (United States)

    Schwartz, R.; Chow, Y. L.; Dunham, M. O.; Kimball, O.; Krasner, M.; Kubala, F.; Makhoul, J.; Price, P.; Roucos, S.

    1986-10-01

    The purpose of this project is to perform research into algorithms for the automatic recognition of individual sounds or phonemes in continuous speech. The algorithms developed should be appropriate for understanding large-vocabulary continuous speech input and are to be made available to the Strategic Computing Program for incorporation in a complete word recognition system. This report describes process to date in developing phonetic models that are appropriate for continuous speech recognition. In continuous speech, the acoustic realization of each phoneme depends heavily on the preceding and following phonemes: a process known as coarticulation. Thus, while there are relatively few phonemes in English (on the order of fifty or so), the number of possible different accoustic realizations is in the thousands. Therefore, to develop high-accuracy recognition algorithms, one may need to develop literally thousands of relatively distance phonetic models to represent the various phonetic context adequately. Developing a large number of models usually necessitates having a large amount of speech to provide reliable estimates of the model parameters. The major contributions of this work are the development of: (1) A simple but powerful formalism for modeling phonemes in context; (2) Robust training methods for the reliable estimation of model parameters by utilizing the available speech training data in a maximally effective way; and (3) Efficient search strategies for phonetic recognition while maintaining high recognition accuracy.

  2. Voice recognition: an enabling technology for modern health care?

    OpenAIRE

    Bergeron, B. P.

    1996-01-01

    Recent performance breakthroughs in affordable, large vocabulary, speaker independent voice recognition systems have rekindled widespread interest in using voice recognition technology to enhance the palatability and effectiveness of clinician-mediated computing. However, even if industry fully addresses the formidable hardware requirements, less than perfect recognition accuracies, discrete voice recognition requirements, and throughput limitations, there are significant cognitive and implem...

  3. Efficient Recognition of Human Faces from Video in Particle Filter

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Face recognition from video requires dealing with uncertainty both in tracking and recognition. This paper proposed an effective method for face recognition from video. In order to realize simultaneous tracking and recognition, fisherface-based recognition is combined with tracking into one model. This model is then embedded into particle filter to perform face recognition from video. In order to improve the robustness of tracking, an expectation maximization (EM) algorithm was adopted to update the appearance model. The experimental results show that the proposed method can perform well in tracking and recognition even in poor conditions such as occlusion and remarkable change in lighting.

  4. Reading Ancient Coin Legends: Object Recognition vs. OCR

    OpenAIRE

    Kavelar, Albert; Zambanini, Sebastian; Kampel, Martin

    2013-01-01

    Standard OCR is a well-researched topic of computer vision and can be considered solved for machine-printed text. However, when applied to unconstrained images, the recognition rates drop drastically. Therefore, the employment of object recognition-based techniques has become state of the art in scene text recognition applications. This paper presents a scene text recognition method tailored to ancient coin legends and compares the results achieved in character and word recognition experiment...

  5. Sugar recognition by human galactokinase

    Directory of Open Access Journals (Sweden)

    Timson David J

    2003-11-01

    Full Text Available Abstract Background Galactokinase catalyses the first committed step of galactose catabolism in which the sugar is phosphorylated at the expense of MgATP. Recent structural studies suggest that the enzyme makes several contacts with galactose – five side chain and two main chain hydrogen bonds. Furthermore, it has been suggested that inhibition of galactokinase may help sufferers of the genetic disease classical galactosemia which is caused by defects in another enzyme of the pathway galactose-1-phosphate uridyl transferase. Galactokinases from different sources have a range of substrate specificities and a diversity of kinetic mechanisms. Therefore only studies on the human enzyme are likely to be of value in the design of therapeutically useful inhibitors. Results Using recombinant human galactokinase expressed in and purified from E. coli we have investigated the sugar specificity of the enzyme and the kinetic consequences of mutating residues in the sugar-binding site in order to improve our understanding of substrate recognition by this enzyme. D-galactose and 2-deoxy-D-galactose are substrates for the enzyme, but N-acetyl-D-galactosamine, L-arabinose, D-fucose and D-glucose are all not phosphorylated. Mutation of glutamate-43 (which forms a hydrogen bond to the hydroxyl group attached to carbon 6 of galactose to alanine results in only minor changes in the kinetic parameters of the enzyme. Mutation of this residue to glycine causes a ten-fold drop in the turnover number. In contrast, mutation of histidine 44 to either alanine or isoleucine results in insoluble protein following expression in E. coli. Alteration of the residue that makes hydrogen bonds to the hydroxyl attached to carbons 3 and 4 (aspartate 46 results in an enzyme that although soluble is essentially inactive. Conclusions The enzyme is tolerant to small changes at position 2 of the sugar ring, but not at positions 4 and 6. The results from site directed mutagenesis could

  6. Novel acoustic features for speech emotion recognition

    Institute of Scientific and Technical Information of China (English)

    ROH; Yong-Wan; KIM; Dong-Ju; LEE; Woo-Seok; HONG; Kwang-Seok

    2009-01-01

    This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech.The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform(FFT) spectral entropy,delta FFT spectral entropy,Mel-frequency filter bank(MFB) spectral entropy,and Delta MFB spectral entropy.Spectral-based entropy features are simple.They reflect frequency characteristic and changing characteristic in frequency of speech.We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance.Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results,respectively.These scores are first obtained from a pattern recognition procedure.The pattern recognition phase uses the Gaussian mixture model(GMM).We classify the four emotional states as anger,sadness,happiness and neutrality.The proposed method is evaluated using 45 sentences in each emotion for 30 subjects,15 males and 15 females.Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy,Zero Crossing Rate(ZCR),linear prediction coefficient(LPC),and pitch parameters.We demonstrate the effectiveness of the proposed approach.One of the proposed features,combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods.We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

  7. Contextual modulation of biases in face recognition.

    Directory of Open Access Journals (Sweden)

    Fatima Maria Felisberti

    Full Text Available BACKGROUND: The ability to recognize the faces of potential cooperators and cheaters is fundamental to social exchanges, given that cooperation for mutual benefit is expected. Studies addressing biases in face recognition have so far proved inconclusive, with reports of biases towards faces of cheaters, biases towards faces of cooperators, or no biases at all. This study attempts to uncover possible causes underlying such discrepancies. METHODOLOGY AND FINDINGS: Four experiments were designed to investigate biases in face recognition during social exchanges when behavioral descriptors (prosocial, antisocial or neutral embedded in different scenarios were tagged to faces during memorization. Face recognition, measured as accuracy and response latency, was tested with modified yes-no, forced-choice and recall tasks (N = 174. An enhanced recognition of faces tagged with prosocial descriptors was observed when the encoding scenario involved financial transactions and the rules of the social contract were not explicit (experiments 1 and 2. Such bias was eliminated or attenuated by making participants explicitly aware of "cooperative", "cheating" and "neutral/indifferent" behaviors via a pre-test questionnaire and then adding such tags to behavioral descriptors (experiment 3. Further, in a social judgment scenario with descriptors of salient moral behaviors, recognition of antisocial and prosocial faces was similar, but significantly better than neutral faces (experiment 4. CONCLUSION: The results highlight the relevance of descriptors and scenarios of social exchange in face recognition, when the frequency of prosocial and antisocial individuals in a group is similar. Recognition biases towards prosocial faces emerged when descriptors did not state the rules of a social contract or the moral status of a behavior, and they point to the existence of broad and flexible cognitive abilities finely tuned to minor changes in social context.

  8. Impaired picture recognition in transient epileptic amnesia.

    Science.gov (United States)

    Dewar, Michaela; Hoefeijzers, Serge; Zeman, Adam; Butler, Christopher; Della Sala, Sergio

    2015-01-01

    Transient epileptic amnesia (TEA) is an epileptic syndrome characterized by recurrent, brief episodes of amnesia. Transient epileptic amnesia is often associated with the rapid decline in recall of new information over hours to days (accelerated long-term forgetting - 'ALF'). It remains unknown how recognition memory is affected in TEA over time. Here, we report a systematic study of picture recognition in patients with TEA over the course of one week. Sixteen patients with TEA and 16 matched controls were presented with 300 photos of everyday life scenes. Yes/no picture recognition was tested 5min, 2.5h, 7.5h, 24h, and 1week after picture presentation using a subset of target pictures as well as similar and different foils. Picture recognition was impaired in the patient group at all test times, including the 5-minute test, but it declined normally over the course of 1week. This impairment was associated predominantly with an increased false alarm rate, especially for similar foils. High performance on a control test indicates that this impairment was not associated with perceptual or discrimination deficits. Our findings suggest that, at least in some TEA patients with ALF in verbal recall, picture recognition does not decline more rapidly than in controls over 1week. However, our findings of an early picture recognition deficit suggest that new visual memories are impoverished after minutes in TEA. This could be the result of deficient encoding or impaired early consolidation. The early picture recognition deficit observed could reflect either the early stages of the process that leads to ALF or a separable deficit of anterograde memory in TEA. Lastly, our study suggests that at least some patients with TEA are prone to falsely recognizing new everyday visual information that they have not in fact seen previously. This deficit, alongside their ALF in free recall, likely affects everyday memory performance. PMID:25506793

  9. What Types of Visual Recognition Tasks Are Mediated by the Neural Subsystem that Subserves Face Recognition?

    Science.gov (United States)

    Brooks, Brian E.; Cooper, Eric E.

    2006-01-01

    Three divided visual field experiments tested current hypotheses about the types of visual shape representation tasks that recruit the cognitive and neural mechanisms underlying face recognition. Experiment 1 found a right hemisphere advantage for subordinate but not basic-level face recognition. Experiment 2 found a right hemisphere advantage for…

  10. A motivational determinant of facial emotion recognition: regulatory focus affects recognition of emotions in faces.

    Directory of Open Access Journals (Sweden)

    Claudia Sassenrath

    Full Text Available Two studies examined an unexplored motivational determinant of facial emotion recognition: observer regulatory focus. It was predicted that a promotion focus would enhance facial emotion recognition relative to a prevention focus because the attentional strategies associated with promotion focus enhance performance on well-learned or innate tasks - such as facial emotion recognition. In Study 1, a promotion or a prevention focus was experimentally induced and better facial emotion recognition was observed in a promotion focus compared to a prevention focus. In Study 2, individual differences in chronic regulatory focus were assessed and attention allocation was measured using eye tracking during the facial emotion recognition task. Results indicated that the positive relation between a promotion focus and facial emotion recognition is mediated by shorter fixation duration on the face which reflects a pattern of attention allocation matched to the eager strategy in a promotion focus (i.e., striving to make hits. A prevention focus did not have an impact neither on perceptual processing nor on facial emotion recognition. Taken together, these findings demonstrate important mechanisms and consequences of observer motivational orientation for facial emotion recognition.

  11. Pupil dilation during recognition memory: Isolating unexpected recognition from judgment uncertainty.

    Science.gov (United States)

    Mill, Ravi D; O'Connor, Akira R; Dobbins, Ian G

    2016-09-01

    Optimally discriminating familiar from novel stimuli demands a decision-making process informed by prior expectations. Here we demonstrate that pupillary dilation (PD) responses during recognition memory decisions are modulated by expectations, and more specifically, that pupil dilation increases for unexpected compared to expected recognition. Furthermore, multi-level modeling demonstrated that the time course of the dilation during each individual trial contains separable early and late dilation components, with the early amplitude capturing unexpected recognition, and the later trailing slope reflecting general judgment uncertainty or effort. This is the first demonstration that the early dilation response during recognition is dependent upon observer expectations and that separate recognition expectation and judgment uncertainty components are present in the dilation time course of every trial. The findings provide novel insights into adaptive memory-linked orienting mechanisms as well as the general cognitive underpinnings of the pupillary index of autonomic nervous system activity. PMID:27253862

  12. Practical vision based degraded text recognition system

    Science.gov (United States)

    Mohammad, Khader; Agaian, Sos; Saleh, Hani

    2011-02-01

    Rapid growth and progress in the medical, industrial, security and technology fields means more and more consideration for the use of camera based optical character recognition (OCR) Applying OCR to scanned documents is quite mature, and there are many commercial and research products available on this topic. These products achieve acceptable recognition accuracy and reasonable processing times especially with trained software, and constrained text characteristics. Even though the application space for OCR is huge, it is quite challenging to design a single system that is capable of performing automatic OCR for text embedded in an image irrespective of the application. Challenges for OCR systems include; images are taken under natural real world conditions, Surface curvature, text orientation, font, size, lighting conditions, and noise. These and many other conditions make it extremely difficult to achieve reasonable character recognition. Performance for conventional OCR systems drops dramatically as the degradation level of the text image quality increases. In this paper, a new recognition method is proposed to recognize solid or dotted line degraded characters. The degraded text string is localized and segmented using a new algorithm. The new method was implemented and tested using a development framework system that is capable of performing OCR on camera captured images. The framework allows parameter tuning of the image-processing algorithm based on a training set of camera-captured text images. Novel methods were used for enhancement, text localization and the segmentation algorithm which enables building a custom system that is capable of performing automatic OCR which can be used for different applications. The developed framework system includes: new image enhancement, filtering, and segmentation techniques which enabled higher recognition accuracies, faster processing time, and lower energy consumption, compared with the best state of the art published

  13. Syllabic Length Effect in Visual Word Recognition

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    Roya Ranjbar Mohammadi

    2014-07-01

    Full Text Available Studies on visual word recognition have resulted in different and sometimes contradictory proposals as Multi-Trace Memory Model (MTM, Dual-Route Cascaded Model (DRC, and Parallel Distribution Processing Model (PDP. The role of the number of syllables in word recognition was examined by the use of five groups of English words and non-words. The reaction time of the participants to these words was measured using reaction time measuring software. The results indicated that there was syllabic effect on recognition of both high and low frequency words. The pattern was incremental in terms of syllable number. This pattern prevailed in high and low frequency words and non-words except in one syllable words. In general, the results are in line with the PDP model which claims that a single processing mechanism is used in both words and non-words recognition. In other words, the findings suggest that lexical items are mainly processed via a lexical route.  A pedagogical implication of the findings would be that reading in English as a foreign language involves analytical processing of the syllable of the words.Keywords: Multi-Trace Memory Model, Dual-Route Cascaded Model, Parallel Distribution Processing Model, Syllabic Effect, Word Recognition

  14. SURVEY OF BIOMETRIC SYSTEMS USING IRIS RECOGNITION

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    S.PON SANGEETHA

    2014-02-01

    Full Text Available The security plays an important role in any type of organization in today’s life. Iris recognition is one of the leading automatic biometric systems in the area of security which is used to identify the individual person. Biometric systems include fingerprints, facial features, voice recognition, hand geometry, handwriting, the eye retina and the most secured one presented in this paper, the iris recognition. Biometric systems has become very famous in security systems because it is not possible to borrow or steel or forgotten the physical or behavioral characteristics. In this paper, we are concentrating on Iris as a biometric component which is somewhat better than other biometrics in terms of stability, uniqueness, accuracy, fast and non-invasive. Usually an iris technique works by capturing & storing the biometric information & then comparing the scanned iris biometric with what is stored in the database [7]. There are so many Iris recognition techniques have been developed so far. Here we presented the survey about those techniques and an outline for a proposed Iris Recognition System which uses the concept of Neural Network and Fuzzy logic.

