Semi-automatic image segmentation: a bimodal thresholding approach

Update Item Information
Publication Type Journal Article
School or College College of Engineering
Department Computing, School of
Creator Johnson, Christopher R.
Other Author Shen, Han-Wei
Title Semi-automatic image segmentation: a bimodal thresholding approach
Date 1994
Description We have developed a semi-automatic image segmentation tool which combines conventional manual segmentation utilities with a novel automatic image segmentation algorithm. Manual segmentation is achieved by dropping control points and fitting cubic splines to these points. Automatic segmentation is achieved by bimodally thresholding local windows of the target image and contour following. By combining these two segmentation methods, a user can obtain accurate boundary descriptions with much less effort.
Type Text
Publisher University of Utah
First Page 94
Last Page 19
Subject Image segmentation; Segmentation algorithms; Bimodal thresholding
Language eng
Bibliographic Citation Shen, H.-W., & Johnson, C. R. (1994). Semi-automatic image segmentation: a bimodal thresholding approach. UUCS-94-019.
Series University of Utah Computer Science Technical Report
Relation is Part of ARPANET
Rights Management ©University of Utah
Format Medium application/pdf
Format Extent 2,779,037 bytes
Identifier ir-main,16308
ARK ark:/87278/s6kh15zz
Setname ir_uspace
ID 707111
Reference URL https://collections.lib.utah.edu/ark:/87278/s6kh15zz
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