Melnyk, R. A.Dubytskyi, A. O.2018-03-012018-03-012015Melnyk R. A. Blood cells classification by image color and intensity features clustering / R. A. Melnyk, A. O. Dubytskyi // Litteris et Artibus : proceedings of the 5th International youth science forum, November 26–28, 2015, Lviv, Ukraine / Lviv Polytechnic National University. – Lviv : Lviv Polytechnic Publishing House, 2015. – P. 46–49. – Bibliography: 7 titles.https://ena.lpnu.ua/handle/ntb/39493A 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.encomputer visionvisual object detectionvisual object classificationbinarizationconnected component labelingintensity featurecolor featurecluster analysisConference Abstract46-49