JahnnobiRahman/Edge_Detection_Image

What are edges We can also say that sudden changes of discontinuities in an image are called as edges. Significant transitions in an image are called as edges. Types of edges Generally edges are of three types: Horizontal edges Vertical Edges Diagonal Edges Why detect edges Most of the shape information of an image is enclosed in edges. So first we detect these edges in an image and by using these filters and then by enhancing those areas of image which contains edges, sharpness of the image will increase and image will become clearer. Here are some of the masks for edge detection that we will discuss in the upcoming tutorials. Prewitt Operator Sobel Operator Robinson Compass Masks Krisch Compass Masks Laplacian Operator. Above mentioned all the filters are Linear filters or smoothing filters. Prewitt Operator Prewitt operator is used for detecting edges horizontally and vertically. Sobel Operator The sobel operator is very similar to Prewitt operator. It is also a derivate mask and is used for edge detection. It also calculates edges in both horizontal and vertical direction. Robinson Compass Masks This operator is also known as direction mask. In this operator we take one mask and rotate it in all the 8 compass major directions to calculate edges of each direction. Kirsch Compass Masks Kirsch Compass Mask is also a derivative mask which is used for finding edges. Kirsch mask is also used for calculating edges in all the directions. Laplacian Operator Laplacian Operator is also a derivative operator which is used to find edges in an image. Laplacian is a second order derivative mask. It can be further divided into positive laplacian and negative laplacian. All these masks find edges. Some find horizontally and vertically, some find in one direction only and some find in all the directions. The next concept that comes after this is sharpening which can be done once the edges are extracted from the image