Project Login
Registration No:
Password:
MAIL ALERTS SMS ALERTS
 
     
   
     

ROBUST IMAGE SEGMENTATION ALGORITHM USING FUZZY CLUSTERING BASED ON KERNEL-INDUCED DISTANCE MEASURE

Platform : DSP

IEEE Projects Years : 2000

This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on Issue Date: Aug 2000 AIM: To verify the Image segmentation algorithm for textured images using Fuzzy clustering based on kernel-induced distance measure ABSTRACT We propose a novel approach for solving the perceptual grouping problem in vision. Rather than focusing on local features and their consistencies in the image data, our approach aims at extracting the global impression of an image. We treat image segmentation as a graph partitioning problem and propose a novel global criterion, the normalized cut, for segmenting the graph. The normalized cut criterion measures both the total dissimilarity between the different groups as well as the total similarity within the groups. We show that an efficient computational technique based on a generalized eigenvalue problem can be used to optimize this criterion. We applied this approach to segmenting static images, as well as motion sequences, and found the results to be very encouraging LEARNING OBJECTIVE: To verify the textured image segmentation techniques. INPUT: Textured Image with fault and without fault OUTPUT : Detected Image with fault APPLICATIONS: Image processing

NOW GET PROJECTS ! GET TRAINED ! GET PLACED !

IEEE, NON-IEEE, REAL TIME LIVE ACADEMIC PROJECTS,

PROJECTS WITH COMPLETE COURSES,SOFT SKILLS & PLACEMENTS

ALLOVER INDIA & WORLD WIDE,

HOSTEL FACILITY AVAILABLE FOR GIRLS & BOYS SEPARATELY,

CALL: 08985129129 ,  E-Mail Id: support@ascentit.in

REGISTER FOR PROJECTS NOW ! GET DISCOUNT
   
1