Paper
2 June 2000 Near-Gabor filter banks for feature detection and curvature estimation
Stephen J. Purves, Satnam Singh Dlay
Author Affiliations +
Proceedings Volume 3959, Human Vision and Electronic Imaging V; (2000) https://doi.org/10.1117/12.387199
Event: Electronic Imaging, 2000, San Jose, CA, United States
Abstract
Accurate detection of elementary features such as edges and lines in digital images plays an important role in early vision and is included as a first step in many image processing systems. An efficient and flexible form of feature detection is based on the responses of sets of orientation selective filters. These steerable filters can be designed to posses near Gabor properties and provide a derivable interpolation function over orientation. However, these filters are rarely designed using non-circular receptive fields and cannot be optimized in terms of angular selectivity. A line of reasoning is developed here which allows orientation selective filters to be constructed using elliptical window functions and used within a conventional steerable filter bank system. Results suggest an optimal situation existing between the rejection of unwanted signals and high angular selectivity of filters. Further results are developed which emphasize phase differences between elliptical and circular filter responses as a measure of locally convex curvature maxima.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephen J. Purves and Satnam Singh Dlay "Near-Gabor filter banks for feature detection and curvature estimation", Proc. SPIE 3959, Human Vision and Electronic Imaging V, (2 June 2000); https://doi.org/10.1117/12.387199
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KEYWORDS
Image filtering

Gaussian filters

Linear filtering

Image processing

Phase measurement

Detection and tracking algorithms

Edge detection

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