A Compressed Brain Image Classification System Enhance with Multi Image Particle Swarm Optimization Segmentation Dr. Palanivelu L M*, Dr. Manavalasundaram V K** *Professor, Velalar College of Engineering and Technology, India **Associate Professor, Velalar College of Engineering and Technology, India Online published on 14 October, 2016. Abstract Compression methods reduce the file size of images through the reduction of data required for representing images that are similar to the original by way or removing redundancies. Smart cards possess embedded integrated circuits comprising memory as well as micro-processing components. Images regarding the card holder's medical history, fingerprints, palm print and so on are stored. Multi-application smart cards are rapidly becoming the replacement for traditional cards like driving license, identity cards, credit cards and so on as a single card. Hence, the quantity of information in storage within one card is great, which requires techniques for compressing the data so that the card may be effectively used. Images are segmented through extension of active contour models for finding image contours through the suggested Multi Image Particle Swarm Optimization (MI-PSO). Top Keywords Brain image classification, Compression, Smart cards, Multi Image Particle Swarm Optimization (MI-PSO), Active Contour, Embedded Zero trees of Wavelets (EZW). Top |