EFFICACY OF CIELAB AND CMYK COLOR SPACES IN LEUKEMIA IMAGE ANALYSIS: A COMPARISON BY STATISTICAL TECHNIQUES

There are several color models available and which color model to be used is a question to many researchers in the field of Medical Image Processing and Analysis. In this paper, the suitability of using the CIELAB and CMYK color spaces in processing and analyzing blood smear images of leukemia is assessed for comparison. Leukemia is commonly known as blood cancer and it usually leads to an abnormal proliferation of leukocytes (White Blood Cells) in the bone marrow and blood. The diagnosis of leukemia is primarily done by Pathologists by microscopically examining the blood and bone marrow smears of the suspected patient. Image processing-based methods can be used for automated detection and classification of leukemia to assist the Pathologists for a speedy diagnosis. The proposed study used [Formula: see text]-means clustering to segment the leukocytes and leukemic blast cells. The microscopic smear images in RGB color format were transformed and processed in CIELAB as well as CMYK color spaces for comparison. Statistical analysis was performed using Student’s [Formula: see text] test. The visual observation of the segmented images revealed that, processing the images in the CIELAB color space is comparatively better than the CMYK color space and it is reflected in the results of statistical comparison by Student’s [Formula: see text] test. The study assessed the suitability of using the CIELAB and CMYK color spaces in segmentation and analysis of microscopic smear images of Leukemic and Normal cases and found that processing the images in CIELAB color space is comparatively better than CMYK and such comparative analysis is not available in the literature.