Paper Info
Title
Comparative Improvement of Image Segmentation Performance with Graph Based Method over Watershed Transform Image Segmentation
Abstract
Watershed transformation based segmentation which is a segmentation based on marker is a special tool used in image processing. Color based image segmentation has been considered an important area since its inception, due to its wide variety of applications in the field of weather forecasting to medical image analysis etc. Due to this color image segmentation is widely researched. This paper analyses the performance of two main algorithms used for image segmentation namely Watershed algorithm and graph based image segmentation. The performance analysis proves that graph based segmentation is better than watershed algorithm in cases where noise is maximum and also the over segmentation problem is removed. Color segmentation with graph based image segmentation gives satisfactory results unlike watershed algorithm.
Year
DOI
Venue
2014
10.1007/978-3-319-04483-5_33
ICDCIT
Keywords
Field
DocType
Watershed transformation, Graph based image segmentation, Marker, Over segmentation
Computer vision,Scale-space segmentation,Pattern recognition,Segmentation,Image texture,Computer science,Segmentation-based object categorization,Image segmentation,Region growing,Artificial intelligence,Connected-component labeling,Minimum spanning tree-based segmentation
Conference
Volume
ISSN
Citations 
8337
0302-9743
0
PageRank 
References 
Authors
0.34
6
2
Name
Order
Citations
PageRank
Suman Deb100.34
Subarna Sinha219820.80