Automated Detection and Counting of Red Blood Cell using Image Processing Techniques

The major issue in clinical laboratory is to produce a precise result for every test especially in the area of Red Blood Cell (RBC) count. Red blood cell (RBC) count in a blood test used to evaluate the overall health and diagnose a wide range of disorders, including anaemia, infection and malaria etc. This blood cell count infers about the disorders against normal healthy blood cell count. The traditional method of manual counting under a microscope yields inaccurate results and put an intolerable amount of stress to medical laboratory technicians. Due to high vulnerability in human error and large time consumption, better and more effective image processing software is needed. As a solution to this problem, this project proposes an image processing technique for counting the number of blood cells.. This paper introduces a cost effective automatic RBC counting method using image analysis technique and specifically aims at improving the results using Hough circle detection. Removing the unnecessary circles created during the Hough Circle Detection will yield more accurate results