A unified granular hybrid soft computing framework for vision engineering
by Mokhtar Beldjehem
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 3, No. 3/4, 2011

Abstract: We propose a novel unifying framework for building a novel granular modular architecture for a machine visual system that accommodates a large spectrum of potential vision problems. Thus removing the ad hoc nature of present solutions and providing the basis for new generation of machine visual systems. Such a framework works by integrating some useful concepts from the human vision processes and adding some interesting granular functionalities of human cognition and it advocates further hybridisation of non-linear digital filters and soft computing in implementing such machine intelligent visual systems. Our focus herein will be on the low level and mid-level stages of such a framework. The goal is to build an automatic system that can be used for degraded multi-modal image processing, including x-rays, MRI, Sonar, etc. for diagnosis, recognition, registration and information fusion purposes. For illustration purposes, an investigation concerning its application to a real world problem is also provided. We are interested by an application to automatic detection and classification of patients' spines affected by idiopathic scoliosis from X-rays images.

Online publication date: Thu, 26-Mar-2015

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