Multi-level Thresholding Selection by using the Honey Bee Mating Optimization

摘要：

Image thresholding is an important technique for image processing and pattern recognition. In this paper, a new multilevel image thresholding algorithm based on the technology of the honey bee mating optimization (HBMO) is proposed. Three different methods such as the particle swarm optimization (PSO), the hybrid cooperative-comprehensive learning based PSO algorithm (HCOCLPSO) and the Fast Otsus method are also implemented for comparison with the results of the proposed method. The experimental results reveal two important interested results for other three image thresholding methods. One is that the results of PSO and Fast Ostus method are unstable that extraordinary segmentations are generated. Another is that the results of HCOCLPSO are superior to original PSO method, but it still slower than ones of HBMO and it had similar segmentation results with the ones of the honey bee mating optimization.

关键词： Image thresholding particle swarm optimization honey bee mating optimization hybrid cooperative-comprehensive learning based PSO algorithm Ostus method

作者: Ren-Jean Liou Ming-Huwi Horng Ting-Wei Jiang

作者单位: Department of Computer Science and Information Engineering, National Pingtung Institute of Commerce, 51 Min Sheng E. Road, Pingtung, Taiwan, ROC

会议类型: 国际会议

会议名称: 2009 Ninth International Conference on Hybrid Intelligent Systems(第九届混合智能系统国际会议 HIS 2009)

会议地点: 沈阳

会议语种:英文

页码: 1-5

在线出版日期: 2009-08-12（万方平台首次上网日期，不代表论文的发表时间）