Coarse-to-Fine Particle Segmentation in Microscopic Urinary Images
This paper presents a coarse-to-fine particle segmentation strategy to extract particles from microscopic urinary images within two stages, coarse stage and fine stage. In coarse stage, to locate particles in a wide range of images including the low contrast, the unevenly illuminated, etc, we develop 4-direction variance mapping followed by an adaptive thresholding method. Within this stage, particles are well located, but their contours fail to exactly represent their shapes and clumped particle clusters are not divided. In fine stage, combined with Canny edges, we extract desired particle contours, then an effective local maxima search algorithm based on distance map successfully separates clumped particle clusters into individual particles. Our strategy is easy for implementation and its effectiveness is verified by large-scale experiments.
Indez Terms- 4-direction variance Canny method distance transform, local mazima search
Jiye Qian Bin Fang Chunyan Li Lin Chen
Department of Computer Science,Chongqing University,Chongqing 400030,P.R.China
国际会议
北京
英文
1-4
2009-06-11（万方平台首次上网日期，不代表论文的发表时间）