30 March 2000 Class of detail-controllable edge-detecting operator
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Proceedings Volume 4055, Applications and Science of Computational Intelligence III; (2000); doi: 10.1117/12.380566
Event: AeroSense 2000, 2000, Orlando, FL, United States
Abstract
The basic idea of theory of Marr's image edge-detecting is firstly to smooth original image with Gaussian function, then obtain the zero-cross map of Laplacian's transform of smoothed image. However, the residual between the original image and smoothed image remain s some feature points that may not be detected. Therefore, this paper firstly proposed a new smoothing operator which has low-pass characteristics similar to a Butterworth filter and limited spatial extent similar to a Gaussian function, then we constructed a class of edge-detecting operator that can be controlled more easily using Laplace's transform. The new edge-detecting operator also has closed forms that facilitate implementation, and allows us flexibility control feature- detecting accuracy compared to Marr's operator. In addition, Marr's edge-detecting operator is a special formulation of a new operator. Practical numerical experimental results showed that hose edge-detecting operators have some practical effect and reference value.
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Zheng Tan, Shuanhu Wu, "Class of detail-controllable edge-detecting operator", Proc. SPIE 4055, Applications and Science of Computational Intelligence III, (30 March 2000); doi: 10.1117/12.380566; https://doi.org/10.1117/12.380566
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KEYWORDS
Smoothing

Linear filtering

Edge detection

Gallium

Image processing

Signal processing

Computer vision technology

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