| Abstract: | Hough transform is a general technique for identifying the locations and orientations of certain types of features in a digital image and used to isolate features of a particular shape within an image. Because it requires that the desired features are specified in some parametric form, classical Hough transform is the most commonly used for the detection of regular curves such as lines, circles, ellipses, etc. A generalized Hough transform can be employed in applications where a simple analytic description of features is not possible. In this paper, Canny edge detector is used in conjunction with Hough transform to detect many coins with different radii. In this case, applying threshold make a significant and determinant factor in coins detection. Also, this paper shows that the Hough transform is an effective tool for coins detection even in the presence of noise such as salt and pepper, Gaussian and speckle noise. Also Hough transform succeeded in detecting blurring coins and deforming coins.
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