Image Segmentation by Using Different Types of Edge Detection Algorithm with Different Thresholds

Segmentation algorithms for images generally are based on one of two basic properties of image intensity values: discontinuity and similarity. In the first category, the approach is to position an image based on abrupt changes in intensity, such as edges. The principal approaches in the second category are based on partitioning an image into regions that are similar. In this paper we discuss a number of approaches into two categories just mentioned, as they apply to images. Edge detection has been staple of segmentation algorithms for many years. We compare different types of edge detection techniques like Sobel, Prewitt, Roberts, Laplacian of Gaussian(LoG),Zero crossing and Canny in this paper.