Blood Group Classification System Based on Image Processing Techniques

The present paper proposes a novel system that automatically classifies the eight different blood groups according to ABO and Rh group systems. proposed is developed by applying MATLAB’s image processing techniques on sample images. These images are acquired from laboratory using slide test. It utilizes mean filter for removing noise In addition, Contrast Limited Adaptive Histogram Equalization (CLAHE) used enhancing characteristics analysis. also automated threshold strategy (Otsu’s approach) obtaining samples binary Since, adding three antigens (A, B, D) works clumping or not, this, in turn, variation number of objects holes groups’ samples. Therefore, “Bwboundaries” Matlab function applied first time count classification. database consists 600 collected laboratories. suggested has many advantages such as simplicity, speeding up time, reducing human interference errors, decreasing risk transfusion reactions, high accuracy, even remote places. As well, it can be lab technician any user who doesn’t have previous knowledge detection technique. addition this assist several applications premarital tests, well paternity tests.