Abstract—This paper describes an automatic detection and recognition system of leukocytes on a given microscopic image. The developed system detects the locations of leukocytes from a blood cell image. After the automatic detection, the system classifies each leukocyte in one of the five categories (neutrophils, eosinophils, basophils, lymphocytes, and monocytes). The system processes an input image with the Scale Invariant Feature Transform (SIFT) algorithm for leukocyte detection. Meanwhile, two different recognition methods, i.e. the Euclidean distance and the Co-occurrence matrix methods are applied for automatic recognition. The combination of detection and recognition approaches provides the optimal recognition accuracies for almost all leukocyte types.
Index Terms—Leukocyte detection, leukocyte recognition, microscopic image, scale invariant feature transform.
Lina A. Chris, B. Mulyawan, and A. B. Dharmawan are with the Computer Science Department, Faculty of Information Technology, Tarumanagara University, Jl. Letjen. S. Parman 1, Jakarta 11440, Indonesia (e-mail: lina@untar.ac.id).
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Cite:Lina Arlends Chris, Bagus Mulyawan, and Agus Budi Dharmawan, "A Leukocyte Detection System Using Scale Invariant Feature Transform Method," International Journal of Computer Theory and Engineering vol. 8, no. 1, pp. 69-73, 2016.
