DocumentCode :
2914887
Title :
Detecting local features in complex images: A combination of Hough transform and moment-based approximations
Author :
Sluzek, Andrzej
Author_Institution :
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
fYear :
2008
fDate :
17-20 Dec. 2008
Firstpage :
1323
Lastpage :
1328
Abstract :
The paper presents fundamentals and preliminary results of a technique for defining, building and positioning novel local feature. The features are created by approximating the content of a scanning circular window by a collection of predefined patterns. Although basics of the technique have been discussed in previous papers, the major modification is the introduction of Hough transform as a part of the algorithm. By applying a modified Hough transform to the contents of scanning windows, approximations can be build more reliably (the algorithm is not sensitive to so-called ldquovisual intrusionsrdquo) more accurately (localization of features is more precise) and at lower computational costs (a part of complex mathematics in previously used moment-based approximations can be avoided).
Keywords :
Hough transforms; approximation theory; image matching; object detection; Hough transforms; complex image; local feature detection; moment-based approximation; scanning window; Computer vision; Detectors; Image analysis; Image matching; Image retrieval; Information retrieval; Machine vision; Object detection; Robotics and automation; Shape; Hough transform; Image matching; keypoints; local features; moments;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on
Conference_Location :
Hanoi
Print_ISBN :
978-1-4244-2286-9
Electronic_ISBN :
978-1-4244-2287-6
Type :
conf
DOI :
10.1109/ICARCV.2008.4795713
Filename :
4795713
Link To Document :
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