The availability of high quality and inexpensive video camera, as well as the increasing need for automated video analysis is leading towards a great deal of interest in numerous applications. However the video tracki...
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PWGL is a visual composition environment that can be used to, among other things, solve musical constraints problems. The constraints system within PWGL, PWGLConstraints, allows us to write rules using a special patte...
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Several system require authenticating a person39;s identity before giving access to resources. With new advances in technology, biometrics is one of the most promising techniques in recognition human. Biometrics int...
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Several system require authenticating a person's identity before giving access to resources. With new advances in technology, biometrics is one of the most promising techniques in recognition human. Biometrics intends to identify a person by his physical and/or behavioural characteristic. Among biometric technologies, iris recognition has received increasing attention due to its high reliability. Iris recognition is a biometric authentication technology that uses patternrecognition techniques based on iris characteristics. In this paper we propose a new biometric-based Iris segmentation system. The system acquires the biometric data in the data base CASIA version 1.0. The experimental results are compared to release the performances of our algorithms.
This paper presents a lossless data hiding approach based on Discrete Cosine Transform (DCT) as a new application of watermarking. In this application, a depth map obtained from a stereoscopic image pair is embedded i...
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Electrooculography (EOG) signal is one of the useful biomedical signals. Development of EOG signal as a control signal has been paid more increasing interest in the last decade. In this study, we are proposing a robus...
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ISBN:
(纸本)9783642221903
Electrooculography (EOG) signal is one of the useful biomedical signals. Development of EOG signal as a control signal has been paid more increasing interest in the last decade. In this study, we are proposing a robust classification algorithm of eight useful directional movements that it can avoid effect of noises, particularly eye-blink artifact. Threshold analysis is used to detect onset of the eye movements. Afterward, four beneficial time features are proposed that are peak and valley amplitude positions, and upper and lower lengths of two EOG channels. Suitable threshold conditions were defined and evaluated. From experimental results, optimal threshold values were selected for each parameters and classification accuracies approach to 100% for three subjects testing. To avoid the eye-blink artifact, the first derivative was additionally implemented.
In this paper we report results from unsupervised texture image classification on a data set of images collected with our intelligent machine vision system for patternrecognition (assuming no a priori human vision ex...
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ISBN:
(纸本)9781601321855
In this paper we report results from unsupervised texture image classification on a data set of images collected with our intelligent machine vision system for patternrecognition (assuming no a priori human vision expert knowledge is available for the image classes). The simulation of the investigated system includes four main phases: data collection and feature extraction, feature analysis, classifier training, and classifier testing and evaluation. Self-Organizing Maps (SOM) are used for classification of the collection of images into several classes, based on their features and texture characteristics. Three main experiments are conducted during this research: in the first one, all extracted features are used for training the classifiers without any statistical pre-processing of the dataset;in the second simulation, the classifiers are trained after normalization of the available data;and in the last experiment, the trained SOMs use linear transformations of the original features, received after pre-processing with principal component analysis (PCA). Each test is performed 50 times and the classification results are assessed using three commonly applied metrics, namely: accuracy rate, sensitivity and specificity. Finally, the findings of this investigation are compared with results from other authors.
Yang-Yang proposed a new key authentication scheme based on fuzzy extractor with Smart Card. The authors claimed their scheme can resist the guessing attack, the parallel attack, masquerade attack and other attack typ...
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Yang-Yang proposed a new key authentication scheme based on fuzzy extractor with Smart Card. The authors claimed their scheme can resist the guessing attack, the parallel attack, masquerade attack and other attack types. In this paper, we find that the scheme proposed by Yang-Yang was unable to resist the masquerade attack as they originally claimed.
The proceedings contain 30 papers. The special focus in this conference is on Tools for Teaching Logic. The topics include: Panda: A Proof Assistant in Natural Deduction for All. A Gentzen Style Proof Assistant for Un...
