DocumentCode
3467271
Title
Robust Invariant Descriptor for Symbol-Based Image Recognition and Retrieval
Author
Wong, Alexander ; Bishop, William
Author_Institution
Univ. of Waterloo, Waterloo
fYear
2007
fDate
17-19 Sept. 2007
Firstpage
637
Lastpage
644
Abstract
This paper presents a robust invariant descriptor for symbol-based image recognition and retrieval. A modified Hough-based Transform is used to extract parameter space information (i.e., position data and angular data) from a symbol image to derive an invariant descriptor. The proposed descriptor provides a compact representation of a symbol image that can be evaluated efficiently. The extracted descriptor is highly robust against geometric transformations such as translation, rotation, reflection, and scaling, and image degradation. A series of experiments were conducted using a set of architectural and engineering symbols subjected to geometric transformations and image degradation. The experimental results clearly show that the proposed descriptor can be used effectively for symbol recognition and retrieval.
Keywords
Hough transforms; content-based retrieval; feature extraction; image recognition; image representation; image retrieval; Hough-based transform; feature extraction; geometric transformation; image degradation; image representation; image retrieval; robust invariant descriptor; symbol-based image recognition; Content based retrieval; Data mining; Degradation; Image recognition; Image retrieval; Information retrieval; Reflection; Robustness; Shape; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantic Computing, 2007. ICSC 2007. International Conference on
Conference_Location
Irvine, CA
Print_ISBN
978-0-7695-2997-4
Type
conf
DOI
10.1109/ICSC.2007.24
Filename
4338404
Link To Document