Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (6A): 220-225.doi: 10.11896/JsJkx.191000180

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Multi-threshold Segmentation for Color Image Based on Improved Tree-seed Algorithm

PENG Hao1 and HE Li-fang2   

  1. 1 Pan-Asia Businesss School,Yunnan Normal University,Kunming 650092,China
    2 City College,Kunming University of Science and Technology,Kunming 650093,China
  • Published:2020-07-07
  • About author:PENG Hao, born in 1981, Ph.D.His main research interests include intelligence optimization algorithm and information management.
    HE Li-fang, born in 1981, Ph.D.Her main research interests include image segmentation, artificial intelligence and intelligence optimization algorithm.

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Abstract: Multi-threshold segmentation for color image plays a very important role in various applications.Traditional multi-threshold segmentation algorithm has the problem that the segmentation time increases sharply with the increase of the number of threshold.To overcome the problem,this paper proposes a multi-threshold segmentation algorithm for color image based on improved tree-seed algorithm (ITSA),and takes OTSU as obJective functions.In order to improve the search speed and accuracy of the basic tree-seed algorithm (TSA),a new self- adaptive search tendency constant is presented to balance the ability of local search and global search.The performance of ITSA is tested on five basic test images and compared with TSA,particle swarm optimization (PSO) and differential evolution (DE) algorithm.Experimental results show that ITSA is better than TSA,PSO and DE algorithm on color image multi-threshold segmentation.The OTSU and ITSA based method is a good algorithm for colorima-ge multi-threshold segmentation.

Key words: Color image, Color image multi-threshold segmentation, Search tendency constant, Self-adaption, Tree-seed algorithm

CLC Number: 

  • TP319
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