Image Thresholding Using TRIBES, a Parameter-Free Particle Swarm Optimization Algorithm

被引：3

作者：

Cooren, Yann ^{[1
]}

Nakib, Amir ^{[1
]}

Siarry, Patrick ^{[1
]}

机构：

[1] Univ Paris 12, LiSSi, EA 3956, F-94010 Creteil, France

来源：

LEARNING AND INTELLIGENT OPTIMIZATION | 2008年 / 5313卷

关键词：

D O I：

10.1007/978-3-540-92695-5_7

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Finding the optimal threshold(s) for an image with a multimodal histogram is described in classical literature as a problem of fitting a sum of Gaussians to the histogram. The fitting problem has been shown experimentally to be a nonlinear minimization problem with local minima. In this paper, we propose to reduce the complexity of the method, by using a parameter-free particle swarm optimization algorithm, called TRIBES which avoids the initialization problem. It was proved efficient to solve nonlinear and continuous optimization problems. This algorithm is used as a "black-box" system and does not need any fitting, thus inducing time gain.

引用

页码：81 / 94

页数：14

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