Overlapping White Blood Cells Detection Based on Watershed Transform and Circle Fitting

Abstract

White blood cell (WBC) count and segmentation is considered to be important step to diagnose diseases like leukemia, malaria etc. Automatic analysis of blood smear images will help hematologists to detect WBCs efficiently and effectively as compared to manual analysis which is quite time consuming. Therefore, an automatic white blood cells detection technique for complex blood smear images is proposed. The proposed scheme uses segmentation and edge map extraction for the separation of overlapped WBCs and further parametric circle approximation is used which is capable of detecting both separated and overlapped white blood cells. Simulation results compared with the existing techniques verify the accuracy and robustness of the proposed scheme.