Image Edge Detection Methods and Problems: A Review

Edge detection s one of the important parameter of image processing it basically help with preserving the image quality when image is either interpolating (enhance pixels) or decimating (compression/reduce pixels), if edges are clear and detected it can be preserve and if not the output image after image processing will not be a good quality image and image processing is in use almost in every area like Modern communication, Medical image processing, Mobile phones, graphics card etc. From the above discussion it is been clear that edge detection is one of the critical part of image processing but the question arise here is that the available methods are good or improvements required, answer is yes there are methods of edge detection which works good but not for all type of images, some methods like Canny, Roberts and Prewitt, works better for the images having high intensity and high frequencies in other hand Sobel works better for low intensity and low frequency images. Proposed work has better solution which provides edge detection for the high and low frequency/ intensity images with modified Thresholding and combination of sobel and canny Edge detection. Feature extraction is a classic problem image processing. Edges are often detected using integer-order differential operators. Hence proposed edge detection method is working in frequency and time domain parallel.