CBIR approach to building image retrieval based on invariant characteristics in Hough domain

Xiang Yuan, Chang Tsun Li

Research output: Book chapter/Published conference paperConference paper

9 Citations (Scopus)

Abstract

In this paper, we propose two rotation and scale invariant features extracted from the Hough transform domain to guide a CBIR system in the search of relevant building images. Upon receiving a query image, the CBIR system transforms the edges detected from the query into the Hough domain with 180 degrees/bins. From each bin, the peak percentage and peak distance ratio are calculated. The circular correlations between the peak percentages and peak distance ratios across the 180 bins of the query image and those of the database images are then taken as the similarity measure for ranking the relevance of the database images to the query.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages1209-1212
Number of pages4
DOIs
Publication statusPublished - 2008
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: 31 Mar 200804 Apr 2008

Conference

Conference2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
CountryUnited States
CityLas Vegas, NV
Period31/03/0804/04/08

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  • Cite this

    Yuan, X., & Li, C. T. (2008). CBIR approach to building image retrieval based on invariant characteristics in Hough domain. In 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP (pp. 1209-1212). [4517833] https://doi.org/10.1109/ICASSP.2008.4517833