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93 articles for “Image Feature Extraction”
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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 · 7,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study of Data Mining approaches for Bag of Visual Words Based Image ClassificationSahar Abd El Hameed Mokhtar, Heba Ahmed ElnemrImage classification is one of the most significant and challenging tasks in computer vision. The goal of this task is to build a system that is capable to reveal an image label within a collection of different image categories. This paper presents and discusses the application of various data mining techniques for image classification based on Bag of Visual Words … …Journal of Computer Science, Vol. 14, Issue 1 · 12 Jan 2018 · 7,990 accessesView PDFCite
Research ArticleOpen accessIn the abstractRecognition of Faces using Efficient Multiscale Local Binary Pattern and Kernel Discriminant Analysis in Varying EnvironmentSujata G. Bhele, V.H. MankarFace recognition involves matching face images with different environmental conditions. Matching face images with different environmental conditions is not a easy task. Also matching face images considering variations such as changing illumination, pose, facial expression and that with uncontrolled conditions becomes more difficult. This paper focuses on accurately recognizing face images considering all the above variations. The proposed system is … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 3 · 31 Aug 2017 · 8,137 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Feature Extraction Method for Accuracy Improvement in “Aksara Lontara” TranslationIntan Sari Areni, Asyraful Insan Asry, IndrabayuAn Optical Character Recognition (OCR) of “Aksara Lontara” has been constructed using a novel combination of feature extraction methods in this study. The ancient font of “Lontara” is then translated into Bahasa Indonesia to help non-native language to learn this language. Two powerful extraction feature methods, i.e., Modified Direction Feature (MDF) and Fourier Descriptor (FD) are stages combined to deal … …Journal of Computer Science, Vol. 13, Issue 9 · 27 Aug 2017 · 8,855 accessesView PDFCite
Research ArticleOpen accessIn the abstractStructural Geodesic-Tchebychev Transform: An Image Similarity Measure for Face RecognitionAli Nadhim Razzaq, Zahir M. Hussain, Hind Rustum MohammedThis work presents a new holistic measure for face recognition. Face recognition involves three steps: Face Detection, Feature Extraction and Matching. In the face detection process to identify the face area in face images, Viola-Jones algorithm has been used. Feature extraction is based on performing double-transformation, where discrete Tchebychev transform is performed on the geodesic distance transform of the grayscale … …Journal of Computer Science, Vol. 12, Issue 9 · 29 Nov 2016 · 7,645 accessesView PDFCite
Research ArticleOpen accessIn the abstractRADIUS BASED BLOCK LOCAL BINARY PATTERN ON T-ZONE FACE AREA FOR FACE RECOGNITIONMd. Jan Nordin, Abdul Aziz K. Abdul Hamid, Sumazly Ulaiman, R. U. GobithaasanThis study presents a comparison of recognition performance between feature extraction on the T-Zone face area and Radius based block on the critical point. A T-Zone face image is first divided into small regions where Local Binary Pattern (LBP) histograms are extracted and then concatenated into a single feature vector. This feature vector will further reduce the dimensionality scope by … …Journal of Computer Science, Vol. 10, Issue 12 · 27 Dec 2014 · 7,971 accessesView PDFCite
Research ArticleOpen accessIn the abstractFACIAL FEATURE EXTRACTION TECHNIQUES FOR FACE RECOGNITIONRahib H. AbiyevFace recognition is one of the biometric techniques used for identification of humans. The design of the face recognition system includes two basic steps. The first step is the extraction of the image's features and the second one is the classification of patterns. Feature extracting is a very important step in face recognition. The recognition rate of the system depends … …Journal of Computer Science, Vol. 10, Issue 12 · 23 Dec 2014 · 10,332 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Approach for Detection and Recognition of VehiclesK. S. Selvanayaki, Rm. SomaSundaramOn road vehicles have increased in numbers and monitoring them is a challenging task. In common areas of public crowd people and vehicles are common objects for monitoring. The proposed system aims at detecting number plate information indicating the possibility for security relevant issues. Existing system performs recognition mainly by using license plate alone. Addition of the features (logo, colour, … …Journal of Computer Science, Vol. 11, Issue 2 · 6 Sep 2014 · 7,436 accessesView PDFCite
Research ArticleOpen accessIn the abstractCOMPUTER AIDED SEGMENTATION OF BRAIN TISSUES USING SOFT COMPUTING TECHNIQUESD. Ramkumar, I. Jacob Raglend, K. BatriIn this study, an efficient computer aided classification of brain tissue in to Gray Matter (GM), White Matter (WM) and Cerebro-Spinal Fluid (CSF) is proposed. The proposed work consists of the following sub blocks like denosing, feature extraction and Classifier. This initial partition is performed by ANFIS after extracting the textural features like local binary pattern and histogram features. The … …American Journal of Applied Sciences, Vol. 11, Issue 6 · 17 Apr 2014 · 6,668 accessesView PDFCite
Research ArticleOpen accessIn the abstractFINGER KNUCKLE-PRINT IDENTIFICATION BASED ON LOCAL AND GLOBAL FEATURE EXTRACTION USING SDOSTN. B. Mahesh Kumar, K. PremalathaFinger knuckle-print biometric system has widely used in modern e-world. The region of interest is needed as the key for the feature extraction in a good biometric system. The symmetric discrete orthonormal stockwell transform provides the computational efficiency and multi-scale information of wavelet transforms, while providing texture features in terms of Fourier frequencies. It outperforms leading wavelet-based texture analysis methods. … …American Journal of Applied Sciences, Vol. 11, Issue 6 · 3 Apr 2014 · 6,931 accessesView PDFCite