Paper Info
Title
Proximity Based Object Segmentation In Natural Color Images Using The Level Set Method
Abstract
Segmenting indicated objects from natural color images remains a challenging problem for researches of image processing. In this paper, a novel level set approach is presented, to address this issue. In this segmentation algorithm, a contour that lies inside a particular region of the concerned object is first initialized by a user. The level set model is then applied, to extract the object of arbitrary shape and size containing this initial region. Constrained on the position of the initial contour, our proposed framework combines two particular energy terms, namely local and global energy, in its energy functional, to control movement of the contour toward object boundaries. These energy terms are mainly based on graph partitioning active contour models and Bhattacharyya flow, respectively. Its flow describes dissimilarities, measuring correlative relationships between the region of interest and surroundings. The experimental results obtained from our image collection show that the suggested method yields accurate and good performance, or better than a number of segmentation algorithms, when applied to various natural images.
Year
DOI
Venue
2013
10.1587/transfun.E96.A.1744
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES
Keywords
Field
DocType
object-of-interest segmentation, Bhattacharyya flow, graph partitioning, level set, natural color image
Computer vision,Scale-space segmentation,Pattern recognition,Level set method,Segmentation,Level set,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Graph partition,Mathematics
Journal
Volume
Issue
ISSN
E96A
8
0916-8508
Citations 
PageRank 
References 
0
0.34
23
Authors
2
Name
Order
Citations
PageRank
Nguyen Tran Lan Anh161.47
Gueesang Lee220852.71