.png){kind=icon}
返回
Non-supervised image segmentation based on multiobjective optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patrec.2007.09.008.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The segmentation process based on the optimization of one criterion only does not work well for a lot of images. In many cases, even when equipped with the optimal value of the threshold of its single criterion, the segmentation program does not produce a satisfactory result. In this paper, we propose to use the multiobjective optimization approach to find the optimal thresholds of two criteria: the within-class criterion and the overall probability of error criterion. In addition we develop a new variant of Simulated Annealing adapted to continuous problems to solve the histogram Gaussian curve fitting problem. Six examples of test images are presented to compare the efficiency of our segmentation method, called Combination of Segmentation Objectives (CSO), based on the multiobjective optimization approach, with that of two classical competing methods: Otsu method and Gaussian curve fitting method. From the viewpoints of visualization, object size and image contrast, our experimental results show that the segmentation method based on multiobjective optimization performs better than the Otsu method and the method based on Gaussian curve fitting. (c) 2007 Elsevier B.V. All rights reserved.
Keyword:
image segmentation
Otsu method
Gaussian curve fitting
multiobjective optimization
simulated annealing
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.3
论文数:
7.9K
被引数:
1.6W
机构
引用论文
.png){kind=icon}
Image segmentation by three-level thresholding based on maximum fuzzy entropy and genetic algorithm
PREAI
分享收藏分享收藏
Electrocatalysis at graphite and carbon nanotube modified electrodes: edge-plane sites and tube ends are the reactive sites石墨和碳纳米管修饰电极上的电催化: 边缘平面位和管端是反应位点
PREAI
分享收藏
查看更多内容