  15. False recognition of instruction-set lures.

    Science.gov (United States)

    Curtis, Evan T; Chubala, Chrissy M; Spear, Jackie; Jamieson, Randall K; Hockley, William E; Crump, Matthew J C

    2016-01-01

    False remembering has been examined using a variety of procedures, including the Deese-Roediger-McDermott procedure, the false fame procedure and the two-list recognition procedure. We present six experiments in a different empirical framework examining false recognition of words included in the experimental instructions (instruction-set lures). The data show that participants' false alarm rate to instruction-set lures was twice their false alarm rate to standard lures. That result was statistically robust even when (1) the relative strength of targets to instruction-set lures was increased, (2) participants were warned about the instruction-set lures, (3) the instruction-set lures were camouflaged in the study instructions and (4) the instruction-set lures were presented verbally at study but visually at test. False recognition of instruction-set lures was only mitigated when participants were distracted between encountering the instruction-set lures and studying the training list. The results confirm the ease with which recognition succumbs to familiarity and demonstrate the robustness of false recognition. PMID:25438094

  16. Social appraisal influences recognition of emotions.

    Science.gov (United States)

    Mumenthaler, Christian; Sander, David

    2012-06-01

    The notion of social appraisal emphasizes the importance of a social dimension in appraisal theories of emotion by proposing that the way an individual appraises an event is influenced by the way other individuals appraise and feel about the same event. This study directly tested this proposal by asking participants to recognize dynamic facial expressions of emotion (fear, happiness, or anger in Experiment 1; fear, happiness, anger, or neutral in Experiment 2) in a target face presented at the center of a screen while a contextual face, which appeared simultaneously in the periphery of the screen, expressed an emotion (fear, happiness, anger) or not (neutral) and either looked at the target face or not. We manipulated gaze direction to be able to distinguish between a mere contextual effect (gaze away from both the target face and the participant) and a specific social appraisal effect (gaze toward the target face). Results of both experiments provided evidence for a social appraisal effect in emotion recognition, which differed from the mere effect of contextual information: Whereas facial expressions were identical in both conditions, the direction of the gaze of the contextual face influenced emotion recognition. Social appraisal facilitated the recognition of anger, happiness, and fear when the contextual face expressed the same emotion. This facilitation was stronger than the mere contextual effect. Social appraisal also allowed better recognition of fear when the contextual face expressed anger and better recognition of anger when the contextual face expressed fear. PMID:22288528

  17. Recall and recognition hypermnesia for Socratic stimuli.

    Science.gov (United States)

    Kazén, Miguel; Solís-Macías, Víctor M

    2016-01-01

    In two experiments, we investigate hypermnesia, net memory improvements with repeated testing of the same material after a single study trial. In the first experiment, we found hypermnesia across three trials for the recall of word solutions to Socratic stimuli (dictionary-like definitions of concepts) replicating Erdelyi, Buschke, and Finkelstein and, for the first time using these materials, for their recognition. In the second experiment, we had two "yes/no" recognition groups, a Socratic stimuli group presented with concrete and abstract verbal materials and a word-only control group. Using signal detection measures, we found hypermnesia for concrete Socratic stimuli-and stable performance for abstract stimuli across three recognition tests. The control group showed memory decrements across tests. We interpret these findings with the alternative retrieval pathways (ARP) hypothesis, contrasting it with alternative theories of hypermnesia, such as depth of processing, generation and retrieve-recognise. We conclude that recognition hypermnesia for concrete Socratic stimuli is a reliable phenomenon, which we found in two experiments involving both forced-choice and yes/no recognition procedures. PMID:25523628

  18. Development of individually distinct recognition cues.

    Science.gov (United States)

    Mateo, Jill M

    2006-11-01

    Despite extensive research on the functions of kin recognition, little is known about ontogenetic changes in the cues mediating such recognition. In Belding's ground squirrels, Spermophilus beldingi, secretions from oral glands are both individually distinct and kin distinct, and function in social recognition across many contexts. Behavioral studies of recognition and kin preferences suggest that these cues may change across development, particularly around the time of weaning and emergence from natal burrows (around 25 days of age). I used an habituation-discrimination task with captive S. beldingi, presenting subjects with odors collected from a pair of pups at several ages across early development. I found that at 21 days of age, but not at 7 or 14, young produce detectable odors. Odors are not individually distinct, however, until 28 days of age, after young have emerged from their burrows and begun foraging. In addition, an individual's odor continues to develop after emergence: odors produced by an individual at 20 and 40 days of age are perceived as dissimilar, yet odors produced at 28 and 40 days are treated as similar. Developmental changes in odors provide a proximate explanation for why S. beldingi littermate preferences are not consolidated until after natal emergence, and demonstrate that conspecifics must update their recognition templates as young develop. PMID:17016836

  19. 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.

  20. Portable Facial Recognition Jukebox Using Fisherfaces (Frj

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    Richard Mo

    2016-03-01

    Full Text Available A portable real-time facial recognition system that is able to play personalized music based on the identified person’s preferences was developed. The system is called Portable Facial Recognition Jukebox Using Fisherfaces (FRJ. Raspberry Pi was used as the hardware platform for its relatively low cost and ease of use. This system uses the OpenCV open source library to implement the computer vision Fisherfaces facial recognition algorithms, and uses the Simple DirectMedia Layer (SDL library for playing the sound files. FRJ is cross-platform and can run on both Windows and Linux operating systems. The source code was written in C++. The accuracy of the recognition program can reach up to 90% under controlled lighting and distance conditions. The user is able to train up to 6 different people (as many as will fit in the GUI. When implemented on a Raspberry Pi, the system is able to go from image capture to facial recognition in an average time of 200ms.

  1. TEXT SIGNAGE RECOGNITION IN ANDROID MOBILE DEVICES

    Directory of Open Access Journals (Sweden)

    Oi-Mean Foong

    2013-01-01

    Full Text Available This study presents a Text Signage Recognition (TSR model in Android mobile devices for Visually Impaired People (VIP. Independence navigation is always a challenge to VIP for indoor navigation in unfamiliar surroundings. Assistive Technology such as Android smart devices has great potential to assist VIPs in indoor navigation using built-in speech synthesizer. In contrast to previous TSR research which was deployed in standalone personal computer system using Otsu’s algorithm, we have developed an affordable Text Signage Recognition in Android Mobile Devices using Tesseract OCR engine. The proposed TSR model used the input images from the International Conference on Document Analysis and Recognition (ICDAR 2003 dataset for system training and testing. The TSR model was tested by four volunteers who were blind-folded. The system performance of the TSR model was assessed using different metrics (i.e., Precision, Recall, F-Score and Recognition Formulas to determine its accuracy. Experimental results show that the proposed TSR model has achieved recognition rate satisfactorily.

  2. Timecourse of neural signatures of object recognition.

    Science.gov (United States)

    Johnson, Jeffrey S; Olshausen, Bruno A

    2003-01-01

    How long does it take for the human visual system to recognize objects? This issue is important for understanding visual cortical function as it places constraints on models of the information processing underlying recognition. We designed a series of event-related potential (ERP) experiments to measure the timecourse of electrophysiological correlates of object recognition. We find two distinct types of components in the ERP recorded during categorization of natural images. One is an early presentation-locked signal arising around 135 ms that is present when there are low-level feature differences between images. The other is a later, recognition-related component arising between 150-300 ms. Unlike the early component, the latency of the later component covaries with the subsequent reaction time. In contrast to previous studies suggesting that the early, presentation-locked component of neural activity is correlated to recognition, these results imply that the neural signatures of recognition have a substantially later and variable time of onset. PMID:14507255

  3. Pattern activation/recognition theory of mind.

    Science.gov (United States)

    du Castel, Bertrand

    2015-01-01

    In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

  4. Text Independent Biometric Speaker Recognition System

    Directory of Open Access Journals (Sweden)

    Luqman Gbadamosi

    2013-11-01

    Full Text Available Designing a machine that mimics the human behavior, particularly with the capability of responding properly to spoken language, has intrigued engineers and scientists for centuries. The earlier research work on voice recognition system which is text-dependent requires that the user must say exactly the same text or passphrase for both enrollment and verification before gaining access. In this method the testing speech is polluted by additive noise at different noise decibel levels to achieve only 75% recognition rate and would require full cooperation by the speaker which could not be used for forensic investigation. This paper presents the historical background, and technological advances in voice recognition and most importantly the study and implementation of text-independent biometric voice recognition system which could be used for speaker identification with 100% recognition rate. The technique makes it possible to use the speaker's voice to verify their identity and control access to services such as voice dialing, telephone shopping, database access services, information services, voice mail, and remote access to computers. The implementation mainly incorporates Mel frequency Cepstral Coefficient (MFCCs which was used for feature extraction and Vector quantization using the Linde-Buzo-Gray (VQLBG algorithm used to minimize the amount of data to be handled. The matching result is given on the basis of minimum distortion distance. The project is coded in MATLAB.

  5. Pattern Activation/Recognition Theory of Mind

    Directory of Open Access Journals (Sweden)

    Bertrand edu Castel

    2015-07-01

    Full Text Available In his 2012 book How to Create a Mind, Ray Kurzweil defines a Pattern Recognition Theory of Mind that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call Pattern Activation/Recognition Theory of Mind. While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

  6. Application of data fusion in computer facial recognition

    Directory of Open Access Journals (Sweden)

    Wang Ai Qiang

    2013-11-01

    Full Text Available The recognition rate of single recognition method is inefficiency in computer facial recognition. We proposed a new confluent facial recognition method using data fusion technology, a variety of recognition algorithm are combined to form the fusion-based face recognition system to improve the recognition rate in many ways. Data fusion considers three levels of data fusion, feature level fusion and decision level fusion. And the data layer uses a simple weighted average algorithm, which is easy to implement. Artificial neural network algorithm was selected in feature layer and fuzzy reasoning algorithm was used in decision layer. Finally, we compared with the BP neural network algorithm in the MATLAB experimental platform. The result shows that the recognition rate has been greatly improved after adopting data fusion technology in computer facial recognition.

  7. Feature quality-based multimodal unconstrained eye recognition

    Science.gov (United States)

    Zhou, Zhi; Du, Eliza Y.; Lin, Yong; Thomas, N. Luke; Belcher, Craig; Delp, Edward J.

    2013-05-01

    Iris recognition has been tested to the most accurate biometrics using high resolution near infrared images. However, it does not work well under visible wavelength illumination. Sclera recognition, however, has been shown to achieve reasonable recognition accuracy under visible wavelengths. Combining iris and sclera recognition together can achieve better recognition accuracy. However, image quality can significantly affect the recognition accuracy. Moreover, in unconstrained situations, the acquired eye images may not be frontally facing. In this research, we proposed a feature quality-based multimodal unconstrained eye recognition method that combine the respective strengths of iris recognition and sclera recognition for human identification and can work with frontal and off-angle eye images. The research results show that the proposed method is very promising.

  8. PCA based Iris Recognition using DWT

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    Shashi Kumar D R

    2011-07-01

    Full Text Available The Iris pattern is an important biological feature of human body. The recognition of an individual based on iris pattern is gaining more popularity due to the uniqueness of the pattern among the people. In this paper PCA based iris recognition using DWT (PIRDWT is proposed. The upper and lower portion of the iris which is occluded by the eyelids and eyelashes is removed using morphological process. According to Springer Analysis of CASIA data base, to get better recognition forty five pixels to left and right of the pupil boundary is considered as iris template for the proposed algorithm analysis. The image is enhanced using Histogram Equalization to get high contrast. DWT is applied on histogram equalised iris template to get DWT coefficients. The features are extracted from the approximation band of the DWT coefficients using PCA. Multiple classifiers such as KNN, RF and SVM are used for matching. The proposed algorithm has better performance parameters compared to existing algorithm.

