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A Novel Plant Root Foraging Algorithm for Image Segmentation Problems
Author(s) -
Lianbo Ma,
Kunyuan Hu,
Yunlong Zhu,
Hanning Chen,
Maowei He
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/471209
Subject(s) - foraging , benchmark (surveying) , segmentation , heuristic , computer science , algorithm , root (linguistics) , image segmentation , artificial intelligence , mathematical optimization , pattern recognition (psychology) , mathematics , ecology , geography , biology , linguistics , philosophy , geodesy
This paper presents a new type of biologically-inspired global optimization methodology for image segmentation based on plant root foraging behavior, namely, artificial root foraging algorithm (ARFO). The essential motive of ARFO is to imitate the significant characteristics of plant root foraging behavior including branching, regrowing, and tropisms for constructing a heuristic algorithm for multidimensional and multimodal problems. A mathematical model is firstly designed to abstract various plant root foraging patterns. Then, the basic process of ARFO algorithm derived in the model is described in details. When tested against ten benchmark functions, ARFO shows the superiority to other state-of-the-art algorithms on several benchmark functions. Further, we employed the ARFO algorithm to deal with multilevel threshold image segmentation problem. Experimental results of the new algorithm on a variety of images demonstrated the suitability of the proposed method for solving such problem.

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