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1 March 1992 Robust method of edge detection
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Abstract
We present here the theory of developing robust test statistics for edge shape matching in one dimensional signals. We show that an unbiased test can be developed under the assumption of uncorrelated noise and this test can be made optimal and robust to perturbations of the assumed noise distribution under the extra assumption of symmetric noise. This approach to edge detection is believed to overcome the shortcomings of the uncertainty principle in image processing and is appropriate for use when edges of a certain type have to be identified with great accuracy in their location.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maria Petrou and Josef Kittler "Robust method of edge detection", Proc. SPIE 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics, (1 March 1992); https://doi.org/10.1117/12.58578
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