  9. Analysis of Human Electrocardiogram for Biometric Recognition

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    Konstantinos N. Plataniotis

    2007-11-01

    Full Text Available Security concerns increase as the technology for falsification advances. There are strong evidences that a difficult to falsify biometric trait, the human heartbeat, can be used for identity recognition. Existing solutions for biometric recognition from electrocardiogram (ECG signals are based on temporal and amplitude distances between detected fiducial points. Such methods rely heavily on the accuracy of fiducial detection, which is still an open problem due to the difficulty in exact localization of wave boundaries. This paper presents a systematic analysis for human identification from ECG data. A fiducial-detection-based framework that incorporates analytic and appearance attributes is first introduced. The appearance-based approach needs detection of one fiducial point only. Further, to completely relax the detection of fiducial points, a new approach based on autocorrelation (AC in conjunction with discrete cosine transform (DCT is proposed. Experimentation demonstrates that the AC/DCT method produces comparable recognition accuracy with the fiducial-detection-based approach.

  10. Analysis of Human Electrocardiogram for Biometric Recognition

    Science.gov (United States)

    Wang, Yongjin; Agrafioti, Foteini; Hatzinakos, Dimitrios; Plataniotis, Konstantinos N.

    2007-12-01

    Security concerns increase as the technology for falsification advances. There are strong evidences that a difficult to falsify biometric trait, the human heartbeat, can be used for identity recognition. Existing solutions for biometric recognition from electrocardiogram (ECG) signals are based on temporal and amplitude distances between detected fiducial points. Such methods rely heavily on the accuracy of fiducial detection, which is still an open problem due to the difficulty in exact localization of wave boundaries. This paper presents a systematic analysis for human identification from ECG data. A fiducial-detection-based framework that incorporates analytic and appearance attributes is first introduced. The appearance-based approach needs detection of one fiducial point only. Further, to completely relax the detection of fiducial points, a new approach based on autocorrelation (AC) in conjunction with discrete cosine transform (DCT) is proposed. Experimentation demonstrates that the AC/DCT method produces comparable recognition accuracy with the fiducial-detection-based approach.

  11. 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).

  12. Unstructured Object Recognition using Morphological Learning

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    S. Kar

    2002-07-01

    Full Text Available A technique of object recognition which can detect absence or presence of objects of interest without making explicit use of their underlying geometric structure is deemed suitable for many practical applications. In this work, a method of recognising unstructured objects has been presented, wherein several gray patterns are input as examples to a morphological rule-based learning algorithm. The output of the algorithm are the corresponding gray structuring elements capable of recognising patterns in query images. The learning is carried out offline before recognition of the queries. The technique has been tested to identify fuel pellet surface imperfections. Robustness wrt intensity, orientation, and shape variations of the query patterns is built into the method. Moreover, simplicity of the recognition process leading to reduced computational time makes the method attractive to solve many practical problems.

  13. Robust Facial Expression Recognition via Compressive Sensing

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    Shiqing Zhang

    2012-03-01

    Full Text Available Recently, compressive sensing (CS has attracted increasing attention in the areas of signal processing, computer vision and pattern recognition. In this paper, a new method based on the CS theory is presented for robust facial expression recognition. The CS theory is used to construct a sparse representation classifier (SRC. The effectiveness and robustness of the SRC method is investigated on clean and occluded facial expression images. Three typical facial features, i.e., the raw pixels, Gabor wavelets representation and local binary patterns (LBP, are extracted to evaluate the performance of the SRC method. Compared with the nearest neighbor (NN, linear support vector machines (SVM and the nearest subspace (NS, experimental results on the popular Cohn-Kanade facial expression database demonstrate that the SRC method obtains better performance and stronger robustness to corruption and occlusion on robust facial expression recognition tasks.

  14. Biologically inspired emotion recognition from speech

    Directory of Open Access Journals (Sweden)

    Buscicchio Cosimo

    2011-01-01

    Full Text Available Abstract Emotion recognition has become a fundamental task in human-computer interaction systems. In this article, we propose an emotion recognition approach based on biologically inspired methods. Specifically, emotion classification is performed using a long short-term memory (LSTM recurrent neural network which is able to recognize long-range dependencies between successive temporal patterns. We propose to represent data using features derived from two different models: mel-frequency cepstral coefficients (MFCC and the Lyon cochlear model. In the experimental phase, results obtained from the LSTM network and the two different feature sets are compared, showing that features derived from the Lyon cochlear model give better recognition results in comparison with those obtained with the traditional MFCC representation.

  15. Biologically inspired emotion recognition from speech

    Science.gov (United States)

    Caponetti, Laura; Buscicchio, Cosimo Alessandro; Castellano, Giovanna

    2011-12-01

    Emotion recognition has become a fundamental task in human-computer interaction systems. In this article, we propose an emotion recognition approach based on biologically inspired methods. Specifically, emotion classification is performed using a long short-term memory (LSTM) recurrent neural network which is able to recognize long-range dependencies between successive temporal patterns. We propose to represent data using features derived from two different models: mel-frequency cepstral coefficients (MFCC) and the Lyon cochlear model. In the experimental phase, results obtained from the LSTM network and the two different feature sets are compared, showing that features derived from the Lyon cochlear model give better recognition results in comparison with those obtained with the traditional MFCC representation.

  16. Character localization and recognition application for Smartphone

    Directory of Open Access Journals (Sweden)

    Snehal Charjan, R. V. Mante, P. N. Chatur

    2012-12-01

    Full Text Available Smart Phones have Internet access anywhere. The automatic text localization and recognition of text within a natural image is very useful for many problems. Once identified, the text can be used for many purposes. User can get current information about the product, place or boards. More exciting applications can be developed over the text extraction method with a high performance while also being computationally inexpensive. There are various methods proposed for Text Localization, text area segmentation, sign recognition and translation, Optical Character Recognition. In this paper we have described these methods. We have also compared all methods on the basis of performance and accuracy. Finally we concluded some good methods for Smartphone OCR application.

  17. Vasopressin selectively impairs emotion recognition in men.

    Science.gov (United States)

    Uzefovsky, Florina; Shalev, Idan; Israel, Salomon; Knafo, Ariel; Ebstein, Richard P

    2012-04-01

    The biological mechanisms underlying empathy, the ability to recognize emotions and to respond to them appropriately, are only recently becoming better understood. This report focuses on the nonapeptide arginine-vasopressin (AVP), which plays an important role in modulating social behavior in animals, especially promoting aggressive behavior. Towards clarifying the role of AVP in human social perception we used the Reading of the Mind in the Eyes Test and intranasal administration of AVP to show that AVP leads to a significant decrease in emotion recognition. Moreover, when comparing photos of males vs. females, all viewed by males, AVP had an effect on gender-matched photos only. Furthermore, the effect of AVP was restricted to recognition of negative emotions while leaving recognition of positive emotions unaffected. The current report emphasizes the selective role of AVP in male emotional perception and empathy, a core element in all human social interactions. PMID:21856082

  18. Real-time, face recognition technology

    Energy Technology Data Exchange (ETDEWEB)

    Brady, S.

    1995-11-01

    The Institute for Scientific Computing Research (ISCR) at Lawrence Livermore National Laboratory recently developed the real-time, face recognition technology KEN. KEN uses novel imaging devices such as silicon retinas developed at Caltech or off-the-shelf CCD cameras to acquire images of a face and to compare them to a database of known faces in a robust fashion. The KEN-Online project makes that recognition technology accessible through the World Wide Web (WWW), an internet service that has recently seen explosive growth. A WWW client can submit face images, add them to the database of known faces and submit other pictures that the system tries to recognize. KEN-Online serves to evaluate the recognition technology and grow a large face database. KEN-Online includes the use of public domain tools such as mSQL for its name-database and perl scripts to assist the uploading of images.

  19. 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.

  20. Recognition bias and the physical attractiveness stereotype.

    Science.gov (United States)

    Rohner, Jean-Christophe; Rasmussen, Anders

    2012-06-01

    Previous studies have found a recognition bias for information consistent with the physical attractiveness stereotype (PAS), in which participants believe that they remember that attractive individuals have positive qualities and that unattractive individuals have negative qualities, regardless of what information actually occurred. The purpose of this research was to examine whether recognition bias for PAS congruent information is replicable and invariant across a variety of conditions (i.e. generalizable). The effects of nine different moderator variables were examined in two experiments. With a few exceptions, the effect of PAS congruence on recognition bias was independent of the moderator variables. The results suggest that the tendency to believe that one remembers information consistent with the physical attractiveness stereotype is a robust phenomenon. PMID:22416805

  1. Facial expression recognition based on improved DAGSVM

    Science.gov (United States)

    Luo, Yuan; Cui, Ye; Zhang, Yi

    2014-11-01

    For the cumulative error problem because of randomization sequence of traditional DAGSVM(Directed Acyclic Graph Support Vector Machine) classification, this paper presents an improved DAGSVM expression recognition method. The method uses the distance of class and the standard deviation as the measure of the classer, which minimize the error rate of the upper structure of the classification. At the same time, this paper uses the method which combines discrete cosine transform (Discrete Cosine Transform, DCT) with Local Binary Pattern(Local Binary Pattern - LBP) ,to extract expression feature and be the input to improve the DAGSVM classifier for recognition. Experimental results show that compared with other multi-class support vector machine method, improved DAGSVM classifier can achieve higher recognition rate. And when it's used at the platform of the intelligent wheelchair, experiments show that the method has a better robustness.

  2. The effects of conformity on recognition judgements.

    Science.gov (United States)

    Reysen, Matthew B

    2005-01-01

    Schneider and Watkins (1996) demonstrated that participants' recognition performance can be affected by responses generated by a confederate. However, it remains uncertain whether the confederate's responses actually change the participants' memories or whether participants simply attempt to conform to the confederate. The present experiments examined this issue by having participants complete a final individual recognition test following a recognition test in which the participants worked with a virtual confederate. The results suggest that responses from virtual confederates affect participants' performance in ways similar to actual confederates and that conforming to a virtual confederate's responses does appear to result in actual deficits in memory. More specifically, it impairs participants' ability to correctly recognise material presented earlier. PMID:15724910

  3. Structural recognition of ancient Chinese ideographic characters

    Institute of Scientific and Technical Information of China (English)

    Li Ning; Chen Dan

    2014-01-01

    Ancient Chinese characters, typically the ideographic characters on bones and bronze before Shang Dynasty (16th—11th century B.C.), are valuable culture legacy of history. However the recognition of Ancient Chinese characters has been the task of paleography experts for long. With the help of modern computer technique, everyone can expect to be able to recognize the characters and understand the ancient inscriptions. This research is aimed to help people recognize and understand those ancient Chinese characters by combining Chinese paleography theory and computer information processing technology. Based on the analysis of ancient character features, a method for structural character recognition is proposed. The important characteristics of strokes and basic components or radicals used in recognition are introduced in detail. A system was implemented based on above method to show the effectiveness of the method.

  4. Cognitive and artificial representations in handwriting recognition

    Science.gov (United States)

    Lenaghan, Andrew P.; Malyan, Ron

    1996-03-01

    Both cognitive processes and artificial recognition systems may be characterized by the forms of representation they build and manipulate. This paper looks at how handwriting is represented in current recognition systems and the psychological evidence for its representation in the cognitive processes responsible for reading. Empirical psychological work on feature extraction in early visual processing is surveyed to show that a sound psychological basis for feature extraction exists and to describe the features this approach leads to. The first stage of the development of an architecture for a handwriting recognition system which has been strongly influenced by the psychological evidence for the cognitive processes and representations used in early visual processing, is reported. This architecture builds a number of parallel low level feature maps from raw data. These feature maps are thresholded and a region labeling algorithm is used to generate sets of features. Fuzzy logic is used to quantify the uncertainty in the presence of individual features.

  5. Recognition of social identity in ants

    DEFF Research Database (Denmark)

    Bos, Nick; d'Ettorre, Patrizia

    2012-01-01

    Recognizing the identity of others, from the individual to the group level, is a hallmark of society. Ants, and other social insects, have evolved advanced societies characterized by efficient social recognition systems. Colony identity is mediated by colony specific signature mixtures, a blend of...... hydrocarbons present on the cuticle of every individual (the “label”). Recognition occurs when an ant encounters another individual, and compares the label it perceives to an internal representation of its own colony odor (the “template”). A mismatch between label and template leads to rejection of the...... encountered individual. Although advances have been made in our understanding of how the label is produced and acquired, contradictory evidence exists about information processing of recognition cues. Here, we review the literature on template acquisition in ants and address how and when the template is...

  6. Neural circuitry for rat recognition memory

    Science.gov (United States)

    Warburton, E.C.; Brown, M.W.

    2015-01-01

    Information concerning the roles of different brain regions in recognition memory processes is reviewed. The review concentrates on findings from spontaneous recognition memory tasks performed by rats, including memory for single objects, locations, object–location associations and temporal order. Particular emphasis is given to the potential roles of different regions in the circuit of interacting structures involving the perirhinal cortex, hippocampus, medial prefrontal cortex and medial dorsal thalamus in recognition memory for the association of objects and places. It is concluded that while all structures in this circuit play roles critical to such memory, these roles can potentially be differentiated and differences in the underlying synaptic and biochemical processes involved in each region are beginning to be uncovered. PMID:25315129

  7. Partially Supervised Approach in Signal Recognition

    Directory of Open Access Journals (Sweden)

    Catalina COCIANU

    2009-01-01

    Full Text Available The paper focuses on the potential of principal directions based approaches in signal classification and recognition. In probabilistic models, the classes are represented in terms of multivariate density functions, and an object coming from a certain class is modeled as a random vector whose repartition has the density function corresponding to this class. In cases when there is no statistical information concerning the set of density functions corresponding to the classes involved in the recognition process, usually estimates based on the information extracted from available data are used instead. In the proposed methodology, the characteristics of a class are given by a set of eigen vectors of the sample covariance matrix. The overall dissimilarity of an object X with a given class C is computed as the disturbance of the structure of C, when X is allotted to C. A series of tests concerning the behavior of the proposed recognition algorithm are reported in the final section of the paper.