ISBN:
(纸本)9783642213496
The proceedings contain 30 papers. The special focus in this conference is on Tools for Teaching Logic. The topics include: Panda: A Proof Assistant in Natural Deduction for All. A Gentzen Style Proof Assistant for Undergraduate Students;the Question of the Question in Critical Thinking?;adding a Dimension to Logic Diagramming;the Many Rewards of Putting Absolutely Everything into Introductory Logic;The SELL Project: A Learning Tool for E-Learning Logic;ten Years of Computer-Based Tutors for Teaching Logic 2000-2010: Lessons Learned;logic in Action: An Open Logic Courseware Project;a Teaching Tool for Proving Equivalences between Logical Formulae;mhy Bib I Fail Logic? Dyslexia in the Teaching of Logic;e-learning and Semantic Technologies: Tools and Concepts;information-Theoretic Perspective for Teaching Logic;teaching Sound Principles about Invalidity;systematic Errors as an Input for Teaching Logic;The AProS Project: Teaching Logic to Business and Engineering Students;using a Learner- and Teacher-Friendly Environment for Turing machine Programming and Testing;using an Argument Ontology to Develop Pedagogical Tool Suites;visual Tools for Teaching Propositional Logic;logicamente: A Virtual Learning Environment for Logic Based on Learning Objects;a Framework for Coping with Logically-Minded Arguments in Philosophy;a Logic Teaching Tool Based on Tableaux for Verification and Debugging of Algorithms;CT2.0: A Collaborative Database of Examples for Teaching Informal Logic;designing an Introductory Course to Elementary Symbolic Logic within the Blackboard E-learning Environment;Araucaria-PL: Software for Teaching Argumentation Theory;teaching Logic in Philosophy;ORGANON: Learning Management System for Basic Logic Courses;variables in Mathematics Education.
Notice of Violation of IEEE Publication Principles "Neural network Based Intelligent Local Face recognition Using Local pattern Averaging" by *** Reddy, *** Krishna, *** Reddy, *** in the 2011 3rd Internatio...
Notice of Violation of IEEE Publication Principles "Neural network Based Intelligent Local Face recognition Using Local pattern Averaging" by *** Reddy, *** Krishna, *** Reddy, *** in the 2011 3rdinternationalconference on Electronics Computer Technology (ICECT), July 7, 2011, pp. 363 – 367 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. This paper contains significant portions of original text from the paper cited below. The original text was copied with insufficient attribution (including appropriate references to the original author(s) and/or paper title) and without permission. Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article: "Intelligent Local Face recognition" by Adnan Khashman in Recent Advances in Face recognition, Kresimir Delac, Mislav Grgic and Marian Stewart Bartlett (Ed.), InTech, 2008 This paper presents a brief review of known face recognition methods such as Principal Component Analysis (PCA) (Turk & Pentland, 1991), Linear Discriminant Analysis (LDA) (Belhumeur et al., 1997) and Locality Preserving Projections (LPP) (He et al., 2005), in addition to intelligent face recognition systems that use neural networks such as (Khashman, 2006) and (Khashman, 2007). There are many works emerging every year suggesting different methods for face recognition (Delac & Grgic, 2007); these methods are mostly appearance. This paper will also provide a detailed case study on intelligent local face recognition, where a neural network is used to identify a person upon presenting his/her face image. Local pattern averaging is used for face image preprocessing prior to training or testing the neural network. Averaging is a simple but efficient method that creates
The Normalized Compression Distance (NCD) has gained considerable interest in patternrecognition as a similarity measure applicable to unstructured data of very different domains, such as text, DNA sequences, or imag...
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The Normalized Compression Distance (NCD) has gained considerable interest in patternrecognition as a similarity measure applicable to unstructured data of very different domains, such as text, DNA sequences, or images. NCD uses existing compression programs such as gzip to compute similarity between objects. NCD has unique features: It does not require any prior knowledge, data preprocessing, feature extraction, domain adaptation or any parameter settings. Further, the NCD can be applied to symbolic data and raw signals alike. In this paper we decompose the NCD and introduce a method to measure compression-based similarity without the need to use compression. The Length Delimiting Dictionary Distance (LD 3 ) takes the one component essential in compression methods, the dictionary generation, and strips the NCD of all dispensable components. The LD 3 performs "compression based patternrecognition without compression", keeping all of the above benefits of the NCD while achieving better speed and recognition rates. We first review the NCD, introduce LD 3 as the "essence" of NCD, and evaluate the LD 3 based on language tree experiments, authorship recognition, and genome phylogeny data.
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