Paper Info
Title
A Novel Approach to Extract Salient Regions by Segmenting Color Images with Hybrid Algorithm
Abstract
Due to the advent of computer technology image-processing techniques have become increasingly important in a wide variety of applications. This is particularly true for medical imaging such as Computer Tomography (CT), magnetic resonance image (MRI), and nuclear medicine, which can be used to assist doctors in diagnosis, treatment, and research. In this paper, hybrid algorithm for segmentation of color images is presented. The segments in images are found automatically based on adaptive multilevel threshold approach and FCM algorithm. Neural network with multisigmoid function tries to label the objects with its original color even after segmentation. One of the advantages of this system is that it does not require a past knowledge about the number of objects in the image. This Fuzzy-Neuro system is tested on Berkley standard image database and also attempts have been made to compare the performance of the proposed algorithm with other currently available algorithms. From experimental results, the performance of the proposed technique is found out to yields better extraction of salient regions with high resolution as nearly same as the original image and better than the existing techniques. It can be used as a primary tool to segment unknown color images. Experimental results show that its performance is robust to different types of color images.
Year
DOI
Venue
2010
10.1109/ICETET.2010.25
ICETET
Keywords
Field
DocType
magnetic resonance image,neural network,segmenting color images,nuclear medicine,color image segmentation,hybrid algorithm,image processing,extract salient regions,adaptive multilevel threshold,image segmentation,color image,berkley standard image database,color images,salient regions,original color,original image,available algorithm,computer technology,object extraction,computer tomography,segment unknown color image,fcm algorithm,multisigmoid function,medical imaging,fuzzy-neuro system,novel approach,fuzzy neural nets,image colour analysis,artificial neural networks,high resolution,pixel,color,computed tomography,feature extraction
Computer vision,Hybrid algorithm,Pattern recognition,Segmentation,Computer science,Medical imaging,Feature extraction,Image segmentation,Artificial intelligence,Pixel,Computer technology,Color quantization
Conference
ISSN
ISBN
Citations 
2157-0477 E-ISBN : 978-0-7695-4246-1
978-0-7695-4246-1
0
PageRank 
References 
Authors
0.34
6
2
Name
Order
Citations
PageRank
Prasanna Palsodkar1303.38
Preeti R. Bajaj28114.51