  8. Molecular Mechanisms of Cell-cell Recognition

    Institute of Scientific and Technical Information of China (English)

    WANG Jia-Huai

    2004-01-01

    Cell-cell recognition is the key for multicellular organisms to survive. This recognition critically depends on protein-protein interactions from opposing cell surfaces. Recent structural investigations reveal unique features of these cell surface receptors and how they interact. These interactions are specific, but usually relatively weak, with more hydrophilic forces involved in binding. The receptors appear to have specialized ways to present their key interacting elements for ligand-binding from the cell surface. Cell-cell contacts are multivalent. A large group of cell surface molecules are engaged in interactions. Characteristic weak interactions make possible for each individual molecule pair within the group to constantly associate-dissociate-reassociate, such that the cell-cell recognition becomes a dynamic process. The immunological synapse is a good example for immune receptors to be orchestrated in performing immunological function in a collective fashion.

  9. Target recognition based on modified combination rule

    Institute of Scientific and Technical Information of China (English)

    Chen Tianlu; Que Peiwen

    2006-01-01

    Evidence theory is widely used in the field of target recognition. The invalidation problem of this theory when dealing with highly conflict evidences is a research hotspot. Several alternatives of the combination rule are analyzed and compared. A new combination approach is proposed. Calculate the reliabilities of evidence sources using existing evidences. Construct reliabilities judge matrixes and get the weights of each evidence source. Weight average all inputted evidences. Combine processed evidences with D-S combination rule repeatedly to identify a target. The application in multi-sensor target recognition as well as the comparison with typical alternatives all validated that this approach can dispose highly conflict evidences efficiently and get reasonable recognition results rapidly.

  10. Recognition methods for 3D textured surfaces

    Science.gov (United States)

    Cula, Oana G.; Dana, Kristin J.

    2001-06-01

    Texture as a surface representation is the subject of a wide body of computer vision and computer graphics literature. While texture is always associated with a form of repetition in the image, the repeating quantity may vary. The texture may be a color or albedo variation as in a checkerboard, a paisley print or zebra stripes. Very often in real-world scenes, texture is instead due to a surface height variation, e.g. pebbles, gravel, foliage and any rough surface. Such surfaces are referred to here as 3D textured surfaces. Standard texture recognition algorithms are not appropriate for 3D textured surfaces because the appearance of these surfaces changes in a complex manner with viewing direction and illumination direction. Recent methods have been developed for recognition of 3D textured surfaces using a database of surfaces observed under varied imaging parameters. One of these methods is based on 3D textons obtained using K-means clustering of multiscale feature vectors. Another method uses eigen-analysis originally developed for appearance-based object recognition. In this work we develop a hybrid approach that employs both feature grouping and dimensionality reduction. The method is tested using the Columbia-Utrecht texture database and provides excellent recognition rates. The method is compared with existing recognition methods for 3D textured surfaces. A direct comparison is facilitated by empirical recognition rates from the same texture data set. The current method has key advantages over existing methods including requiring less prior information on both the training and novel images.

  11. Character Recognition Using Genetically Trained Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Diniz, C.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1998-10-01

    Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfid recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the

  12. 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.

  13. Handwritten Digits Recognition Using Neural Computing

    OpenAIRE

    Călin Enăchescu; Cristian-Dumitru Miron

    2009-01-01

    In this paper we present a method for the recognition of handwritten digits and a practical implementation of this method for real-time recognition. A theoretical framework for the neural networks used to classify the handwritten digits is also presented.The classification task is performed using a Convolutional Neural Network (CNN). CNN is a special type of multy-layer neural network, being trained with an optimized version of the back-propagation learning algorithm.CNN is designed to recogni...

  14. Mid-level Representation for Visual Recognition

    OpenAIRE

    Nabi, Moin

    2015-01-01

    Visual Recognition is one of the fundamental challenges in AI, where the goal is to understand the semantics of visual data. Employing mid-level representation, in particular, shifted the paradigm in visual recognition. The mid-level image/video representation involves discovering and training a set of mid-level visual patterns (e.g., parts and attributes) and represent a given image/video utilizing them. The mid-level patterns can be extracted from images and videos using the motion and appe...

  15. Performance appraisal and merit recognition exercise 2007

    CERN Multimedia

    HR Department

    2006-01-01

    The 2007 performance appraisal and merit recognition exercise will start in the usual way with annual interviews between staff and their supervisors. This year, these interviews should be held in the period from 8 January 2007 to 16 April 2007. Interconnection with the 5-yearly review, a number of modifications to the procedures relating to the performance appraisal and merit recognition are currently under study. Administrative Circular No. 26 (Procedures governing the Career Development of Staff Members) and the electronic MAPS form in EDH are being reviewed and will be available from January onwards. HR Department will shortly provide further information on this subject. Human Resources Department Tel. 73566

  16. Human action recognition with depth cameras

    CERN Document Server

    Wang, Jiang; Wu, Ying

    2014-01-01

    Action recognition technology has many real-world applications in human-computer interaction, surveillance, video retrieval, retirement home monitoring, and robotics. The commoditization of depth sensors has also opened up further applications that were not feasible before. This text focuses on feature representation and machine learning algorithms for action recognition from depth sensors. After presenting a comprehensive overview of the state of the art, the authors then provide in-depth descriptions of their recently developed feature representations and machine learning techniques, includi

  17. 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.

  18. 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.

  19. Pattern Recognition via PCNN and Tsallis Entropy

    OpenAIRE

    YuDong Zhang; LeNan Wu

    2008-01-01

    In this paper a novel feature extraction method for image processing via PCNN and Tsallis entropy is presented. We describe the mathematical model of the PCNN and the basic concept of Tsallis entropy in order to find a recognition method for isolated objects. Experiments show that the novel feature is translation and scale independent, while rotation independence is a bit weak at diagonal angles of 45° and 135°. Parameters of the application on face recognition are acquired by bacterial...

  20. Attention Modifies Gender Differences in Face Recognition

    OpenAIRE

    Lovén, Johanna

    2007-01-01

    Gender differences favoring women have been found in face recognition, and in addition to this, it has been shown that women remember more female than male faces. This own-gender effect may be a result of women directing more attention towards female faces, resulting in a better memory. The aim of this study was to assess the role of attention for gender differences in face recognition and women’s own-gender bias by dividing attention at encoding of faces. Thirty-two participants completed tw...

  1. Molecular Recognition Studies on Modified Cyclodextrins

    Institute of Scientific and Technical Information of China (English)

    LIU,Yu; YOU,Chang-Cheng

    2001-01-01

    This account deacribes our research progress in recent years in the areas of the molecular recognition studies on modified cy clodextrins, including positively charged cyclodextrins, cy clodextrin derivatives with hydrophobic substituent, and dimeric cyclodextrins. Calorimetric titration and various spec trometric techniques were employed to determine the complex stability constants, as well as the thermodynamic parameters, for their inclusion complexation with diverse guest molecules. The results obtained have heen discussed from the viewpoint of size/shape-matching, induced-fit, geometric compensation, and multiple recognition. Thermodynamically, the compen satory relationship between △H and T△S was found to be ex hibited in the inclusion complexation of modified cyclodextrin.

  2. Recognition, System Justification and Reconstructive Critique

    OpenAIRE

    Celikates, Robin

    2012-01-01

    When we think about the relations of recognition that structure a social order, exclusion is usually regarded as the problem and inclusion as the solution. In the following I will argue that in some cases inclusion—or rather the specific mode of inclusion—may very well constitute the problem. This is the case when we are dealing with ideological forms of recognition. System Justification Theory—a relatively novel approach in social and political psychology—offers an analysis of those cases in...

  3. Stereo vision with distance and gradient recognition

    Science.gov (United States)

    Kim, Soo-Hyun; Kang, Suk-Bum; Yang, Tae-Kyu

    2007-12-01

    Robot vision technology is needed for the stable walking, object recognition and the movement to the target spot. By some sensors which use infrared rays and ultrasonic, robot can overcome the urgent state or dangerous time. But stereo vision of three dimensional space would make robot have powerful artificial intelligence. In this paper we consider about the stereo vision for stable and correct movement of a biped robot. When a robot confront with an inclination plane or steps, particular algorithms are needed to go on without failure. This study developed the recognition algorithm of distance and gradient of environment by stereo matching process.

  4. A Survey on Human Ear Recognition

    Directory of Open Access Journals (Sweden)

    Suvarnsing Bhable

    2015-11-01

    Full Text Available This paper presents an efficient ear recognition technique which derives benefits from the local features of the ear and attempt to handle the problems due to pose, poor contrast, change in illumination and lack of registration. Recognizing humans by their ear have recently received significant attention in the field of research. Ear is the rich in characteristics. This paper provides a detailed survey of research done in ear detection and recognition. This survey paper is very useful in the current state-of- art for those who are working in this area and also for those who might exploit this new approach.

  5. Human recognition at a distance in video

    CERN Document Server

    Bhanu, Bir

    2010-01-01

    Most biometric systems employed for human recognition require physical contact with, or close proximity to, a cooperative subject. Far more challenging is the ability to reliably recognize individuals at a distance, when viewed from an arbitrary angle under real-world environmental conditions. Gait and face data are the two biometrics that can be most easily captured from a distance using a video camera. This comprehensive and logically organized text/reference addresses the fundamental problems associated with gait and face-based human recognition, from color and infrared video data that are

  6. Recognition and Judgement in Social Work

    DEFF Research Database (Denmark)

    Juul, Søren

    2009-01-01

    The purpose of this article is to argue for recognition as a normative ideal for social work and to confront the ideal with the reality found in the social institutions. I shall use the concept "judgement" to describe institutional routines and ways of thinking which constitute barriers to...... recognition. In the first part, I outline the normative ideal and show its relevance for practical social work on the basis of social clients' experiences of disrespect. In the second, I expalin the concept of judgement and criticise the prevailing forms of judgement to be found in the social institutions. In...

  7. Adaptive Face Recognition via Structed Representation

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yu-hua; ZENG Xiao-ming

    2014-01-01

    In this paper, we propose a face recognition approach-Structed Sparse Representation-based classification when the measurement of the test sample is less than the number training samples of each subject. When this condition is not satisfied, we exploit Nearest Subspace approach to classify the test sample. In order to adapt all the cases, we combine the two approaches to an adaptive classification method-Adaptive approach. The adaptive approach yields greater recognition accuracy than the SRC approach and CRC_RLS approach with low sample rate on the Extend Yale B dataset. And it is more efficient than other two approaches.

  8. Multiclass Recognition with Multiple Feature Trees

    Directory of Open Access Journals (Sweden)

    Guan-Lin Li

    2015-01-01

    Full Text Available This paper proposes a multiclass recognition scheme which uses multiple feature trees with an extended scoring method evolved from TF-IDF. Featur e trees consisting of different feature descriptors such as SIFT and SURF are built by the hierarchical k-means algorithm. The experimental results show that the proposed scoring method combing with the proposed multiple feature trees yields high accuracy for mul ticlass recognition and achieves significant improvement compared to methods using a single feat ure tree with original TF-IDF.

  9. Fingerprint Recognition Using Minutia Score Matching

    CERN Document Server

    J, Ravi; R, Venugopal K

    2010-01-01

    The popular Biometric used to authenticate a person is Fingerprint which is unique and permanent throughout a person's life. A minutia matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. In this paper we projected Fingerprint Recognition using Minutia Score Matching method (FRMSM). For Fingerprint thinning, the Block Filter is used, which scans the image at the boundary to preserves the quality of the image and extract the minutiae from the thinned image. The false matching ratio is better compared to the existing algorithm.

  10. Fingerprint recognition using standardized fingerprint model

    CERN Document Server

    Thai, Le Hoang

    2011-01-01

    Fingerprint recognition is one of most popular and accuracy Biometric technologies. Nowadays, it is used in many real applications. However, recognizing fingerprints in poor quality images is still a very complex problem. In recent years, many algorithms, models...are given to improve the accuracy of recognition system. This paper discusses on the standardized fingerprint model which is used to synthesize the template of fingerprints. In this model, after pre-processing step, we find the transformation between templates, adjust parameters, synthesize fingerprint, and reduce noises. Then, we use the final fingerprint to match with others in FVC2004 fingerprint database (DB4) to show the capability of the model.

  11. Fingerprint recognition using standardized fingerprint model

    Directory of Open Access Journals (Sweden)

    Le Hoang Thai

    2010-05-01

    Full Text Available Fingerprint recognition is one of most popular and accuracy Biometric technologies. Nowadays, it is used in many real applications. However, recognizing fingerprints in poor quality images is still a very complex problem. In recent years, many algorithms, models are given to improve the accuracy of recognition system. This paper discusses on the standardized fingerprint model which is used to synthesize the template of fingerprints. In this model, after pre-processing step, we find the transformation between templates, adjust parameters, synthesize fingerprint, and reduce noises. Then, we use the final fingerprint to match with others in FVC2004 fingerprint database (DB4 to show the capability of the model.

  12. Clothing Style Recognition using Fashion Attribute Detection

    Directory of Open Access Journals (Sweden)

    Guang-Lu Sun

    2015-08-01

    Full Text Available In this paper, a new framework is proposed for clothing style recognition in natural scenes. Clothing region is first detected through the fusion of super-pixel segmentation, saliency detection and Gaussian Mixture Model (GMM. Next, a group of fashion attribute detectors are trained to get the likelihood of each attribute in the clothing image. Finally, the correlation matrix between clothing styles and fashion attributes is adopted to predict the clothing style. For evaluation, we collect a dataset for clothing style recognition which contains 5 styles and 14 fashion attributes. Extensive experiments demonstrate that the proposed framework has a promising ability to recognize the clothing style.

