A NOVEL MORPHOLOGICAL GRADIENT TECHNIQUE FOR EDGE DETECTION USING FUZZY LOGIC

This paper presents the edges characterize boundaries and are therefore a problem of fundamental importance in image processing. Image Edge detection significantly reduces the amount of data and filters out useless information, while preserving the important structural properties in an image. Since edge detection is in the forefront of image processing for object detection, it is crucial to have a good understanding of edge detection algorithms. In this project an edge detection method based on the morphological gradient technique and generalized type-2 fuzzy logic. The theory of alpha planes is used to implement generalized type-2 fuzzy logic for edge detection. In proposed system, a new First order Edge Detection technique is implemented. By applying the new First order techniques on the image to detect its edges, it is found that the modified version of edge map has less noise and less edge corruption. The robustness of the proposed method is analyzed, compared and evaluated using the image quality assessment metrics such as signal to noise ratio(SNR), peak signal to noise ratio (PSNR) and root mean square (RMSE) and the results are presented