A Novel Approach for Segmenting WBCs in Smartphones Using Color-Based Segmentation

Abstract

White Blood cell (WBC) is one of the most important blood cells in our body. This cell controls human immune system. The high count and low count of WBC reflect different kinds of disease in our body. Therefore, WBC counting is very important to diagnose several diseases. The pathological process of WBC counting is very time consuming, tedious, and prone to human error. Thus, an automated WBC counting system is highly needed to obtain accurate results. WBC segmentation is very important to make an automated WBC counting system. In our work, we are proposing a color-based WBC segmentation algorithm, which segments WBCs from microscopic images of peripheral blood smear in smart phones. Experimental results show the system to be robust and effective for WBC segmentation. The proposed technique will be very helpful to make an automated WBC counting system and could potentially overcome the errors arising due to manual inspection.