  13. Multimodal Interactive Pattern Recognition and Applications

    CERN Document Server

    Toselli, Alejandro Hector; Casacuberta, Francisco

    2011-01-01

    This book presents a different approach to pattern recognition (PR) systems, in which users of a system are involved during the recognition process. This can help to avoid later errors and reduce the costs associated with post-processing. The book also examines a range of advanced multimodal interactions between the machine and the users, including handwriting, speech and gestures. Features: presents an introduction to the fundamental concepts and general PR approaches for multimodal interaction modeling and search (or inference); provides numerous examples and a helpful Glossary; discusses ap

  14. Hierachical Arabic Phoneme Recognition using MFCC Analysis

    Directory of Open Access Journals (Sweden)

    Abduladhem Abdulkareem Ali

    2007-01-01

    Full Text Available In this paper, a hierarchical Arabic phoneme recognition system is proposed in which Mel FrequencyCepstrum Coefficients (MFCC features is used to train the hierarchical neural networks architecture.Here, separate neural networks (subnetworks are to be recursively trained to recognize subsets ofphonemes. The overall recognition process is a combination of the outputs of these subnetworks.Experiments that explore the performance of the proposed hierarchical system in comparison to nonhierarchical(flat baseline systems are also presented in this paper.

  15. Advances in image processing and pattern recognition

    International Nuclear Information System (INIS)

    The conference papers reported provide an authorative and permanent record of the contributions. Some papers are more theoretical or of review nature, while others contain new implementations and applications. They are conveniently grouped into the following 7 fields (after a general overview): Acquisition and Presentation of 2-D and 3-D Images; Static and Dynamic Image Processing; Determination of Object's Position and Orientation; Objects and Characters Recognition; Semantic Models and Image Understanding; Robotics and Computer Vision in Manufacturing; Specialized Processing Techniques and Structures. In particular, new digital image processing and recognition methods, implementation architectures and special advanced applications (industrial automation, robotics, remote sensing, biomedicine, etc.) are presented. (Auth.)

  16. An Embedded Application for Degraded Text Recognition

    Directory of Open Access Journals (Sweden)

    Thillou Céline

    2005-01-01

    Full Text Available This paper describes a mobile device which tries to give the blind or visually impaired access to text information. Three key technologies are required for this system: text detection, optical character recognition, and speech synthesis. Blind users and the mobile environment imply two strong constraints. First, pictures will be taken without control on camera settings and a priori information on text (font or size and background. The second issue is to link several techniques together with an optimal compromise between computational constraints and recognition efficiency. We will present the overall description of the system from text detection to OCR error correction.

  17. The role of gender in face recognition

    OpenAIRE

    Rehnman, Jenny

    2007-01-01

    Faces constitute one of the most important stimuli for humans. Studies show that women recognize more faces than men, and that females are particularly able to recognize female faces, thus exhibiting an own-sex bias. In the present thesis, three empirical studies investigated the generality of sex differences in face recognition and the female own-sex bias. Study I explored men’s and women’s face recognition performance for Bangladeshi and Swedish female and male faces of adults and children....

  18. Phoneme Based Speaker—Independent English Command Recognition

    Institute of Scientific and Technical Information of China (English)

    贲俊; 万旺根; 余小清

    2003-01-01

    In this paper we propose a new algorithm of phoneme based speaker-independent English command recognition and develop a speaker-independent English command recognition system. It accelerates the whole system development by using HTK (hide Markov toolkits) and Visual C + + based on the character' istics of speaker-independent speech recognition. In recognition phase we combine the confidence measures with incomplete matching, which considerably improve the quality of recognition. The recognition accuracyis increased by 4.8 % over complete matching without back-end processing when the sige of vocabulary is more than 10.

  19. Radar automatic target recognition (ATR) and non-cooperative target recognition (NCTR)

    CERN Document Server

    Blacknell, David

    2013-01-01

    The ability to detect and locate targets by day or night, over wide areas, regardless of weather conditions has long made radar a key sensor in many military and civil applications. However, the ability to automatically and reliably distinguish different targets represents a difficult challenge. Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR) captures material presented in the NATO SET-172 lecture series to provide an overview of the state-of-the-art and continuing challenges of radar target recognition. Topics covered include the problem as applied to th

  20. An Upgrade of Network Traffic Recognition System for SIP/VoIP Traffic Recognition

    OpenAIRE

    Hou, Jiaqi

    2009-01-01

    The purpose of this project is to update the tool of Network Traffic Recognition System (NTRS) which is proprietary software of Ericsson AB and Tsinghua University, and to implement the updated tool to finish SIP/VoIP traffic recognition. Basing on the original NTRS, I analyze the traffic recognition principal of NTRS, and redesign the structure and module of the tool according to characteristics of SIP/VoIP traffic, and then finally I program to achieve the upgrade. After the final test with...

  1. Good, Evil and Successful Recognition. A Processualist View on Recognitive Attitudes, Relations and Norms

    Directory of Open Access Journals (Sweden)

    Särkelä Arvi-Antti

    2013-06-01

    Full Text Available In this paper I am proposing a “processual” account of struggles for recognition. I read Hegel in the section of “Evil and Its Forgiveness,” in his Phenomenology of Spirit, as arguing for a transition from basically action-theoretic, relational or institutional conceptions of recognition to a processual conception. Furthermore, I will be claiming that John Dewey’s experimentalist social philosophy can be understood as an attempt at working out the implications of this move in Hegel’s thought. Finally, I will try to indicate how to integrate central concepts of the recognition-theoretical vocabulary into such a processual account

  2. Plastic Antibodies: Molecular Recognition with Imprinted Polymers

    Science.gov (United States)

    Rushton, Gregory T.; Furmanski, Brian; Shimizu, Ken D.

    2005-01-01

    Synthetic polymers are prepared and tested in a study for their molecular recognition properties of an adenine derivative, ethyl adenine-9-acetate (EA9A), within two laboratory periods. The procedure introduces undergraduate chemistry students to noncovalent molecular imprinting as well as the analytical techniques for assessing their recognition…

  3. Compact Acoustic Models for Embedded Speech Recognition

    Directory of Open Access Journals (Sweden)

    Christophe Lévy

    2009-01-01

    Full Text Available Speech recognition applications are known to require a significant amount of resources. However, embedded speech recognition only authorizes few KB of memory, few MIPS, and small amount of training data. In order to fit the resource constraints of embedded applications, an approach based on a semicontinuous HMM system using state-independent acoustic modelling is proposed. A transformation is computed and applied to the global model in order to obtain each HMM state-dependent probability density functions, authorizing to store only the transformation parameters. This approach is evaluated on two tasks: digit and voice-command recognition. A fast adaptation technique of acoustic models is also proposed. In order to significantly reduce computational costs, the adaptation is performed only on the global model (using related speaker recognition adaptation techniques with no need for state-dependent data. The whole approach results in a relative gain of more than 20% compared to a basic HMM-based system fitting the constraints.

  4. IRIS Biometric Recognition System Employing Canny Operator

    Directory of Open Access Journals (Sweden)

    Binsu C. Kovoor

    2013-05-01

    Full Text Available Biometrics has become important in security applica tions. In comparison with many other biometric features, iris recognition has very high recognition accuracy because it depends on iris which is located in a place that still stable throughout human life and the probability to find two identical iris's is close to zero. The identifi cation system consists of several stages including segmentation stage which is the most serious and cr itical one. The current segmentation methods still have limitation in localizing the iri s due to circular shape consideration of the pupil. In this research, Daugman method is done to investigate the segmentation techniques. Eyelid detection is another step that has been incl uded in this study as a part of segmentation stage to localize the iris accurately and remove un wanted area that might be included. The obtained iris region is encoded using haar wavelets to construct the iris code, which contains the most discriminating feature in the iris pattern . Hamming distance is used for comparison of iris templates in the recognition stage. The datase t which is used for the study is UBIRIS database. A comparative study of different edge det ector operator is performed. It is observed that canny operator is best suited to extract most of the edges to generate the iris code for comparison. Recognition rate of 89% and rejection r ate of 95% is achieved.

  5. An explorative study on pork loin recognition

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo; Hviid, Marchen Sonja; Larsen, Rasmus;

    2013-01-01

    Bag-of-words (BoW) image description has shown good performance for a large variety of image recognition scenarios. We investigate approaches to alleviating a standard BoW image description pipeline representations for the specific task of recognizing pork loins. Specifically, we extend the Bo...

  6. Pumilio RNA recognition: the consequence of promiscuity.

    Science.gov (United States)

    Ryder, Sean P

    2011-03-01

    In this issue, Lu and Hall (2011) reveal the structural basis for degenerate RNA recognition by human Pumilio proteins. The structures suggest an appealing model where nucleotides that do not contribute to binding affinity define Pumilio regulatory activity by adopting distinctive conformations with differential ability to recruit regulatory cofactors. PMID:21397178

  7. Illumination-invariant hand gesture recognition

    Science.gov (United States)

    Mendoza-Morales, América I.; Miramontes-Jaramillo, Daniel; Kober, Vitaly

    2015-09-01

    In recent years, human-computer interaction (HCI) has received a lot of interest in industry and science because it provides new ways to interact with modern devices through voice, body, and facial/hand gestures. The application range of the HCI is from easy control of home appliances to entertainment. Hand gesture recognition is a particularly interesting problem because the shape and movement of hands usually are complex and flexible to be able to codify many different signs. In this work we propose a three step algorithm: first, detection of hands in the current frame is carried out; second, hand tracking across the video sequence is performed; finally, robust recognition of gestures across subsequent frames is made. Recognition rate highly depends on non-uniform illumination of the scene and occlusion of hands. In order to overcome these issues we use two Microsoft Kinect devices utilizing combined information from RGB and infrared sensors. The algorithm performance is tested in terms of recognition rate and processing time.

  8. Transfer learning for bimodal biometrics recognition

    Science.gov (United States)

    Dan, Zhiping; Sun, Shuifa; Chen, Yanfei; Gan, Haitao

    2013-10-01

    Biometrics recognition aims to identify and predict new personal identities based on their existing knowledge. As the use of multiple biometric traits of the individual may enables more information to be used for recognition, it has been proved that multi-biometrics can produce higher accuracy than single biometrics. However, a common problem with traditional machine learning is that the training and test data should be in the same feature space, and have the same underlying distribution. If the distributions and features are different between training and future data, the model performance often drops. In this paper, we propose a transfer learning method for face recognition on bimodal biometrics. The training and test samples of bimodal biometric images are composed of the visible light face images and the infrared face images. Our algorithm transfers the knowledge across feature spaces, relaxing the assumption of same feature space as well as same underlying distribution by automatically learning a mapping between two different but somewhat similar face images. According to the experiments in the face images, the results show that the accuracy of face recognition has been greatly improved by the proposed method compared with the other previous methods. It demonstrates the effectiveness and robustness of our method.

  9. Size Scaling in Visual Pattern Recognition

    Science.gov (United States)

    Larsen, Axel; Bundesen, Claus

    1978-01-01

    Human visual recognition on the basis of shape but regardless of size was investigated by reaction time methods. Results suggested two processes of size scaling: mental-image transformation and perceptual-scale transformation. Image transformation accounted for matching performance based on visual short-term memory, whereas scale transformation…

  10. Conformal Predictions in Multimedia Pattern Recognition

    Science.gov (United States)

    Nallure Balasubramanian, Vineeth

    2010-01-01

    The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…

  11. Multiple degree of freedom optical pattern recognition

    Science.gov (United States)

    Casasent, D.

    1987-01-01

    Three general optical approaches to multiple degree of freedom object pattern recognition (where no stable object rest position exists) are advanced. These techniques include: feature extraction, correlation, and artificial intelligence. The details of the various processors are advanced together with initial results.

  12. Recognition of aircraft using HRR features

    NARCIS (Netherlands)

    Kossen, A.S.

    2008-01-01

    Automated target recognition (ATR) based on high resolution radar (HRR) features can be used to increase the confidence in aircraft class. Standard radar systems are not designed for performing classification and uses additional identification systems. It is shown that with the use of features the a

  13. Colour measurement and white blood cell recognition

    CERN Document Server

    Gelsema, E S

    1972-01-01

    As a part of a collaboration with NEMCH aimed at the automation of the differential white blood cell count, studies have been made of the different possibilities for using colour to help in the recognition process. Results are presented comparing data obtained with a microspectrophotometer and with a simulated three-colour scanner.

  14. Emotion recognition a pattern analysis approach

    CERN Document Server

    Konar, Amit

    2014-01-01

    Offers both foundations and advances on emotion recognition in a single volumeProvides a thorough and insightful introduction to the subject by utilizing computational tools of diverse domainsInspires young researchers to prepare themselves for their own researchDemonstrates direction of future research through new technologies, such as Microsoft Kinect, EEG systems etc.

  15. Interstate Recognition and its Global Limits

    Czech Academy of Sciences Publication Activity Database

    Hrubec, Marek

    Nitra: Constantine the Philosopher University in Nitra, 2014 - (Javorská, A.; Mitterpach, K.; Sťahel, R.), s. 51-82 ISBN 978-80-558-0714-0 Institutional support: RVO:67985955 Keywords : recognition * states * Critical theory * globalization * legitimacy Subject RIV: AA - Philosophy ; Religion http://www.academia.edu/9617812/PHILOSOPHICA_14_Rendering_Change_in_Philosophy_and_Society

  16. Facial Action Units Recognition: A Comparative Study

    NARCIS (Netherlands)

    Popa, M.C.; Rothkrantz, L.J.M.; Wiggers, P.; Braspenning, R.A.C.; Shan, C.

