Sonerud, G. A.; Smedshaug, C. A.; Bråthen, O.
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...
Carlo, Troy; Levy, Bruce D.
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...
Haugen, Liv Merete; Olavsbråten, Inge
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...
Diefenderfer, Graig T.
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...
Rabiner, Lawrence R.
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.
Shy, Oz; Stenbacka , Rune
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 ...
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.
Wang, Man-Ying; Ching, Chi-Le
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
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...
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.
Cornel, Michiel; van Zutphen, Wim M.
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.
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.
Ali, Nanna; Ben-Ahmed, Michele; Bom, Thomas Falk; Ching, Rune Kieran; Steffensen, Lars Schmidt; Funningsstovu, Janus Hanusarson í
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...
Fichtner, K. -H.; Freudenberg, W.; Ohya, M.
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.
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
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
Yu, Francis T. S.; Jutamulia, Suganda
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.
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.
MAYANK PARASHER; SHRUTI SHARMA; A .K. SHARMA,; J.P.Gupta
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...
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...
Webb, Andrew R
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,
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)
Ahlmark, Nanna; Whyte, Susan Reynolds; Harting, Janneke;
-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...
Li, Stan Z
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
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
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.
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
-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...
Sturm, Bob L.
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....
Bendale, Abhijit; Boult, Terrance
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...
Ronak P Patel; Narendra M Patel; Keyur Brahmbhatt
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...
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...
Bhawna Negi; Varun Sharma
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 ...
This thesis is a continuation of the authors 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 authors goal was to increase the flexibility, usability and perfor...
Elsass, Peter; Jensen, Bodil; Mørup, Rikke;
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...
Clintin P. Davis-Stober
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.
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
Genovese, Angelo; Scotti, Fabio
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
Dai, Dao-Qing; Yan, Hong
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.
Perepelitsa, VA; Sergienko, [No Value; Kochkarov, AM
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
SONMEZ, Öznur Sinem; OZTAS, Oguzhan
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 ...
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.
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...
DIMA FLORIN CONSTANTIN
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.
Ali, Tauseef; Spreeuwers, Luuk; Veldhuis, Raymond; Quaglia, Adamo; Epifano, Calogera M.
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
Rodrigues, Marcos; Robinson, Alan; Alboul, Lyuba; Brink, Willie
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.
Putyatin, Yevgeniy; Gorohovatsky, Vladimir; Gorohovatsky, Alexey; Peredriy, Elena
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.
Mansi Jhamb, Vinod Kumar Khera
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.
Meenakshi,R. B. Dubey
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.
Liu, Ming; Xu, Xun; Huang, Thomas S.
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.
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.
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’
Khaliq Masood; Muhammad Younus Javed; Abdul Basit
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...
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 ...
Lee, Colin K.
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 ...
Neeta Sarode; Prof. Shalini Bhatia
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...
Hammer, Dana; Piascik, Peggy; Medina, Melissa; Pittenger, Amy; Rose, Renee; Creekmore, Freddy; Soltis, Robert; Bouldin, Alicia; Schwarz, Lindsay; Scott, Steven
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...
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.
Moore, R. K.
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).
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
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...
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 '
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. .
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.
Pillai, Sudeep; Leonard, John,
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...
Anushree S. Patil; Sushil M. Rajbhoj
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...
Wald, Mike; Bain, Keith; Basson, Sara H
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...
Ali, Tauseef; Veldhuis, Raymond; Spreeuwers, Luuk
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 , guidelin...
Sumant Raj Chauhan; Punit Soni
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...
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...
Avinash Prakash Pandhare; Umesh Balkrishna Chavan
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...
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
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.
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.
Tascini, Guido; Passerini, Giorgio; Puliti, Paolo; Zingaretti, Primo
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.
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 rotaxanes can be switched by altering electrochemical potentials. In a tristable 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.
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.
De Meulder, Maartje
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…
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.
Osadchy, Margarita; Keren, Daniel; Raviv, Dolev
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
Wagner, J.S.; Trahan, M.W.; Nelson, W.E.; Hargis, P.J. Jr.; Tisone, G.C.
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.
Wagner, J.S.; Trahan, M.W.; Nelson, W.E.; Hargis, P.H. Jr.; Tisone, G.C.
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.
Parul,R. B. Dubey
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.
