Classification of White Blood Cells Using Image Processing Techniques – Preliminary Results
; Marques, A. M.
Classification of White Blood Cells Using Image Processing Techniques – Preliminary Results, Proc Portuguese Conf. on Pattern Recognition - RecPad, Porto, Portugal, Vol. , pp. - , October, 2019.
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This paper describes an approach that successfully classifies five types of white blood cells based on image processing algorithms and a Support Vector Machine classifier. The images were taken from peripheral blood of healthy subjects. The cells, nucleus, and cytoplasm are segmented through thresholding techniques and mathematical morphology. Then, a set of textural and morphological features are extracted from the segmented regions. System evaluation is performed using 4-fold stratified cross-validation. An overall accuracy of 90.5 ± 1.6% was achieved.