Detection of continuous and thin edges of noisy images by new kernel approach

In image processing, edge detection concerns with the localization of discontinuity of the gray scale images, accurately detecting continuous edges is difficult in noisy images. Usually for accurate edge detection requires smoothing and differentiation, to localize edge pixels in intensity images. Smoothing images with median filter instead of Gaussian filter has more edge preserving tendency. In this proposed method, filtered images with non- linear filter, which is convolved with two new developed 3x3 operators for detecting gradient magnitude of images. The resulted thick binary edges were filter with two new developed structure matrices for enhancement in binary edges. The new algorithm is examined and compared with the traditional edge detectors. The comparison is based on two type of distributed noises Gaussian and salt and pepper. The results comparison suggests that the new algorithm detect edges more accurate thinner and smoother than the edges detected by traditional edge detector.