Ali, Tauseef; Veldhuis, Raymond; Spreeuwers, Luuk
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
WANG Xiaohong; ZHAO Rongchun
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.
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.
Li, Jun-Bao; Pan, Jeng-Shyang
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
Santemiz, Pinar; Spreeuwers, Luuk J.; Veldhuis, Raymond N. J.; Biggelaar, van den, M.
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...
Santemiz, Pinar; Spreeuwers, Luuk J.; Veldhuis, Raymond N. J.
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...
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
Hashidzume, Akihito; Harada, Akira
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.
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...
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.
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.
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...
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
Muhammad Sharif; Sajjad Mohsin; Muhammad Younas Javed
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...
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...
Harmat, Veronika; Náray-Szabó, Gábor
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...
de Paiva, Gilberto
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...
Hanhela, T. (Teemu)
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...
James V Stone
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 ...
Rajshree Dhruw; Dharmendra Roy
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...
Senthil Ragavan Valayapalayam Kittusamy; Venkatesh Chakrapani
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...
Roytberg, M A; Astakhova, T V; Gelfand, M S
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
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...
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.
Sferrella, Sheila M
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
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.
Jacobsen, Michael Hviid; Kristiansen, Søren
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...
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...
Nussipbekov, A. K.; Amirgaliyev, E. N.; Hahn, Minsoo
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.
Anushree S. Patil
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.
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.
Monnig, Nathan D.; Sakla, Wesam
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.
LI Zhan; XU Ji-sheng; XU Min; SUN Hong
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.
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 .It improving the interface between man and machine in many applications
Anne, Koteswara Rao; Vankayalapati, Hima Deepthi
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.
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
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
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
Hoogsteen, G; Krist, J.O.; Bakker, V.; Smit, G.J.M.
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
Tan, Zheng-Hua; Lindberg, Børge
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...
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].
Du, Qianzhou; Xuan ZHANG
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.
Joswig, Michael; Lutz, Frank H.; Tsuruga, Mimi
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.
Li Zheng Dong; He Wu Liang; Pei Chun Lan; Peng Wen; SongChen; Zheng Xiao Dong
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
Sumant Raj Chauhan
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.
Prof.D.D.Patil; Prof.N.A.Nemade; K.M.Attarde
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.
Podilchuk, Christine; Hulbert, William; Flachsbart, Ralph; Barinov, Lev
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.(
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.
Manfredotti, Cristina Elena; Fleet, David J.; Hamilton, Howard J.;
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...
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
Saleh A.K. Al-Omari
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
Garris, Michael D.; Blue, James L.; Candela, Gerald T.; Dimmick, Darrin L.; Geist, Jon C.; Grother, Patrick J.; Janet, Stanley A.; Wilson, Charles L.
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.
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.
Ma Chi; Zhu Yongyong; Tian Ying
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...
Wang, Patrick S P
""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
Dr.Asmahan M Altaher
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...
Bjerre, Henrik Jøker
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....
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 ...
Olsen, Søren I.
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....
Daniela COLTUC; Laurentiu FRANGU; Ana-Elena LUNGU
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.
Klinger, A; Kunii, T L
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
Bradler, C.; Dur, R.; Neckermann, S.; Non, J.A.
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...
Hlaing Htake Khaung Tin
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...
... 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...
Saeed, Khalid; Dardzinska, Agnieszka
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)
Muhammad Hameed Siddiqi
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.
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
Rafiqul Zaman Khan
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
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.)
Craciunescu, Razvan; Mihovska, Albena Dimitrova; Kyriazakos, Sofoklis;
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...
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.
J Sheeba Rani; D Devaraj
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.
H. D. Ellis
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.
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.
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...
Rao, K Sreenivasa
“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...
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, ...
Saurabh D. Parmar,
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.
D'Ettorre, Patrizia; Heinze, Jürgen
recognize each other's unique facial color patterns  . 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...
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.
Fihl, Preben; Holte, Michael Boelstoft; Moeslund, Thomas B.
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....
Huebener, K; Huebener, Kai; Carson-Berndsen, Julie
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.
Pan, Gang; Wu, Zhaohui; Sun, Lin
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...
Gurung, Deepak; Jiang, Cansen; Deray, Jeremie; Sidibé, Désiré
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...
