Blood Cells classification by Image color and intensity features clustering

R. A. Melnyk1 ramelnyk246 [at] gmail.com
A.O. Dubytskyi2 andrii.dubytskyi [at] gmail.com
  1. Doctor of Technical Science, Professor, Institute of Computer Science and Information Technologies, Lviv Polytechnic National University, Lviv, Ukraine; 2The 2nd year master, Institute of Computer Science and Information Technologies, Lviv Polytechnic National University, Lviv, Ukraine
Abstract 

A new approach for cells detection and classification on blood smear images is considered. Benefit of 4-connected over 8-connected component labeling for cell detection is shown. Color and intensity histogram clustering are proposed to extract common features for cells classification. A new approach for k-means initial centroids detection proposed. The algorithms effectiveness was tested
and estimated for some blood smear images. The algorithm examples, figures and result table to illustrate the approach are presented

References 

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