    2011-01-01

    Many approaches to facial expression recognition focus on assessing the six basic emotions (anger, disgust, happiness, fear, sadness, and surprise). Real-life situations proved to produce many more subtle facial expressions. A reliable way of analyzing the facial behavior is the Facial Action Coding

  17. Emotional context influences micro-expression recognition.

    Directory of Open Access Journals (Sweden)

    Ming Zhang

    Full Text Available Micro-expressions are often embedded in a flow of expressions including both neutral and other facial expressions. However, it remains unclear whether the types of facial expressions appearing before and after the micro-expression, i.e., the emotional context, influence micro-expression recognition. To address this question, the present study used a modified METT (Micro-Expression Training Tool paradigm that required participants to recognize the target micro-expressions presented briefly between two identical emotional faces. The results of Experiments 1 and 2 showed that negative context impaired the recognition of micro-expressions regardless of the duration of the target micro-expression. Stimulus-difference between the context and target micro-expression was accounted for in Experiment 3. Results showed that a context effect on micro-expression recognition persists even when the stimulus similarity between the context and target micro-expressions was controlled. Therefore, our results not only provided evidence for the context effect on micro-expression recognition but also suggested that the context effect might result from both the stimulus and valence differences.

  18. ORNL Biometric Eye Model for Iris Recognition

    Energy Technology Data Exchange (ETDEWEB)

    Santos-Villalobos, Hector J [ORNL; Barstow, Del R [ORNL; Karakaya, Mahmut [ORNL; Chaum, Edward [University of Tennessee, Knoxville (UTK); Boehnen, Chris Bensing [ORNL

    2012-01-01

    Iris recognition has been proven to be an accurate and reliable biometric. However, the recognition of non-ideal iris images such as off angle images is still an unsolved problem. We propose a new biometric targeted eye model and a method to reconstruct the off-axis eye to its frontal view allowing for recognition using existing methods and algorithms. This allows for existing enterprise level algorithms and approaches to be largely unmodified by using our work as a pre-processor to improve performance. In addition, we describe the `Limbus effect' and its importance for an accurate segmentation of off-axis irides. Our method uses an anatomically accurate human eye model and ray-tracing techniques to compute a transformation function, which reconstructs the iris to its frontal, non-refracted state. Then, the same eye model is used to render a frontal view of the reconstructed iris. The proposed method is fully described and results from synthetic data are shown to establish an upper limit on performance improvement and establish the importance of the proposed approach over traditional linear elliptical unwrapping methods. Our results with synthetic data demonstrate the ability to perform an accurate iris recognition with an image taken as much as 70 degrees off-axis.

  19. Teaching Recognition Skills to Improve Products.

    Science.gov (United States)

    Knight, G. William; And Others

    1990-01-01

    First year dental students (n=86) in a conservative restorations course were taught a discrimination learning paradigm to improve production quality. Evaluation of Class 1 amalgam preparations indicates the improved recognition skills corresponded with improved cavity preparation, supporting the use of this teaching model. (Author/MSE)

  20. Iris Recognition: The Consequences of Image Compression

    Directory of Open Access Journals (Sweden)

    Bishop DanielA

    2010-01-01

    Full Text Available Iris recognition for human identification is one of the most accurate biometrics, and its employment is expanding globally. The use of portable iris systems, particularly in law enforcement applications, is growing. In many of these applications, the portable device may be required to transmit an iris image or template over a narrow-bandwidth communication channel. Typically, a full resolution image (e.g., VGA is desired to ensure sufficient pixels across the iris to be confident of accurate recognition results. To minimize the time to transmit a large amount of data over a narrow-bandwidth communication channel, image compression can be used to reduce the file size of the iris image. In other applications, such as the Registered Traveler program, an entire iris image is stored on a smart card, but only 4 kB is allowed for the iris image. For this type of application, image compression is also the solution. This paper investigates the effects of image compression on recognition system performance using a commercial version of the Daugman iris2pi algorithm along with JPEG-2000 compression, and links these to image quality. Using the ICE 2005 iris database, we find that even in the face of significant compression, recognition performance is minimally affected.

  1. Employee Recognition and Performance: A Field Experiment

    NARCIS (Netherlands)

    C. Bradler (Christiane); A.J. Dur (Robert); S. Neckermann (Susanne); J.A. Non (Arjan)

    2013-01-01

    textabstractThis 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 rec

  2. Employee recognition and performance: A field experiment

    NARCIS (Netherlands)

    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 recogn

  3. The Formulation of Extra-Territorial Recognition

    Czech Academy of Sciences Publication Activity Database

    Hrubec, Marek

    2010-01-01

    Roč. 1, č. 1 (2010), s. 65-72. ISSN 1674-1277 R&D Projects: GA MŠk(CZ) LC06013 Institutional research plan: CEZ:AV0Z90090514 Keywords : global justice * extra-territorial recognition Subject RIV: AA - Philosophy ; Religion

  4. Recognition of social identity in ants

    Directory of Open Access Journals (Sweden)

    Nick Bos

    2012-03-01

    Full Text Available Recognizing the identity of others, from the individual to the group level, is a hallmark of society. Ants, and other social insects, have evolved advanced societies characterized by efficient social recognition systems. Colony identity is mediated by colony specific signature mixtures, a blend of hydrocarbons present on the cuticle of every individual (the label. Recognition occurs when an ant encounters another individual, and compares the label it perceives to an internal representation of its own colony odor (the template. A mismatch between label and template leads to rejection of the encountered individual. Although advances have been made in our understanding of how the label is produced and acquired, contradictory evidence exists about information processing of recognition cues. Here, we review the literature on template acquisition in ants and address how and when the template is formed, where in the nervous system it is localized, and the possible role of learning. We combine seemingly contradictory evidence in to a novel, parsimonious theory for the information processing of nestmate recognition cues.

  5. Music Education Intervention Improves Vocal Emotion Recognition

    Science.gov (United States)

    Mualem, Orit; Lavidor, Michal

    2015-01-01

    The current study is an interdisciplinary examination of the interplay among music, language, and emotions. It consisted of two experiments designed to investigate the relationship between musical abilities and vocal emotional recognition. In experiment 1 (N = 24), we compared the influence of two short-term intervention programs--music and…

  6. Affect Recognition in Adults with ADHD

    Science.gov (United States)

    Miller, Meghan; Hanford, Russell B.; Fassbender, Catherine; Duke, Marshall; Schweitzer, Julie B.

    2011-01-01

    Objective: This study compared affect recognition abilities between adults with and without ADHD. Method: The sample consisted of 51 participants (34 men, 17 women) divided into 3 groups: ADHD-combined type (ADHD-C; n = 17), ADHD-predominantly inattentive type (ADHD-I; n = 16), and controls (n = 18). The mean age was 34 years. Affect recognition…

  7. Face Recognition Using Simplified Fuzzy Artmap

    Directory of Open Access Journals (Sweden)

    Antu Annam Thomas

    2011-02-01

    Full Text Available Face recognition has become one of the most active research areas of pattern recognition since the early1990s. This project thesis proposes a novel face recognition method based on Simplified Fuzzy ARTMAP(SFAM. For extracting features to be used for classification, combination of Principal ComponentAnalysis (PCA and Linear Discriminant Analysis (LDA is used. This is for improving the capability ofLDA and PCA when used alone.PCA reduces the dimensionality of input face images while LDA extractsthe features that help the classifier to classify the input face images. The classifier employed was SFAM.Experiment is conducted on ORL, Yale and Indian Face Database and results demonstrate SFAM’sefficiency as a recognizer. The training time of SFAM is negligible. SFAM has the added advantage thatthe network is adaptive, that is, during testing phase if the network comes across a new face that it is nottrained for; the network identifies this to be a new face and also learns this new face. Thus SFAM can beused in applications where database needs to be updated frequently. SFAM thus proves itself to be anefficient recognizer when a speedy, accurate and adaptive Face Recognition System is required.

  8. Handwriting Moroccan regions recognition using Tifinagh character

    Directory of Open Access Journals (Sweden)

    B. El Kessab

    2015-09-01

    In this context we propose a data set for handwritten Tifinagh regions composed of 1600 image (100 Image for each region. The dataset can be used in one hand to test the efficiency of the Tifinagh region recognition system in extraction of characteristics significatives and the correct identification of each region in classification phase in the other hand.

  9. Speech recognition: Acoustic, phonetic and lexical knowledge

    Science.gov (United States)

    Zue, V. W.

    1985-08-01

    During this reporting period we continued to make progress on the acquisition of acoustic-phonetic and lexical knowledge. We completed development of a continuous digit recognition system. The system was constructed to investigate the use of acoustic-phonetic knowledge in a speech recognition system. The significant achievements of this study include the development of a soft-failure procedure for lexical access and the discovery of a set of acoustic-phonetic features for verification. We completed a study of the constraints that lexical stress imposes on word recognition. We found that lexical stress information alone can, on the average, reduce the number of word candidates from a large dictionary by more than 80 percent. In conjunction with this study, we successfully developed a system that automatically determines the stress pattern of a word from the acoustic signal. We performed an acoustic study on the characteristics of nasal consonants and nasalized vowels. We have also developed recognition algorithms for nasal murmurs and nasalized vowels in continuous speech. We finished the preliminary development of a system that aligns a speech waveform with the corresponding phonetic transcription.

  10. RECOGNITION AND VERIFICATION OF TOUCHING HANDWRITTEN NUMERALS

    NARCIS (Netherlands)

    Zhou, J.; Kryzak, A.; Suen, C.Y.

    2004-01-01

    In the field of financial document processing, recognition of touching handwritten numerals has been limited by lack of good benchmarking databases and low reliability of algorithms. This paper addresses the efforts toward solving the two problems. Two databases IRIS-Bell\\\\\\'98 and TNIST are built/o

  11. Unpacking Recognition and Esteem in School Pedagogies

    Science.gov (United States)

    Wulf, Christoph; Bittner, Martin; Clemens, Iris; Kellermann, Ingrid

    2012-01-01

    The article focuses on pedagogical practices of recognition and esteem (Wertschatzung) and on the question of how those practices can be appropriately studied and epistemologically grasped. The investigation involves an inner-city elementary school in a socio-economically problematic district. With regard to the communication forms in this…

  12. Word Spotting and Recognition with Embedded Attributes.

    Science.gov (United States)

    Almazán, Jon; Gordo, Albert; Fornés, Alicia; Valveny, Ernest

    2014-12-01

    This paper addresses the problems of word spotting and word recognition on images. In word spotting, the goal is to find all instances of a query word in a dataset of images. In recognition, the goal is to recognize the content of the word image, usually aided by a dictionary or lexicon. We describe an approach in which both word images and text strings are embedded in a common vectorial subspace. This is achieved by a combination of label embedding and attributes learning, and a common subspace regression. In this subspace, images and strings that represent the same word are close together, allowing one to cast recognition and retrieval tasks as a nearest neighbor problem. Contrary to most other existing methods, our representation has a fixed length, is low dimensional, and is very fast to compute and, especially, to compare. We test our approach on four public datasets of both handwritten documents and natural images showing results comparable or better than the state-of-the-art on spotting and recognition tasks. PMID:26353157

  13. Early recognition of basal cell naevus syndrome

    NARCIS (Netherlands)

    Veenstra-Knol, HE; Scheewe, JH; van der Vlist, GJ; van Doorn, ME; Ausems, MGEM

    2005-01-01

    The basal cell naevus syndrome is an autosomal dominant syndrome characterised by major manifestations such as basal cell carcinomas, jaw cysts, palmar or plantar pits, and intracranial calcifications. Early recognition is important in order to reduce morbidity due to cutaneous and cerebral malignan

  14. Speech Recognition: A World of Opportunities

    Science.gov (United States)

    PACER Center, 2004

    2004-01-01

    Speech recognition technology helps people with disabilities interact with computers more easily. People with motor limitations, who cannot use a standard keyboard and mouse, can use their voices to navigate the computer and create documents. The technology is also useful to people with learning disabilities who experience difficulty with spelling…

  15. Recognition and Exteriority: Towards a Recognition-Theoretic Account of Globalization

    Directory of Open Access Journals (Sweden)

    Sebastian Purcell

    2011-06-01

    Full Text Available This essay aims to extend Paul Ricœur’s account of recognition to address some of the concerns of globalization, especially those voiced by Enrique Dussel. The extension is accomplished in two parts.  First, Dussel’s account of spatial existence as dwelling is reviewed as it is pertinent to the concerns of globalization.  Next, it is demonstrated that each of the aspects of Ricœur’s account of recognition may be given a spatial re-articulation.  The results thus establish an outline of how recognition theory might address some of the concerns of globalization.  The essay concludes with several consequences for the modification of recognition politics as one finds it in the late work of Ricœur and in Axel Honneth’s ongoing inquiries. 

