COUNTING OF WBCs AND RBCs FROM BLOOD IMAGES USING GRAY THRESHOLDING

Fast and cost-effective production of blood cell count reports are of paramount importance in the healthcare industry. In the market there are various systems for the automatic quantification of blood cells that allow counting the number of different types of cells within the blood smear. 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. The main goal of this work is the analysis and processing of a microscopic image, in order to provide an automated procedure to support the medical activity. In this project, the WBCs and RBCs are counted by using the gray thresholding algorithm computing with the manual method. This means that, the number of WBCs and RBCs are counted from the five blood images. This procedure is done because in manual counting method, the cells are counted from the five squares. After counting the number of WBCs and RBCs from these five squares, these counts are then applied to the formula to count the normalized count. So, this same procedure is done to calculate the number of WBCs and RBCs in this project. The use of image processing help in improving the image quality and analysis approach from different application. It improves the effectiveness of the analysis in term of accuracy, time consuming and so on.