Blood cells classification by image color and intensity features clustering

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.