Fuzzy system for color image enhancement

The main objective of image enhancement is to process the image so that the result is more suitable than the original image for a specific application. Image enhancement is a field that is being used in various areas and disciplines. Advances in computers, microcontrollers and DSP boards have opened new horizons to digital image processing, and have opened many avenues to the design and implementation of new innovative techniques. This paper involves the use of knowledge-base (fuzzy expert) systems that are capable of mimicking the behavior of a human expert. Fuzzy approach of knowing severity of tumor is essential to determine if there is a need for the biopsy and it gives to user a clear idea of spread and severity level of tumor. Fuzzy based enhancement of color feature of tumor is an application of fuzzy in the area of color feature extraction for enhancement of a peculiar feature. It has been found that RGB color model is not suitable for enhancement because the color components are not decoupled. On the other hand, in HSV color model, hue (H), the color content, is separate from saturation (S), which can be used to dilute the color content and V, the intensity of the color content. By preserving H, and changing only S and V, it is possible to enhance color image. Therefore, we need to convert RGB into HSV for the purpose. A Gaussian type membership function is used to model S and V property of the image. This membership function uses only one fuzzifier and is evaluated by maximizing fuzzy contrast. Our aim is be to analyze and enhance the features related to a specific disease. The biomedical images will be sent for fuzzification and decisions related to classification of colors will be done and accordingly output will be consisting of only the serious tumor region and noisy pixels will be filtered and image will be enhanced in the features we desire.