Comparative analysis for Edge Detection Techniques

Edge detection is a vital feature in the field of Computer Vision for extracting meaningful information from digital images. The primary aim of our proposed technique is to obtain thin edges, so that the result derived is suitable more for further applications such as boundary detection, image segmentation, motion detection/estimation, texture analysis, object identification and so on. We have done comparative analysis for four edge detectors that use different methods for detecting edges and have tested their results under a variety of situations to determine which detector was preferable under different circumstances. For practical analysis it was used to detect the edges and results have been compared with the gradient based methods of edge detection like Sobel, Prewitt, Robert these are first order derivative methods. Testing and analysis on different satellite images by Laplacian and gradient based method have done by using the ideal thresholding parameter for good true edges.To evaluate the performance of Laplacian based algorithms and gradient based algorithms. There is a need of calculating the some parameter for calculating the image quality. These parameters are able to identify which algorithm is best suited in detecting edges for satellite images.