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White blood cells (WBCs) count and segmentation is considered to be an 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 with the manual analysis which is quite time consuming. Therefore, an automatic white blood cells detection technique for complex blood smear images has been proposed. The proposed scheme uses segmentation and edge map extraction for the separation of overlapped WBCs further, parametric circle approximation has been 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.

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