一种基于颜色聚类和种子填充的目标识别算法

摘要

针对类人足球机器人目标识别易受光照强度变化影响的问题,改进了常规的扫描线种子填充算法,提出了一种基于颜色聚类分割和种子填充的目标识别算法.该算法采用HSI颜色模型,依据亮度和饱和度信息对图像粗分割,基于阈值将彩色区域和灰色区域分离,同时将灰色区域二值化;基于色调直方图聚类分析对彩色区域的像素进行了归类,通过改进扫描线种子填充算法实现了色块的最简扩充和特征提取,使颜色分割和特征提取同步进行,解决了目标物体的快速、精确识别.实验结果表明,该算法抗干扰能力强,分割精度高,能满足实时性要求,具有一定的实用价值.%Aiming at the problem that the target recognition is impressionable of illumination variation in humanoid robot soccer, conventional seed filling algorithm was improved, and a target recognition algorithm based on color clustering segmentation and seed filling was proposed.The HSI color space was employed in the target recognition algorithm.Based on intensity and saturation, the image was separated to two parts, which were color area and gray area, by the method of thresholding.Then the color area was sorted to different color classes by clustering method based on the hue histogram.Meanwhile, the improved seed filling algorithm was used to minimal expand the color regions and extract regions' features.In this way, fast and precise target recognition was implemented.Experimental results show that the proposed method is higher free of disturbance, precise in segmentation and satisfies the real-time.It has certain practical value.