一种基于粒子群优化算法的快速圆检测方法

为了实现以较少的内存资源,快速而准确地进行圆 检测, 提出一种基于粒子群的快速圆检测方法。方法中,以每个粒子作为一个候选圆,采用优化策 略,以粒子 运动、融合更新等操作完成圆的检测。优化策略包括提出使用一种图像分块的策略限 定圆检测的感兴趣区 域,各个图像块的大小由各个块内粒子的生成结果决定,以起到抑制部分噪声的作用。为减 少生成无用粒子的概 率,提高检测效率,提出融入图像金字塔的思想,并以循证的方法对粒子的有效性加以验证 。实验结果表明,本文 方法对于检测手绘的、嵌套的、不完整的或包含有大量噪声的圆,均能起到较好的检测效果 ；能 够在较短的时间内排除众多干扰,准确地进行圆的检测,具有检测速度快、内存消耗小和适 用范围广等优点。

A fast circle detection method based on particle swarm optimization algorithm

In order to detect circles quickly and accurately with less memory,we present a fast circle detection method based on particle sw arm optimization (PSO) in this paper.Under some optimization strategies with each particle as a candidate circle,the appro ach uses some operations for updating the particles to complete the circle detec tion.The optimization strategies in this approach use an image blocking to limit the circle detection area of interest,and the size of each image block depende on the result of generating particles.In order to redu ce the generation probability of those useless particles and improve the efficiency of detection,we use an image pyrami d and the evidence-based method to verify the effectiveness of particles.Experi mental results validate that the proposed method is suitable for detecting circles which are regular,hand-drawn,nested,incomplete or containi ng a lot of noise.The proposed method can exclude much interference in a short time,and accurately detect circles.It exhibits small memory consumption,fast running speed and wide application range.