Design And Implementation Of The Multiple Tracking Algorithm For Sperm Analysis

Multiple Object detection and tracking related to computer image processing, pattern recognition, artificial intelligence and other areas, is widely applied in many aspects such as military, industrial, life, and so on.The computer-aided sperm analysis (CASA) is important application of the image analysis technique in the biological and medical area. It provides a rapid and automated assessment of the parameters of sperm motion, together with improved standardization and quality control.This paper summarizes and classifies two major components of a visual tracking system; target representation and localization and filtering and data association. Target representation and localization is mostly a bottom-up process. Typically the computational complexity for these algorithms is low. Filtering and data association is mostly a top-down process, which involves incorporating prior information about the scene or object, dealing with object dynamics, and evaluation of different hypotheses. The computational complexity for these algorithms is usually much higher.Examines pros and cons of tracking system and based on the sperm movement characteristics, Otsu and feature matching key technologies, the paper presents an efficient and low-cost method for automatically detecting and tracking the moving object from sperm image sequences. This tracking algorithm was used after the background and extra particles were successfully removed through a two-step enhancement algorithm. The algorithm improves the effectiveness and accuracy of sperm detecting.