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Comparative Analysis of White Blood Cell by Different Segmentation Methods Using Knowledge Based Learning

Rajwinder Kaur, Harpreet Kaur

Blood cells extraction and detection is very much important for all human beings, because there are WBCs, RBCs, Platelets in our blood, White blood cell count gives the vital information that help diagnosis many of the patient’s sickness. This work presents a new adaptive approach of extracting and detecting the WBCs in blood sample microscopic images. In the research work the author used two different approaches one is k-means clustering algorithm and second is Hough transform. Author also used to study the different parameters like radius of the cells, calculate the time for getting the output from te sample input image.