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

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Advanced Intelligence Paradigms (IJAIP):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com