Parallel Computation of the Region-Based Level Set Method for Boundary Detection of Moving Objects | Zendy

Xianfeng Fei | Zendy; Yasunobu Igarashi | Zendy; M. Shinkai | Zendy; Masatoshi Ishikawa | Zendy; Koichi Hashimoto | Zendy

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Parallel Computation of the Region-Based Level Set Method for Boundary Detection of Moving Objects

Author(s) -

Xianfeng Fei,

Yasunobu Igarashi,

M. Shinkai,

Masatoshi Ishikawa,

Koichi Hashimoto

Publication year - 2009

Publication title -

journal of robotics and mechatronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.257

H-Index - 19

eISSN - 1883-8049

pISSN - 0915-3942

DOI - 10.20965/jrm.2009.p0698

Subject(s) - computation , computer vision , boundary (topology) , artificial intelligence , computer science , discretization , contrast (vision) , image (mathematics) , set (abstract data type) , image processing , robot , algorithm , mathematics , mathematical analysis , programming language

We formulate a parallel, region-based level set model to speed up accurate boundary detection of moving objects in low-contrast images, applying parallelization and discretization to a Chan-Vese (CV) model. We implement the model in a column parallel vision (CPV) system that is one of parallel image processing systems we developed for robot vision. Using a microscopic image of moving paramecia as a sample of a low-contrast image, our model detects moving paramecia boundaries within 2 ms per image. Comparisons of our model to a CV model using the CPV system and a nonparallel PC, we found that our model cuts calculation time for a CV model while obtaining accuracy similar to the CV model in boundary detection of moving objects.

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