Two Stage Distributed Canny Edge Detector For Images Corrupted With Gaussian Noise

Abstract

In classification and recognition of objects the most commonly used features are edges, which are the locations where the intensity values change more than a predefined threshold value. The widely used edge detection algorithms is Canny edge detection method due to its superior performance. Directly applying the original Canny detector on noisy images will identify noise content also as edge content. The proposed method is a two stage filter , will restore the image corrupted by Gaussian noise using Nonlinear filtering and then applies distributed Canny edge detection algorithm that adaptively computes the thresholds used to identify the edges based on the type of a block and the local distribution of the gradients in the image block. This proposed scheme, obtains accurate edge pixels from a denoised image with higher Figure of Merit (FOM values.