Zhou, Tongqing; Hamer, Dean H.; Hendrickson, Wayne A.; Sattentau, Quentin J.; Kwong, Peter D.
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...
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...
Santosh Kumar; Sanjay Kumar Singh
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...
Chappelier, Jean-Cédric; Rajman, Martin; Aragües, Ramon; Rozenknop, Antoine
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...
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.
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
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...
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.
Müller, Christian; Despras, Guillaume; Lindhorst, Thisbe K
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
Baldi, Pierre; Chauvin, Yves
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...
Yoon, Soweon; Anil K Jain
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...
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...
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...
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.
Wenndt, Stanley J
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
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...
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.
Reynolds, Greg D.
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
Susilo, Tirta; Wright, Victoria; Tree, Jeremy J; Duchaine, Bradley
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
Gribble Kristin E
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
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 Daugmans 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.
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
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.
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.
Dr.Asmahan M Altaher
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.
GAOJun; DONGHuoming; SHAOJing; ZHAOJing
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.
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.
BAI BoFeng; ZHANG ShaoJun; ZHAO Liang; ZHANG XiMin; GUO LieJin
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.
Fruchterman, James R.
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.
Kriti Sharma*1,; Himanshu Monga2
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...
S.PON SANGEETHA; DR.M.KARNAN
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...
González-Díaz, Iván; Boujut, Hugo; Buso, Vincent; Benois-Pineau, Jenny; Domenger, Jean-Philippe
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...
Wenjuan Gong; Weishan Zhang; Jordi Gonzàlez; Yan Ren; Zhen Li
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...
Minaee, Shervin; Wang, Yao
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...
Titus Felix FURTUNA
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.
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.
Tencer, Lukas; Režnáková, Marta; Cheriet, Mohamed
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 ...
Richard Mo; Adnan Shaout
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 ...
Yafeng Li; Changjiang Song; Xingpeng Xu; Zhenhua Guo
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, ...
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
Artur Popko; Marek Jakubowski; Rafał Wawer
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...
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.
Jamal Ahmad Dargham; Ali Chekima; Ervin Gubin Moung
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 ...
Chen, Xiaoming; Cheng, Wushan
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. 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...
Khattab M. Ali Alheeti
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.
Theodoridis, Sergios; Koutroumbas, Konstantinos; Cavouras, Dionisis
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
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)
Matthew K Luka
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.
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
Olsen, Søren I.
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....
Nehring, Volker; Evison, Sophie E F; Santorelli, Lorenzo A;
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...
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.
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.
Woo, Seng-Ryong; Corrales, Leticia; Gajewski, Thomas F
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
Claudia Sassenrath; Kai Sassenberg; Devin G Ray; Katharina Scheiter; Halszka Jarodzka
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...
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.)
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....
Lee, Chang H.; Kwon, Youan; Kim, Kyungil; Rastle, Kathleen
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…
Fernando, Basura; Gavves, Stratis; Oramas Mogrovejo, José Antonio; Ghodrati, Amir; Tuytelaars, Tinne
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.
Wild, Peter; Radu, Petru; Ferryman, James
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 ...
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.
Bergstein, Jacquelyn; Erdelyi, Matthew
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
Herzog, Dennis; Krüger, Volker
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...
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.
Pang, Chao-Yang; Ding, Cong-Bao; Hu, Ben-Qiong
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
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.
Møller, Maiken Bjerg; Gaarsdal, Jesper; Steen, Kim Arild;
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...
Vácha, Pavel; Haindl, Michal
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
Broadbent, Nicola J.; Gaskin, Stephane; Squire, Larry R.; Clark, Robert E.
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…
LI Xungao; FENG Xinxin; GE Yi
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.
Segelke, Brent W.; Toppani, Dominique
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.
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
Rawan I. Zaghloul
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.
Dmitry Lyusin; Victoria Ovsyannikova
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...
Pham, Viet-Khoi; Nguyen, Hai-Dang; Nguyen-Khac, Tung-Anh; Tran, Minh-Triet
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%.
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.
ROH Yong-Wan; KIM Dong-Ju; LEE Woo-Seok; HONG Kwang-Seok
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.
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.
Smead, Rory; Forber, Patrick
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
Quan, Changqin; Ren, Fuji
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.
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.
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.
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.
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