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Optimal ramp edge detection using expansion matching

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3 Author(s)
Zhiqian Wang ; Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA ; Raghunath Rao, K. ; Ben-Arie, J.

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 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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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:18 ,  Issue: 11 )