NDLI: Comparison between immersion-based and toboggan-based watershed image segmentation

Content Provider	IEEE Xplore Digital Library
Author	Yung-Chieh Lin Yu-Pao Tsai Yi-Ping Hung Zen-Chung Shih
Copyright Year	1992
Abstract	Watershed segmentation has recently become a popular tool for image segmentation. There are two approaches to implementing watershed segmentation: immersion approach and toboggan simulation. Conceptually, the immersion approach can be viewed as an approach that starts from low altitude to high altitude and the toboggan approach as an approach that starts from high altitude to low altitude. The former seemed to be more popular recently (e.g., Vincent and Soille), but the latter had its own supporters (e.g., Mortensen and Barrett). It was not clear whether the two approaches could lead to exactly the same segmentation result and which approach was more efficient. In this paper, we present two "order-invariant" algorithms for watershed segmentation, one based on the immersion approach and the other on the toboggan approach. By introducing a special RIDGE label to achieve the property of order-invariance, we find that the two conceptually opposite approaches can indeed obtain the same segmentation result. When running on a Pentium-III PC, both of our algorithms require only less than 1/30 s for a 256 /spl times/ 256 image and 1/5 s for a 512 /spl times/ 512 image, on average. What is more surprising is that the toboggan algorithm, which is less well known in the computer vision community, turns out to run faster than the immersion algorithm for almost all the test images we have used, especially when the image is large, say, 512 /spl times/ 512 or larger. This paper also gives some explanation as to why the toboggan algorithm can be more efficient in most cases.
Sponsorship	IEEE Signal Processing Society
Page Count	9
File Size	1101216
Starting Page	632
Ending Page	640
File Format	PDF
ISSN	10577149
Volume Number	15
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Information science Computer science Computer vision Testing Councils Electronic mail Inspection Biomedical imaging Image color analysis watershed image segmentation Immersion approach order-invariance toboggan approach
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Automatic watershed segmentation of randomly textured color images

Edge-Based Color Constancy

Four-Color Theorem and Level Set Methods for Watershed Segmentation

Adaptive image region-growing

Robust image segmentation against complex color distribution

A fast recursive shortest spanning tree for image segmentation and edge detection

A multivalued image wavelet representation based on multiscale fundamental forms

Segmentation of bones in magnetic resonance images of the wrist

Region growing: a new approach

Comparison between immersion-based and toboggan-based watershed image segmentation

Similar Documents

Automatic watershed segmentation of randomly textured color images

Edge-Based Color Constancy

Four-Color Theorem and Level Set Methods for Watershed Segmentation

Adaptive image region-growing

Robust image segmentation against complex color distribution

A fast recursive shortest spanning tree for image segmentation and edge detection

A multivalued image wavelet representation based on multiscale fundamental forms

Segmentation of bones in magnetic resonance images of the wrist

Region growing: a new approach

Comparison between immersion-based and toboggan-based watershed image segmentation