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Edge detection is an important field in image processing. It can be used in many applications such as segmentation, registration, feature extraction, and identification of objects in a scene. This book deals with the different types of applications of edge detection in real life. It presents the different methods of edge detection, such as classical methods, multi-resolution methods, nonlinear methods, wavelet based methods, statistical methods, machine learning based methods, contextual methods, line edge detectors, and coloured edges methods. In addition, it presents various techniques of different authors such as Pun, Kapur, Li, Shanbag, Sahoo, Yen, and Pal. In this way, it presents the modified algorithm of Baljit and Amar algorithm. It has been observed that the proposed edge detector works effectively for different gray scale digital images. The results of this study were quite promising. In addition, it introduces new proposed algorithm of edge detection based on split/merge technique. It is decrease the computation time with generate high quality of edge detection. From the results; it works well as compare to the previous classical methods.