An edge extraction technique for noisy images
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An algorithm for extracting edges from noisy images is presented. The method uses an unsupervised learning approach for local threshold computation by means of K. Pearson's (1984) method for mixture density identification. The technique was tested by applying it to computer-generated images corrupted with artificial noise and to an actual thallium-201 heart image, and it is shown that the technique has potential use for noisy images.<<ETX>>
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