In c-Met cancer this way, two sets of values corresponding to the pixels

of healthy skin are captured. Then 2 s and 3° polynomial functions, which are defined in equations 2 and 3, respectively, have been considered and are adopted adapted on these two sets of samples by the least squares method. In the equations 2 and 3, Pi (i = 1,…, 6 for Q2 and i = 1,…, 10 for Q3) determines quadric function parameter and (x, y) is image spatial location. Thus, four different planes were estimated which represent four various modes of illumination distribution on the image with respect to the relative area of the lesion in image, location of lesion on body and the way of lighting while imaging. Then four V channels which have uniform illumination are obtained by dividing the original

V channel on these four planes. Figure 3 shows the four estimated planes for a skin lesion image and the result of elimination of each one from the image. Figure 3 (a) Smoothed image of a skin lesion, (b and c) Results of adaption of two-degree polynomial function on the corners samples, (d and e) Results of adaption of three-degree polynomial function on the corners samples, (f and g) Results of adaption of two-degree … If each one of these four processed V channel would be used for the following operations, images with uniform illumination are obtained that their healthy skin color is bright and different from the original image as can be seen in Figure 3.

In order to retrieve true color of the skin, Eq. 4 is applied on each of processed V channels.[9] In this equation, Vproc is the processed V channel, Vorig is the original V channel, μ represents mean of the respective channel and Vnew is new V channel. Then among new and original V channels, an image which has the least instability level, and therefore entropy, is chosen as the best V channel with uniform illumination because existence of shadow on the image leads to Batimastat increased instability. This channel is replaced to the original V channel, and the final image is converted from HSV color space to RGB space. Figure 4 shows the image of a skin lesion with shadow that the proposed median filter and shadow reduction method were applied on. Figure 4 A skin lesion image (a) The original image, (b) The processed image after applying median filter and shadow reduction method The second step in the preprocessing stage is segmentation of the lesion area from surrounding normal skin. For this purpose, a new, simple and accurate segmentation method, which is based on thresholding technique is introduced in which the single-channel images containing determinant factors of lesion border meaning color, illumination and texture are obtained firstly.