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Optimal Ramp Edge Detection Using Expansion Matching
November 1996 (vol. 18 no. 11)
pp. 1092-1097

Abstract—In practical images, ideal step edges are actually transformed into ramp edges, due to the general low pass filtering nature of imaging systems. This paper discusses the application of the recently developed Expansion Matching (EXM) method for optimal ramp edge detection. EXM optimizes a novel matching criterion called Discriminative Signal-to-Noise Ratio (DSNR) and has been shown to robustly recognize templates under conditions of noise, severe occlusion, and superposition. We show that our ramp edge detector performs better than the ramp detector obtained from Canny's criteria in terms of DSNR and is relatively easier to derive for various noise levels and slopes.

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Index Terms:
Canny edge detector, edge detection, optimal filters; ramp edges, step edges, Expansion Matching (EXM), Discriminative Signal-to-Noise Ratio (DSNR).
Citation:
Zhiqian Wang, K. Raghunath Rao, Jezekiel Ben-Arie, "Optimal Ramp Edge Detection Using Expansion Matching," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 11, pp. 1092-1097, Nov. 1996, doi:10.1109/34.544078
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