基于改进树种算法的彩色图像多阈值分割

doi:10.11896/JsJkx.191000180

摘要/Abstract

摘要： 彩色图像多阈值分割在许多应用领域中都发挥着非常重要的作用,传统的多阈值分割算法存在随着阈值个数的增加分割时间急剧增长的问题。为了解决此问题,提出了一种基于改进树种算法(ITSA)的彩色图像多阈值分割方法,以最大类间方差(OTSU)为目标函数。为了提高基本树种算法的搜索速度和搜索精度,提出自适应搜索趋势常数来平衡树种算法的局部搜索和全局搜索能力,并利用五幅标准测试图像对算法的性能进行测试,将ITSA算法与树种算法(TSA)、粒子群优化算法(PSO)和差分进化(DE)算法的性能进行比较,实验结果表明,针对多阈值彩色图像分割问题,ITSA算法的性能优于TSA,PSO和DE算法,基于OTSU和ITSA的彩色图像多阈值分割算法是一种性能较好的算法。

关键词: 彩色图像, 彩色图像多阈值分割, 树种算法, 搜索趋势常数, 自适应

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

中图分类号:

TP319

彭浩, 和丽芳. 基于改进树种算法的彩色图像多阈值分割[J]. 计算机科学, 2020, 47(6A): 220-225. https://doi.org/10.11896/JsJkx.191000180

PENG Hao and HE Li-fang. Multi-threshold Segmentation for Color Image Based on Improved Tree-seed Algorithm[J]. Computer Science, 2020, 47(6A): 220-225. https://doi.org/10.11896/JsJkx.191000180

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