DOI: 10.5176/978-981-08-8669-1_SCR2011_14

Authors: Puteri Suriyani Binti Megat Wazir, Ahmad Fauzan Kadmin, Hamzah Asyrani Sulaiman, Shamsul Fakhar Abd Ghani

Abstract:
Performing analysis of the blood cell using sophisticated image recognition system is not always an easy task for researcher. Numerous algorithms have been developed in order to characterize type of blood cell from hundreds of images. Blood cell consists three different kinds of cells that represent its blood elements; they are red, white, and blood platelets. In order to differentiate the blood cell from the image, image segmentation algorithms will be used to highlight all existing elements. Unfortunately there will always be an overlapping area on the blood cell image, creating a so-called gray area that will reduce the accuracy of the segmentation result. For example, the image might show an overlap area between red and white cells and thus a gray area appeared as a result of those overlapping parts. Thus, in this research, a review of a few selected algorithms to recognize and perform segmentation is discussed in details. This paper intends to give an overview and brief details about common and well-known technology to perform segmentation and recognition of the blood cells image.

Keywords: Blood cell algorithm, image recognition, image segmentation, algorithm

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