A semen analysis evaluates certain characteristics of a male's semen and the sperm contained in the semen. The chance of pregnancy will be reduced, if more than 50 percent of a man's sperm lack movement. Assessing the ability of sperm to move forward through the cervix into the fallopian tubes is a widely used measure of male infertility. Since the examination is done by a person through a microscope, a fairly simple system is used for classifying the spermatozoa. This paper proposes a technique to evaluate the motility of human spermatozoon which includes moving object detection, tracking and behavioral analysis. The objective is to measure the speed and quality of movement by tracking video clips of individual sperm cells. The approach chosen was frame differencing on consecutive frames, which identifies moving objects from the portion of a video frame that differs significantly from the previous frame. This method has less computation complexity, high recognition rate and a faster processing speed.

An important parameter assessed during the semen analysis is the overall morphology, or shape of the sperm. Currently, the morphological analysis of sperm is done manually and is based on visual observation of at least 200 spermatozoa in a microscope followed by a classification stage based on strict criteria. But this method has led to incorrect results due to various factors such as different staining procedures, experience of technicians and human errors. So this paper focuses on morphological classification of spermatozoon either as normal or abnormal using Matlab. The first stage is the image preprocessing stage which involves the conversion of RGB image to a gray scale image and then image noises are removed using median filter. The second stage is the detection and extraction of individual spermatozoon which involves the extraction of sperm objects from images using sobel edge detection algorithm. The third stage segments the spermatozoon into various region of interest such as sperm head, midpiece and tail. The fourth stage involves the statistical measurement of spermatozoon which classifies Spermatozoa as normal or abnormal.

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