DocumentCode
2612127
Title
A Curve Fitting Based Image Segmentation Method
Author
Shen, Wei ; Wu, Lifang ; Tu, Ling
Author_Institution
Sch. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China
fYear
2009
fDate
17-20 April 2009
Firstpage
71
Lastpage
75
Abstract
In this paper a method is proposed to segment the board in Snooker games automatically. The algorithm involves the following steps: first, separable second derivative of Guassian steerable filters, which are linear combination of basis filters and can implement filtering with variant direction, are used to extract the edges in both horizontal and vertical directions. The input image f(x,y) is convolved with every base filter, then weighted the summation of outputs of all the base filter, the resulted image g(x,y) can be obtained. Second, the candidate board regions are extracted by color segmentation. After image dilation, which can make the points which are around the background merge to the objects, it is helpful that extracting the edge pixels exactly. And next, the candidate edge pixels are extracted by both the peak value of edge pixel and the candidate board region. Finally, the true edge pixels can be obtained by curve fitting, and the board is segmented by the results of curve fitting.
Keywords
Gaussian processes; curve fitting; edge detection; filtering theory; image colour analysis; image segmentation; Guassian steerable filters; basis filters linear combination; candidate board regions; color segmentation; curve fitting; edge extraction; edge pixel; image dilation; image segmentation method; snooker games; Computer science; Computer vision; Control engineering; Curve fitting; Filtering; Games; Image segmentation; Nonlinear filters; Pixel; Springs; Guassian steerable filters; basis filters; color segmentation; curve fitting; the candidate board regions;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology - Spring Conference, 2009. IACSITSC '09. International Association of
Conference_Location
Singapore
Print_ISBN
978-0-7695-3653-8
Type
conf
DOI
10.1109/IACSIT-SC.2009.86
Filename
5169312
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