摘要
目的针对目标与背景对象的色彩值比较接近的RGB图像中,目标对象难以有效分割的问题,探索一种基于mean shift的RGB多通道图像的分割方法。方法根据RGB图像的3个通道对颜色的敏感性差异,运用均值偏移算法对RGB图像的3个通道分层聚类,再引入可靠性因子,分别对3个单通道的各聚类像素进行可靠性计算,并保留可靠性高的像素作为分割结果,最后采用逻辑"或"运算融合单通道的分割结果,得到最终分割图像。结果与一般分割算法相比,该方法的分割效果好,误分率低,改善了图像的分割质量。结论该算法具有很好的推广性,能够应用于彩色印品缺陷检测、彩色包装图像检测中。
To overcome low efficiency of segmentation for multi-channel images when the color values of target region is similar to that of the background object, a multi-channel mean shift segmentation algorithm was proposed. The algorithm was achieved through mean shift algorithm for R, G, B three-channel hierarchical clustering in terms of the different sensitivity of R,G,B image to color. A reliability factor was introduced for separately evaluating the reliability of each pixel belonging to a cluster. Then the pixels of high reliability score were retained as the final segmentation results.Finally, a logical ＂OR＂ operation was used to fuse each single channel segmentation result to obtain the final result of image segmentation. The experimental results showed that compared to common segmentation algorithms, this algorithm could improve the segmentation results and improve the quality of the image segmentation. With the advantages of accuracy, the proposed algorithm was suitable for computer vision in defect detection of color printing and packaging image detection.
出处
《包装工程》
CAS
CSCD
北大核心
2015年第21期89-94,共6页
Packaging Engineering
基金
国家自然科学基金(61305016)
江南大学自主科研计划青年基金(JUSRP1059)
关键词
多通道
均值偏移
分割
可靠性
multi-channel
mean shift
segmentation
reliability
作者简介
吴静静（1982-），女，安徽滁州人，江南大学讲师，主要研究方向为信息融合与目标跟踪。
