Image segmentation is the pre-step of multi-target tracing in Computer Assisted Sperm Motion Analysis System (CASMA). As a special sperm-tracing problem, a fast, automatic, unsupervised segmentation algorithm is required. In this paper, we utilize four segmentation algorithms to segment three different kinds of sperm images sampled from our actual system. By making an overall comparison between them, a conclusion is reached that the Otsu's maximum between-class variance algorithm is the most suitable for the special sperm microscopic image segmentation and this segmentation algorithm has been successfully applied to our developed system.
"Segmentation methods of spermatoza microscopic image", Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); doi: 10.1117/12.477193; https://doi.org/10.1117/12.477193