Title :
Optimal ramp edge detection using expansion matching
Author :
Wang, Zhiqian ; Rao, K. Raghunath ; Ben-Arie, Jezekiel
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA
fDate :
11/1/1996 12:00:00 AM
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 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
Keywords :
edge detection; filtering theory; low-pass filters; Canny´s criteria; discriminative signal-to-noise ratio; expansion matching; ideal step edges; imaging systems; low pass filtering; optimal ramp edge detection; severe occlusion; superposition; Detectors; Filtering; IIR filters; Image edge detection; Low pass filters; Matched filters; Noise level; Optical filters; Optical imaging; Signal to noise ratio;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
