Image Segmentation Method Using Thresholds Automatically Determined from Picture Contents.

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Bibliographic Details
Title:	Image Segmentation Method Using Thresholds Automatically Determined from Picture Contents.
Authors:	Yuan Been Chen^1,2 ybchen@ctu.edu.tw, Chen, Oscal T.-C.¹
Source:	EURASIP Journal on Image & Video Processing. 2009, Vol. 2009, p1-15. 15p. 5 Black and White Photographs, 6 Diagrams, 3 Charts, 5 Graphs.
Subjects:	Automation, Selection theorems, Threshold logic, Digital signal processing, Markov random fields
Abstract:	Image segmentation has become an indispensable task in many image and video applications. This work develops an image segmentation method based on the modified edge-following scheme where different thresholds are automatically determined according to areas with varied contents in a picture, thus yielding suitable segmentation results in different areas. First, the iterative threshold selection technique is modified to calculate the initial-point threshold of the whole image or a particular block. Second, the quad-tree decomposition that starts from the whole image employs gray-level gradient characteristics of the currently-processed block to decide further decomposition or not. After the quad-tree decomposition, the initial-point threshold in each decomposed block is adopted to determine initial points. Additionally, the contour threshold is determined based on the histogram of gradients in each decomposed block. Particularly, contour thresholds could eliminate inappropriate contours to increase the accuracy of the search and minimize the required searching time. Finally, the edge-following method is modified and then conducted based on initial points and contour thresholds to find contours precisely and rapidly. By using the Berkeley segmentation data set with realistic images, the proposed method is demonstrated to take the least computational time for achieving fairly good segmentation performance in various image types. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Image segmentation has become an indispensable task in many image and video applications. This work develops an image segmentation method based on the modified edge-following scheme where different thresholds are automatically determined according to areas with varied contents in a picture, thus yielding suitable segmentation results in different areas. First, the iterative threshold selection technique is modified to calculate the initial-point threshold of the whole image or a particular block. Second, the quad-tree decomposition that starts from the whole image employs gray-level gradient characteristics of the currently-processed block to decide further decomposition or not. After the quad-tree decomposition, the initial-point threshold in each decomposed block is adopted to determine initial points. Additionally, the contour threshold is determined based on the histogram of gradients in each decomposed block. Particularly, contour thresholds could eliminate inappropriate contours to increase the accuracy of the search and minimize the required searching time. Finally, the edge-following method is modified and then conducted based on initial points and contour thresholds to find contours precisely and rapidly. By using the Berkeley segmentation data set with realistic images, the proposed method is demonstrated to take the least computational time for achieving fairly good segmentation performance in various image types. [ABSTRACT FROM AUTHOR]
ISSN:	16875176
DOI:	10.1155/2009/140492