Malaria is an extensively prevalent blood infection, the most severe and widespread parasitic disease that stirring millions of people in the world. Currently, microscopy diagnosis still the most widely used method for malaria diagnosis. However, this procedure contains the probability of miscalculation of parasites due to human error. Computerized system by using image processing is recognized as a quick and easy ways to analyze a lot of blood samples. However, because of the non-standard preparation of the blood slides which producing color varieties in different slides will result on low quality images. Hence, it is difficult to identify the existence of malaria parasites as well as observing its morphological characteristics to recognize malaria parasites. Therefore, this paper aims to analyze the standardization performance between six types of color constancy algorithms namely, gray world (GW), white patch (WP), modified white patch (MWP), progressive hybrid (PH), shades of gray (SoG) and gray edge (GE) on both thick and thin blood smear malaria images of P. falciparum and P. vivax species. Six types of color constancy algorithms standardization performance are analysed by using quantitative measure namely, peak signal to noise ratio (PSNR), normalized absolute error (NAE), mean square error (MSE) and root mean square error (RMSE). Based on the qualitative and quantitative findings, the results show that SoG algorithm is the best color constancy as compared to others proposed color constancy. SoG algorithm has achieved the highest PSNR and lowest NAE, MSE and RMSE values, thus proved that the quality of malaria images have been improved.