  16. Spoken word recognition without a TRACE.

    Science.gov (United States)

    Hannagan, Thomas; Magnuson, James S; Grainger, Jonathan

    2013-01-01

    How do we map the rapid input of spoken language onto phonological and lexical representations over time? Attempts at psychologically-tractable computational models of spoken word recognition tend either to ignore time or to transform the temporal input into a spatial representation. TRACE, a connectionist model with broad and deep coverage of speech perception and spoken word recognition phenomena, takes the latter approach, using exclusively time-specific units at every level of representation. TRACE reduplicates featural, phonemic, and lexical inputs at every time step in a large memory trace, with rich interconnections (excitatory forward and backward connections between levels and inhibitory links within levels). As the length of the memory trace is increased, or as the phoneme and lexical inventory of the model is increased to a realistic size, this reduplication of time- (temporal position) specific units leads to a dramatic proliferation of units and connections, begging the question of whether a more efficient approach is possible. Our starting point is the observation that models of visual object recognition-including visual word recognition-have grappled with the problem of spatial invariance, and arrived at solutions other than a fully-reduplicative strategy like that of TRACE. This inspires a new model of spoken word recognition that combines time-specific phoneme representations similar to those in TRACE with higher-level representations based on string kernels: temporally independent (time invariant) diphone and lexical units. This reduces the number of necessary units and connections by several orders of magnitude relative to TRACE. Critically, we compare the new model to TRACE on a set of key phenomena, demonstrating that the new model inherits much of the behavior of TRACE and that the drastic computational savings do not come at the cost of explanatory power. PMID:24058349

  17. Spoken word recognition without a TRACE

    Directory of Open Access Journals (Sweden)

    Thomas eHannagan

    2013-09-01

    Full Text Available How do we map the rapid input of spoken language onto phonological and lexical representations over time? Attempts at psychologically-tractable computational models of spoken word recognition tend either to ignore time or to transform the temporal input into a spatial representation. TRACE, a connectionist model with broad and deep coverage of speech perception and spoken word recognition phenomena, takes the latter approach, using exclusively time-specific units at every level of representation. TRACE reduplicates featural, phonemic, and lexical inputs at every time step in a large memory trace, with rich interconnections (excitatory forward and backward connections between levels and inhibitory links within levels. As the length of the memory trace is increased, or as the phoneme and lexical inventory of the model is increased to a realistic size, this reduplication of time- (temporal position specific units leads to a dramatic proliferation of units and connections, begging the question of whether a more efficient approach is possible. Our starting point is the observation that models of visual object recognition - including visual word recognition - have grappled with the problem of spatial invariance, and arrived at solutions other than a fully-reduplicative strategy like that of TRACE. This inspires a new model of spoken word recognition that combines time-specific phoneme representations similar to those in TRACE with higher-level representations based on string kernels: temporally independent (time invariant diphone and lexical units. This reduces the number of necessary units and connections by several orders of magnitude relative to TRACE. Critically, we compare the new model to TRACE on a set of key phenomena, demonstrating that the new model inherits much of the behavior of TRACE and that the drastic computational savings do not come at the cost of explanatory power.

  18. Seeing women as objects: The sexual body part recognition bias

    NARCIS (Netherlands)

    S.J. Gervais; T.K. Vescio; J. Förster; A. Maass; C. Suitner

    2012-01-01

    Objectification theory suggests that the bodies of women are sometimes reduced to their sexual body parts. As well, an extensive literature in cognitive psychology suggests that global processing underlies person recognition, whereas local processing underlies object recognition. Integrating these l

  19. The Role of Wing Coloration in Sex Recognition and Competitor Recognition in Rubyspot Damselflies (Hetaerina spp.)

    OpenAIRE

    Grether, GF; Drury, JP; Berlin, E.; Anderson, CN

    2015-01-01

    © 2015 Blackwell Verlag GmbH. The decision rules that animals use for distinguishing between conspecifics of different age and sex classes are relevant for understanding how closely related species interact in sympatry. In rubyspot damselflies (Hetaerina spp.), the red wing coloration of mature males is hypothesized to be a key trait for sex recognition and competitor recognition within species and the proximate trigger for interspecific male-male aggression. We tested this hypothesis by mani...

  20. Facial emotional recognition in schizophrenia: preliminary results of the virtual reality program for facial emotional recognition

    OpenAIRE

    Teresa Souto; Alexandre Baptista; Diana Tavares; Cristina Queirós; Marques António

    2013-01-01

    BACKGROUND: Significant deficits in emotional recognition and social perception characterize patients with schizophrenia and have direct negative impact both in inter-personal relationships and in social functioning. Virtual reality, as a methodological resource, might have a high potential for assessment and training skills in people suffering from mental illness. OBJECTIVES: To present preliminary results of a facial emotional recognition assessment designed for patients with schizophrenia,...

  1. Model-based objects recognition in man-made environments

    OpenAIRE

    Martí Bonmatí, Joan; Casals, Alícia

    1996-01-01

    We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some ...

  2. Framework of Pattern Recognition Model Based on the Cognitive Psychology

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    According to the fundamental theory of visual cognition mechanism and cognitive psychology,the visual pattern recognition model is introduced briefly.Three pattern recognition models,i.e.template-based matching model,prototype-based matching model and feature-based matching model are built and discussed separately.In addition,the influence of object background information and visual focus point to the result of pattern recognition is also discussed with the example of recognition for fuzzy letters and figures.

  3. Iris Recognition System using canny edge detection for Biometric Identification

    OpenAIRE

    Bhawna Chouhan; Dr.(Mrs) Shailja Shukla

    2011-01-01

    biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system available. Most commercial iris recognition systems use patented algorithms developed by Daugman, and these algorithms are able to produce perfect recognition rates. Especially it focuses on image segmentation and feature extraction for iris recognition process...

  4. Arabic Speech Recognition System using CMU-Sphinx4

    CERN Document Server

    Satori, H; Chenfour, N

    2007-01-01

    In this paper we present the creation of an Arabic version of Automated Speech Recognition System (ASR). This system is based on the open source Sphinx-4, from the Carnegie Mellon University. Which is a speech recognition system based on discrete hidden Markov models (HMMs). We investigate the changes that must be made to the model to adapt Arabic voice recognition. Keywords: Speech recognition, Acoustic model, Arabic language, HMMs, CMUSphinx-4, Artificial intelligence.

  5. Cortical mechanisms of sensory learning and object recognition

    OpenAIRE

    Hoffman, K. L.; Logothetis, N.K.

    2008-01-01

    Learning about the world through our senses constrains our ability to recognise our surroundings. Experience shapes perception. What is the neural basis for object recognition and how are learning-induced changes in recognition manifested in neural populations? We consider first the location of neurons that appear to be critical for object recognition, before describing what is known about their function. Two complementary processes of object recognition are considered: discrimination among d...

  6. Random-Profiles-Based 3D Face Recognition System

    OpenAIRE

    Joongrock Kim; Sunjin Yu; Sangyoun Lee

    2014-01-01

    In this paper, a noble nonintrusive three-dimensional (3D) face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D) face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3D face recognition, which uses 3D face data, has recently received much attention. However, the perf...

  7. The limited value of precise tests of the recognition heuristic

    OpenAIRE

    Thorsten Pachur

    2011-01-01

    The recognition heuristic models the adaptive use and dominant role of recognition knowledge in judgment under uncertainty. Of the several predictions that the heuristic makes, empirical tests have predominantly focused on the proposed noncompensatory processing of recognition. Some authors have emphasized that the heuristic needs to be scrutinized based on precise tests of the exclusive use of recognition. Although precise tests have clear merits, I critically evaluate the value of such test...

  8. Signature Recognition using Multi Scale Fourier Descriptor And Wavelet Transform

    CERN Document Server

    Ismail, Ismail A; danaf, Talaat S El; Samak, Ahmed H

    2010-01-01

    This paper present a novel off-line signature recognition method based on multi scale Fourier Descriptor and wavelet transform . The main steps of constructing a signature recognition system are discussed and experiments on real data sets show that the average error rate can reach 1%. Finally we compare 8 distance measures between feature vectors with respect to the recognition performance. Key words: signature recognition; Fourier Descriptor; Wavelet transform; personal verification

  9. Comparison of Emotion Recognition from Facial Expression and Music

    OpenAIRE

    Gašpar, Tina; Labor, Marina; Jurić, Iva; Dumančić, Dijana; Ilakovac, Vesna; Heffer, Marija

    2011-01-01

    The recognition of basic emotions in everyday communication involves interpretation of different visual and auditory clues. The ability to recognize emotions is not clearly determined as their presentation is usually very short (micro expressions), whereas the recognition itself does not have to be a conscious process. We assumed that the recognition from facial expressions is selected over the recognition of emotions communicated through music. In order to compare the success rate in recogni...

  10. Voice Recognition Technology: Has It Come of Age?

    OpenAIRE

    Zumalt, Joseph R.

    2005-01-01

    Voice recognition software allows computer users to bypass their keyboards and use their voices to enter text. While the library literature is somewhat silent about voice recognition technology, the medical and legal communities have reported some success using it. Voice recognition software was tested for dictation accuracy and usability within an agriculture library at the University of Illinois. Dragon NaturallySpeaking 8.0 was found to be more accurate than speech recognition within Micro...

  11. A Comparison of Moments-Based Logo Recognition Methods

    OpenAIRE

    Zili Zhang; Xuan Wang; Waqas Anwar; Zoe L. Jiang

    2014-01-01

    Logo recognition is an important issue in document image, advertisement, and intelligent transportation. Although there are many approaches to study logos in these fields, logo recognition is an essential subprocess. Among the methods of logo recognition, the descriptor is very vital. The results of moments as powerful descriptors were not discussed before in terms of logo recognition. So it is unclear which moments are more appropriate to recognize which kind of logos. In this paper we find ...

  12. Research of Artificial Neural Networks Abilities in Printed Words Recognition

    OpenAIRE

    A. Bondarenko; Borisovs, A

    2010-01-01

    This paper provides a brief overview on document analysis and recognition area, highlighting main steps and modules that are used to build recognition systems of the mentioned type. We underline basic workflow of such system down to the problem of single character recognition problem and highlighting possibilities and ways for artificial neural networks usage. Further we are conductinga formal comparison of abilities of printed characters recognition between two well known types of second ge...

  13. A Survey on Tamil Handwritten Character Recognition using OCR Techniques

    OpenAIRE

    M. Antony Robert Raj; S.Abirami

    2012-01-01

    In today’s fast growing technology, digital recognitions are playing wide role and providing more scope to perform research in OCR techniques. Recognition of Tamil handwritten scripts is complicated compared to other western language scripts. However, many researchers have provided real-time solutions for offline Tamil character recognition also. Offline Tamil handwritten documents recognition still offers many motivating challenges to researchers. Current research offers many ...

  14. 46 CFR 8.220 - Recognition of a classification society.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 1 2010-10-01 2010-10-01 false Recognition of a classification society. 8.220 Section 8... INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.220 Recognition of a classification society. (a) A classification society must be recognized by the Commandant before it may receive...

  15. An Improved Difference of Gaussian Filter in Face Recognition

    OpenAIRE

    Shoujia Wang; Wenhui Li; Ying Wang; Yuanyuan Jiang; Shan Jiang; Ruilin Zhao

    2012-01-01

    In this paper, we analyze an improved DOG filter with different parameters in horizontal and vertical directions and the improved filter uses oval recognition domain instead of round recognition domain of classic DOG filter. The improved filter is used to compare with major illumination pretreatment methods. The experiment result shows the improved method has better recognition and false detection rate.

  16. The Recognition Heuristic: A Review of Theory and Tests

    Directory of Open Access Journals (Sweden)

    Thorsten ePachur

    2011-07-01

    Full Text Available The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a that recognition is often an ecologically valid cue; (b that people often follow recognition when making inferences; (c that recognition supersedes further cue knowledge; (d that its use can produce the less-is-more effect—the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference.

  17. Recognition of Face and Emotional Facial Expressions in Autism

    OpenAIRE

    Muhammed Tayyib Kadak; Burak Dogangn; Turkay Demir

    2013-01-01

    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 s...

  18. Recognition of Face and Emotional Facial Expressions in Autism

    OpenAIRE

    Kadak, Muhammed Tayyib; Demir, Türkay; Doğangün, Burak

    2013-01-01

    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...

  19. An Optical Character Recognition for Handwritten Devanagari Script

    Directory of Open Access Journals (Sweden)

    Trupti R. Zalke

    2015-01-01

    Full Text Available Optical Character Recognition is process of recognition of character from scanned document and lots of OCR now available in the market. But most of these systems work for Roman, Chinese, Japanese and Arabic characters . There are no sufficient number of work on Indian language script like Devanagari so this paper present a review on optical character recognition on handwritten Devanagari script.

  20. The recognition heuristic: a review of theory and tests.

    Science.gov (United States)

    Pachur, Thorsten; Todd, Peter M; Gigerenzer, Gerd; Schooler, Lael J; Goldstein, Daniel G

    2011-01-01

    The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect - the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference). PMID:21779266

  1. Phonological modeling for continuous speech recognition in Korean

    CERN Document Server

    Lee, W I; Lee, J H; Lee, WonIl; Lee, Geunbae; Lee, Jong-Hyeok

    1996-01-01

    A new scheme to represent phonological changes during continuous speech recognition is suggested. A phonological tag coupled with its morphological tag is designed to represent the conditions of Korean phonological changes. A pairwise language model of these morphological and phonological tags is implemented in Korean speech recognition system. Performance of the model is verified through the TDNN-based speech recognition experiments.

  2. Setting a world record in 3D face recognition

    NARCIS (Netherlands)

    Spreeuwers, Luuk

    2015-01-01

    Biometrics - recognition of persons based on how they look or behave, is the main subject of research at the Chair of Biometric Pattern Recognition (BPR) of the Services, Cyber Security and Safety Group (SCS) of the EEMCS Faculty at the University of Twente. Examples are finger print recognition, ir

  3. Doping graphene films via chemically mediated charge transfer

    Directory of Open Access Journals (Sweden)

    Ishikawa Ryousuke

    2011-01-01

    Full Text Available Abstract Transparent conductive films (TCFs are critical components of a myriad of technologies including flat panel displays, light-emitting diodes, and solar cells. Graphene-based TCFs have attracted a lot of attention because of their high electrical conductivity, transparency, and low cost. Carrier doping of graphene would potentially improve the properties of graphene-based TCFs for practical industrial applications. However, controlling the carrier type and concentration of dopants in graphene films is challenging, especially for the synthesis of p-type films. In this article, a new method for doping graphene using the conjugated organic molecule, tetracyanoquinodimethane (TCNQ, is described. Notably, TCNQ is well known as a powerful electron accepter and is expected to favor electron transfer from graphene into TCNQ molecules, thereby leading to p-type doping of graphene films. Small amounts of TCNQ drastically improved the resistivity without degradation of optical transparency. Our carrier doping method based on charge transfer has a huge potential for graphene-based TCFs.

