An Improved Fast Edge Detection for Medical Image Based on Fuzzy Techniques

Image detection is important step in image processing. Image processing is to process and dispose by some mathematical operation on the image information in order to meet the human visual and medical needs. Finding the correct boundary in noisy images is a difficult task. The function of edge detection is to identify the boundaries of homogeneous regions in an image based on properties such as intensity and texture. A fast edge detection method basing on the combination of Fuzzy techniques was developed. Fuzzy logic represents a good mathematical framework to deal with uncertainty of information. Fuzzy image processing is the collection of all approaches that understand, represent and process the images, their segments and features as Fuzzy sets. 
The representation and processing depend on the selected Fuzzy technique and on the problem to be solved. In Medical imaging, the level of beam projection is kept low to minimize the damage to the tissues, also minimizing image signal contrast. In this work the detection of an edge as a classification problem will be considered, partitioning the image into two portions: the edge portion and the non-edge portion. The latter one, as the main constituent of an image, consists of the object and its background. Removing the non-edge portion from an image, the remainder is nothing but the edge of this image. The proposed method is robust and applicable on various kinds of noisy images without prior knowledge of noise properties. The simulation results shows efficacy of proposed method.