Applications of intelligent image processing

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The project involves investigations on the applications of pattern recognition and machine learning techniques to problems in image retrieval, image scene analysis and biometrics. The use of machine learning techniques in computer vision applications is relatively new except for applications to face recognition. We propose to investigate an efficient classification and retrieval from large image databases, and also its applications to dermatological images to provide a diagnostic tool to dermatologists and oncologists, problems in biometrics involving iris recognition. We also investigate problems in mobile computing involving biometrics-based identification and verification. We propose an approach to image retrieval by classifying images into different semantic categories and using probabilistic similarity measures. With the growing availability of information technology and digital imaging revolution in the medical domain, large collections of digital dermatological images are regularly being generated by clinics for image-guided diagnosis. We propose an intelligent content-based image retrieval approach of digital medical images in the domain of dermatology. It may be used as an efficient training tool for medical students, residents and researchers to search efficiently large collection of disease-related illustrations by their visual attributes. As an application of machine learning to biometrics, we propose an iris recognition system as a biometrically based technology for person identification using support vector machines. The project is partly interdisciplinary and would provide interactions with the industry and medical doctors. The project would train three  graduate students and a Postdoctoral Fellow.