Multimoving Human Sperm Tracking Using CGM-CS Approach and Comparative Analysis for Proper Diagnosis in Infertility

In this paper, we introduced an algorithm for tracking and detecting multi moving human sperm using Course Grained Multi Threading Cam Shift (CGM-CS) approach in a microscopic human sperm moving video. This method is fully based on adaptive Cam Shift algorithm using color model. This algorithm is design to track and detect the sperms by using multi threading concept. The multi threading concept is compared continuously to its mean value in the successive frame in the appropriate video. The result obtained by the proposed method is also compared with the Maximum Intensity Region (MIR) algorithm, Lukas-Kanade (LK) algorithm and Kernel Based (KB) algorithm. Experimental results demonstrate that the CGM-CS algorithm is capable of tracking the sperm with high detection rate with minimum time taken as compared to existing approaches.