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Edge detection using the linear model

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2 Author(s)
Kay, S.M. ; University of Rhode Island, Kingston, RI, USA ; Lemay, G.

An edge detector based on the linear model is developed which utilizes the generalized likelihood ratio for statistical hypothesis testing. The detector is invariant to multiplicative changes in the gray-scale values of the image. Hence, thresholding based histogram segmentation is not required. The performance of this detector is analytically and experimentally compared to that of a gradient operator (Sobel) and is shown to have only a slightly poorer detection rate for a given false alarm rate.

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Acoustics, Speech and Signal Processing, IEEE Transactions on  (Volume:34 ,  Issue: 5 )