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10 articles for “Iris Classification”
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Research ArticleOpen accessIn the keywordsNON-COOPERATIVE IRIS RECOGNITION: A NOVEL APPROACH FOR SEGMENTATION AND FAKE IDENTIFICATIONM. Rajeev Kumar, M. Dilsath Fathima, K. Kiruthika, M. S. SaravananIris recognition, the ability to recognize and distinguish individuals by their pattern, is the most reliable biometric in terms of recognition and identification performance. However, performance of these systems is affected by the heterogeneous images (regarding focus, contrast, or brightness) and with several noise factors (iris obstruction and reflection) when the cooperation is not expectable from the subject. Current Iris … …Journal of Computer Science, Vol. 9, Issue 9 · 6 Aug 2013 · 6,744 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Finger Vein Image Using Convolutional Neural NetworkAhmed S. Hameed, Shawkat K. Guirguis, Hend A. ElsayedCurrently available technologies can perform rather well, but their effectiveness is mostly contingent on how well the venous images being analyzed are quality images. Finger vein features have garnered significant attention in the past few years as a potential means of automatic user identification. A significant amount of daily usage goes into the very vital personal identification procedure. The identification … …Journal of Computer Science, Vol. 21, Issue 2 · 6 Jan 2025 · 4,712 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of LDA, AdaBoost and Ensemble Bag Classifiers for Automatically Recognizing Nine Common Facial ExpressionsM.D. Sumithra, M. Abdul RahimanFacial expression recognition holds a prominent role in today’s digital world with more Human –Computer Interaction happening in day to day life. Successful identification of facial expressions needs extraction of descriptive attributes from the active facial patches and accurate classification. This paper is presented with the comparison of three multi class classifiers namely Linear Discriminant Analysis, AdaBoost and Ensemble bag. … …Journal of Computer Science, Vol. 14, Issue 9 · 27 Sep 2018 · 7,787 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Review Study of Brain Activity-Based Biometric AuthenticationAla Abdulhakim Alariki, Abdul Wasi Ibrahimi, Mohammad Wardak, John WallBiometrics is the process of identifying an individual among others by biological means. Concerning security, biometric system is one of the best options available in this technology driven era. Places such as nuclear facilities, airports, banks etc. are on the frontline of security threats. Therefore, biometrics such as Iris, face and fingerprint recognition is frequently used to avoid any security … …Journal of Computer Science, Vol. 14, Issue 2 · 27 Jan 2018 · 9,471 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementation of Multi-Centroid Moment Invariants in Thermal-Based Face Identification SystemKhairul Hamimah Abas, Osamu OnoProblem statement: Current paramount methods and approaches in face identification field rely on facial characteristics; such as location of eyes, length of nose and mouth, regardless the type of medium used to acquire the facial images. The visibility of these facial characteristics varies significantly with environmental factors (e.g., lighting elements). Various researches have been devoted to develop methodologies for addressing … …American Journal of Applied Sciences, Vol. 7, Issue 3 · 31 Mar 2010 · 7,163 accessesView PDFCite
Research ArticleOpen accessIn the abstractFacial Features for Template Matching Based Face RecognitionChai Tong Yuen, M. Rizon, Woo San San, Tan Ching SeongProblem statement: Template matching had been a conventional method for object detection especially facial features detection at the early stage of face recognition research. The appearance of moustache and beard had affected the performance of features detection and face recognition system since ages ago. Approach: The proposed algorithm aimed to reduce the effect of beard and moustache for facial features … …American Journal of Applied Sciences, Vol. 6, Issue 11 · 30 Nov 2009 · 9,375 accessesView PDFCite
Research ArticleOpen accessIn the abstractIris Recognition Using Discrete Cosine Transform and Artificial Neural NetworksAhmad M. SarhanProblem statement: The study presented an efficient Iris recognition system. Approach: The design used the discrete cosine transform for feature extraction and artificial neural networks for classification. The iris images used in this system were obtained from the CASIA database. Results: A robust system for iris recognition was developed. Conclusion: An iris recognition system that produces very low error rates … …Journal of Computer Science, Vol. 5, Issue 5 · 30 May 2009 · 7,751 accessesView PDFCite
Research ArticleOpen accessIn the abstractRule Extraction from Radial Basis Functional Neural Networks by Using Particle Swarm OptimizationM. R. Senapati, I. Vijaya, P. K. DashRadial basis functional neural networks (RBFNN) provide an outstanding possibility for generating rules for solving pattern classification problems. One of the most important factors in RBFNN is finding out the center and spread. This paper examines rules extracted from RBF networks trained by Particle swarm Optimization (PSO). The selection of the RBFNN centers, spreads and the network weights can be … …Journal of Computer Science, Vol. 3, Issue 8 · 31 Aug 2007 · 6,784 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesign of Output Codes for Fast Covering Learning using Basic Decomposition TechniquesAruna Tiwari, Narendra S. ChaudhariWe propose the design of output codes for solving the classification problem in Fast Covering Learning Algorithm (FCLA). For a complex multi-class problem normally the classifiers are constructed by combining the outputs of several binary ones. In this paper, we use the basic methods of decomposition; one per class (OPC) and Error Correcting Output Code (ECOC) with FCLA, binary to … …Journal of Computer Science, Vol. 2, Issue 7 · 31 Jul 2006 · 6,302 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordFish Classification Based on Robust Features Extraction From Color Signature Using Back-Propagation ClassifierMutasem Khalil Alsmadi, Khairuddin Bin Omar, Shahrul Azman Mohd NoahProblem statement: Image recognition was a challenging problem researchers had been research into this area for so long especially in the recent years, due to distortion, noise, segmentation errors, overlap and occlusion of objects in digital images. In our study, there are many fields concern with pattern recognition, for example, fingerprint verification, face recognition, iris discrimination, chromosome shape discrimination, optical … …Journal of Computer Science, Vol. 7, Issue 1 · 27 Dec 2010 · 8,636 accessesView PDFCite