Illumination normalization of non-uniform images based on double mean filtering

In segmentation process, non-uniform illumination problem can affect the segmentation result. In this paper, a new method is proposed to solve the problem based on double mean filtering. By applying a combination between mean and threshold value, the varying background is normalized. This proposed method had been experimented with a few badly illuminated images and the result is evaluated by using Misclassification Error (ME), Sensitivity and Specificity. Based on the ME results, proposed method increases the segmentation correction to 88.27%. Besides that, the sensitivity and specificity of proposed method obtained is 94.56190% and 98.57924% and for classical Otsu is 90.30550% and 61.85435%.