Building Local Features from Pattern-Based Approximations of Patches: Discussion on Moments and Hough Transform

The paper overviews the concept of using circular patches as local features for image description, matching, and retrieval. The contents of scanning circular windows are approximated by predefined patterns. Characteristics of the approximations are used as feature descriptors. The main advantage of...

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Main Author: Andrzej Sluzek
Format: Article
Language:English
Published: SpringerOpen 2009-01-01
Series:EURASIP Journal on Image and Video Processing
Online Access:http://dx.doi.org/10.1155/2009/959536
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spelling doaj-25be77fe651f4090b54bc200e063dd612020-11-25T01:37:17ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-51761687-52812009-01-01200910.1155/2009/959536Building Local Features from Pattern-Based Approximations of Patches: Discussion on Moments and Hough TransformAndrzej SluzekThe paper overviews the concept of using circular patches as local features for image description, matching, and retrieval. The contents of scanning circular windows are approximated by predefined patterns. Characteristics of the approximations are used as feature descriptors. The main advantage of the approach is that the features are categorized at the detection level, and the subsequent matching or retrieval operations are, thus, tailored to the image contents and more efficient. Even though the method is not claimed to be scale invariant, it can handle (as explained in the paper) image rescaling within relatively wide ranges of scales. The paper summarizes and compares various aspects of results presented in previous publications. In particular, three issues are discussed in detail: visual accuracy, feature localization, and robustness against “visual intrusions.†The compared methods are based on relatively simple tools, that is, area moments and modified Hough transform, so that the computational complexity is rather low.http://dx.doi.org/10.1155/2009/959536
collection DOAJ
language English
format Article
sources DOAJ
author Andrzej Sluzek
spellingShingle Andrzej Sluzek
Building Local Features from Pattern-Based Approximations of Patches: Discussion on Moments and Hough Transform
EURASIP Journal on Image and Video Processing
author_facet Andrzej Sluzek
author_sort Andrzej Sluzek
title Building Local Features from Pattern-Based Approximations of Patches: Discussion on Moments and Hough Transform
title_short Building Local Features from Pattern-Based Approximations of Patches: Discussion on Moments and Hough Transform
title_full Building Local Features from Pattern-Based Approximations of Patches: Discussion on Moments and Hough Transform
title_fullStr Building Local Features from Pattern-Based Approximations of Patches: Discussion on Moments and Hough Transform
title_full_unstemmed Building Local Features from Pattern-Based Approximations of Patches: Discussion on Moments and Hough Transform
title_sort building local features from pattern-based approximations of patches: discussion on moments and hough transform
publisher SpringerOpen
series EURASIP Journal on Image and Video Processing
issn 1687-5176
1687-5281
publishDate 2009-01-01
description The paper overviews the concept of using circular patches as local features for image description, matching, and retrieval. The contents of scanning circular windows are approximated by predefined patterns. Characteristics of the approximations are used as feature descriptors. The main advantage of the approach is that the features are categorized at the detection level, and the subsequent matching or retrieval operations are, thus, tailored to the image contents and more efficient. Even though the method is not claimed to be scale invariant, it can handle (as explained in the paper) image rescaling within relatively wide ranges of scales. The paper summarizes and compares various aspects of results presented in previous publications. In particular, three issues are discussed in detail: visual accuracy, feature localization, and robustness against “visual intrusions.†The compared methods are based on relatively simple tools, that is, area moments and modified Hough transform, so that the computational complexity is rather low.
url http://dx.doi.org/10.1155/2009/959536
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