  4. Chemically-mediated quantum criticality in NbFe2

    Energy Technology Data Exchange (ETDEWEB)

    Alam, Aftab; Johnson, Duane

    2011-11-09

    Laves-phase Nb{sub 1+c}Fe{sub 2-c} is a rare itinerant intermetallic compound exhibiting magnetic quantum criticality at c{sub cr} {approx} 1.5% Nb excess; its origin, and how alloying mediates it, remains an enigma. For NbFe{sub 2}, we show that an unconventional band critical point above the Fermi level E{sub F} explains most observations and that chemical alloying mediates access to this unconventional band critical point by an increase in E{sub F} with decreasing electrons (increasing %Nb), counter to rigid-band concepts. We calculate that E{sub F} enters the unconventional band critical point region for c{sub cr} > 1.5% Nb and by 1.74% Nb there is no Nb site-occupation preference between symmetry-distinct Fe sites, i.e., no electron-hopping disorder, making resistivity near constant as observed. At larger Nb (Fe) excess, the ferromagnetic Stoner criterion is satisfied.

  5. Workpiece defect recognition methods based on industrial CT

    International Nuclear Information System (INIS)

    Industrial CT is an effective method of workpiece defect recognition, which represents the development orientation of nondestructive test. This paper first summarizes the application of Industrial CT to workpiece defect recognition, and makes a brief comparison with other common ways. Then, each step of recognition process is explained form the aspects of the idea and the methods. In the following part, some methods which have potentials in workpiece defect recognition (Level Set method and Gabor analysis) were introduced and analyzed. Finally, the prospect of industrial CT application to workpiece defect recognition is discussed. (authors)

  6. The Phase Spectra Based Feature for Robust Speech Recognition

    Directory of Open Access Journals (Sweden)

    Abbasian ALI

    2009-07-01

    Full Text Available Speech recognition in adverse environment is one of the major issue in automatic speech recognition nowadays. While most current speech recognition system show to be highly efficient for ideal environment but their performance go down extremely when they are applied in real environment because of noise effected speech. In this paper a new feature representation based on phase spectra and Perceptual Linear Prediction (PLP has been suggested which can be used for robust speech recognition. It is shown that this new features can improve the performance of speech recognition not only in clean condition but also in various levels of noise condition when it is compared to PLP features.

  7. Offline Handwriting Recognition using Genetic Algorithm

    CERN Document Server

    Kala, Rahul; Shukla, Anupam; Tiwari, Ritu

    2010-01-01

    Handwriting Recognition enables a person to scribble something on a piece of paper and then convert it into text. If we look into the practical reality there are enumerable styles in which a character may be written. These styles can be self combined to generate more styles. Even if a small child knows the basic styles a character can be written, he would be able to recognize characters written in styles intermediate between them or formed by their mixture. This motivates the use of Genetic Algorithms for the problem. In order to prove this, we made a pool of images of characters. We converted them to graphs. The graph of every character was intermixed to generate styles intermediate between the styles of parent character. Character recognition involved the matching of the graph generated from the unknown character image with the graphs generated by mixing. Using this method we received an accuracy of 98.44%.

  8. Spoken Word Recognition Strategy for Tamil Language

    Directory of Open Access Journals (Sweden)

    An. Sigappi

    2012-01-01

    Full Text Available This paper outlines a strategy for recognizing a preferred vocabulary of words spoken in Tamil language. The basic philosophy is to extract the features using mel frequency cepstral coefficients (MFCC from the spoken words that are used as representative features of the speech to create models that aid in recognition. The models chosen for the task are hidden Markov models (HMM and autoassociative neural networks (AANN. The HMM is used to model the temporal nature of speech and the AANNs to capture the distribution of feature vectors in the feature space. The created models provide a way to investigate an unexplored speech recognition arena for the Tamil language. The performance of the strategy is evaluated for a number of test utterances through HMM and AANN and the results project the reliability of HMM for emerging applications in regional languages.

  9. Chinese handwriting recognition an algorithmic perspective

    CERN Document Server

    Su, Tonghua

    2013-01-01

    This book provides an algorithmic perspective on the recent development of Chinese handwriting recognition. Two technically sound strategies, the segmentation-free and integrated segmentation-recognition strategy, are investigated and algorithms that have worked well in practice are primarily focused on. Baseline systems are initially presented for these strategies and are subsequently expanded on and incrementally improved. The sophisticated algorithms covered include: 1) string sample expansion algorithms which synthesize string samples from isolated characters or distort realistic string samples; 2) enhanced feature representation algorithms, e.g. enhanced four-plane features and Delta features; 3) novel learning algorithms, such as Perceptron learning with dynamic margin, MPE training and distributed training; and lastly 4) ensemble algorithms, that is, combining the two strategies using both parallel structure and serial structure. All the while, the book moves from basic to advanced algorithms, helping ...

  10. Speech emotion recognition with unsupervised feature learning

    Institute of Scientific and Technical Information of China (English)

    Zheng-wei HUANG; Wen-tao XUE; Qi-rong MAO

    2015-01-01

    Emotion-based features are critical for achieving high performance in a speech emotion recognition (SER) system. In general, it is difficult to develop these features due to the ambiguity of the ground-truth. In this paper, we apply several unsupervised feature learning algorithms (including K-means clustering, the sparse auto-encoder, and sparse restricted Boltzmann machines), which have promise for learning task-related features by using unlabeled data, to speech emotion recognition. We then evaluate the performance of the proposed approach and present a detailed analysis of the effect of two important factors in the model setup, the content window size and the number of hidden layer nodes. Experimental results show that larger content windows and more hidden nodes contribute to higher performance. We also show that the two-layer network cannot explicitly improve performance compared to a single-layer network.

  11. Active Appearance Model Based Hand Gesture Recognition

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    This paper addresses the application of hand gesture recognition in monocular image sequences using Active Appearance Model (AAM). For this work, the proposed algorithm is conposed of constructing AAMs and fitting the models to the interest region. In training stage, according to the manual labeled feature points, the relative AAM is constructed and the corresponding average feature is obtained. In recognition stage, the interesting hand gesture region is firstly segmented by skin and movement cues.Secondly, the models are fitted to the image that includes the hand gesture, and the relative features are extracted.Thirdly, the classification is done by comparing the extracted features and average features. 30 different gestures of Chinese sign language are applied for testing the effectiveness of the method. The Experimental results are given indicating good performance of the algorithm.

  12. Texture Recognition using Robust Markovian Features

    Czech Academy of Sciences Publication Activity Database

    Vácha, Pavel; Haindl, Michal

    Berlin: Springer, 2012, s. 126-137. (Lecture Notes in Computer Science. 7252). ISBN 978-3-642-32435-2. ISSN 0302-9743. [MUSCLE. Pisa (IT), 13.12.2011-15.12.2011] R&D Projects: GA MŠk 1M0572; GA ČR GAP103/11/0335; GA ČR GA102/08/0593 Grant ostatní: CESNET(CZ) 387/2010 Institutional support: RVO:67985556 Keywords : texture recognition * illumination invariance * Markov random fields * Bidirectional Texture Function * textural databases Subject RIV: BD - Theory of Information http://library.utia.cas.cz/separaty/2012/RO/vacha-texture recognition using robust markovian features.pdf

  13. Visualization of License Plate Recognition System

    Directory of Open Access Journals (Sweden)

    Zhiyi Ruan

    2013-11-01

    Full Text Available The image of the license plate is located and segmented by some digital-image processing technologies such as gray-scale processing, gray-scale stretching and filtering, edge detection, morphological processing, Hough transformation etc. According to the characteristics of the license plate, binary matrix of character image sets the fuzzy matrix, and based on the principle of proximity computing space of closeness to get the fuzzy pattern recognition of characters. On the basis of the data of image pixels, the samples which are randomly selected under noisy condition and which are treated by morphological processing are randomly selected, and then the samples are used to test the simulation and identification of Back Propagation (BP Neural Networks. With the mathematical software-Matlab programming, the license plates are recognized. The aim is to develop the Visualization of user interface in License Plate Recognition System.  

  14. Recognition of Words from the EEG Laplacian

    CERN Document Server

    de Barros, J Acacio; de Mendonça, J P R F; Suppes, P

    2012-01-01

    Recent works on the relationship between the electro-encephalogram (EEG) data and psychological stimuli show that EEG recordings can be used to recognize an auditory stimulus presented to a subject. The recognition rate is, however, strongly affected by technical and physiological artifacts. In this work, subjects were presented seven auditory simuli in the form of English words (first, second, third, left, right, yes, and no), and the time-locked electric field was recorded with a 64 channel Neuroscan EEG system. We used the surface Laplacian operator to eliminate artifacts due to sources located at regions far from the electrode. Our intent with the Laplacian was to improve the recognition rates of auditory stimuli from the electric field. To compute the Laplacian, we used a spline interpolation from spherical harmonics. The EEG Laplacian of the electric field were average over trials for the same auditory stimulus, and with those averages we constructed prototypes and test samples. In addition to the Lapla...

  15. Hierarchical Neural Network Structures for Phoneme Recognition

    CERN Document Server

    Vasquez, Daniel; Minker, Wolfgang

    2013-01-01

    In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are evaluated on the phoneme recognition task where a  Hybrid Hidden Markov Model/Artificial Neural Network paradigm is used. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron. Additionally, the output of the first level serves as a second level input. The computational speed of the phoneme recognizer can be substantially increased by removing redundant information still contained at the first level output. Several techniques based on temporal and phonetic criteria have been investigated to remove this redundant information. The computational time could be reduced by 57% whilst keeping the system accuracy comparable to the baseline hierarchical approach.

  16. Photonics: From target recognition to lesion detection

    Science.gov (United States)

    Henry, E. Michael

    1994-01-01

    Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

  17. Static hand gesture recognition from a video

    Science.gov (United States)

    Rokade, Rajeshree S.; Doye, Dharmpal

    2011-10-01

    A sign language (also signed language) is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns to convey meaning- "simultaneously combining hand shapes, orientation and movement of the hands". Sign languages commonly develop in deaf communities, which can include interpreters, friends and families of deaf people as well as people who are deaf or hard of hearing themselves. In this paper, we proposed a novel system for recognition of static hand gestures from a video, based on Kohonen neural network. We proposed algorithm to separate out key frames, which include correct gestures from a video sequence. We segment, hand images from complex and non uniform background. Features are extracted by applying Kohonen on key frames and recognition is done.

  18. Protein-targeted corona phase molecular recognition

    Science.gov (United States)

    Bisker, Gili; Dong, Juyao; Park, Hoyoung D.; Iverson, Nicole M.; Ahn, Jiyoung; Nelson, Justin T.; Landry, Markita P.; Kruss, Sebastian; Strano, Michael S.

    2016-01-01

    Corona phase molecular recognition (CoPhMoRe) uses a heteropolymer adsorbed onto and templated by a nanoparticle surface to recognize a specific target analyte. This method has not yet been extended to macromolecular analytes, including proteins. Herein we develop a variant of a CoPhMoRe screening procedure of single-walled carbon nanotubes (SWCNT) and use it against a panel of human blood proteins, revealing a specific corona phase that recognizes fibrinogen with high selectivity. In response to fibrinogen binding, SWCNT fluorescence decreases by >80% at saturation. Sequential binding of the three fibrinogen nodules is suggested by selective fluorescence quenching by isolated sub-domains and validated by the quenching kinetics. The fibrinogen recognition also occurs in serum environment, at the clinically relevant fibrinogen concentrations in the human blood. These results open new avenues for synthetic, non-biological antibody analogues that recognize biological macromolecules, and hold great promise for medical and clinical applications.

  19. Probabilistic recognition of human faces from video

    DEFF Research Database (Denmark)

    Zhou, Saohua; Krüger, Volker; Chellappa, Rama

    2003-01-01

    Recognition of human faces using a gallery of still or video images and a probe set of videos is systematically investigated using a probabilistic framework. In still-to-video recognition, where the gallery consists of still images, a time series state space model is proposed to fuse temporal...... information in a probe video, which simultaneously characterizes the kinematics and identity using a motion vector and an identity variable, respectively. The joint posterior distribution of the motion vector and the identity variable is estimated at each time instant and then propagated to the next time...... instant. Marginalization over the motion vector yields a robust estimate of the posterior distribution of the identity variable. A computationally efficient sequential importance sampling algorithm is developed to provide numerical solution to the model. Theoretical derivations under minor assumptions...

  20. Action Recognition Using Discriminative Structured Trajectory Groups

    KAUST Repository

    Atmosukarto, Indriyati

    2015-01-06

    In this paper, we develop a novel framework for action recognition in videos. The framework is based on automatically learning the discriminative trajectory groups that are relevant to an action. Different from previous approaches, our method does not require complex computation for graph matching or complex latent models to localize the parts. We model a video as a structured bag of trajectory groups with latent class variables. We model action recognition problem in a weakly supervised setting and learn discriminative trajectory groups by employing multiple instance learning (MIL) based Support Vector Machine (SVM) using pre-computed kernels. The kernels depend on the spatio-temporal relationship between the extracted trajectory groups and their associated features. We demonstrate both quantitatively and qualitatively that the classification performance of our proposed method is superior to baselines and several state-of-the-art approaches on three challenging standard benchmark datasets.