Color transformation method for protanopia vision deficiency using artificial neural network - Wahab, N. H. N. A. (Universiti Teknikal Malaysia Melaka, 2016)
The objective of this project is to improve the ability of color discrimination for Protanope, who does not naturally develop red color or long wavelength cones. Intelligent method using image processing with Artificial Neural Network (ANN) is proposed to improve the ability of color discrimination as well as adjusting the images and colors. The image is stimulated by converting RGB space to LMS (long, medium, short) color space based on cone response and then modifies the response of the deficient cones. The linear multiplication matrix is referred to CIE color matching functions. Then the ANN is setting up by using the input/output from matrix conversion. The transformation of RGB color contrast technique is used to enhance contrast between red and green, which in general is green pixels appear to be bluer. Based on the result, the objectives are successfully achieved, which the ANN gives the minimum computational time than conventional matrix conversion, which is 36% increment. The changes of the image drastically for both color blind and non-color blind viewer. The result shows that the reds become redder and greens become greener from the image before being adjusted.