Comparative Analysis of Edge Detection Techniques
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Segmentation of images is a major task of image processing. It is a long standing problem in computer vision as there is no general segmentation procedure that can deal with all sorts of images. Different fundamental algorithms of image segmentation are implemented like Edge Detection (Discontinuity based Segmentation), Region Growing (Similarity Based Segmentation), Iterative Thresholding Method. The purpose of this report is to use edge detection and Thresholding based on edge operators of the images of license plates, name plates and sign boards. Five operators used are Prewitt, Roberts, So...
Segmentation of images is a major task of image processing. It is a long standing problem in computer vision as there is no general segmentation procedure that can deal with all sorts of images. Different fundamental algorithms of image segmentation are implemented like Edge Detection (Discontinuity based Segmentation), Region Growing (Similarity Based Segmentation), Iterative Thresholding Method. The purpose of this report is to use edge detection and Thresholding based on edge operators of the images of license plates, name plates and sign boards. Five operators used are Prewitt, Roberts, Sobel, LoG and Canny and towards the end all these operators are compared on the basis of results. In the method mathematical morphological operations also plays a significant role. Two morphological operations used are Dilation and holes filling process. Dilation helps in thickening the edges of characters and holes filling process enhanced the visual appearance of the images. The proposed system has been implemented using MATLAB.
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