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CBIR approach to building image retrieval based on invariant characteristics in Hough domain
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.
History
Event
IEEE Signal Processing Society. Conference (2008 : Las Vegas, Nevada)Series
IEEE Signal Processing Society ConferencePagination
1209 - 1212Publisher
Institute of Electrical and Electronics EngineersLocation
Las Vegas, NevadaPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2008-03-31End date
2008-04-04ISSN
1520-6149ISBN-13
9781424414840ISBN-10
1424414849Language
engPublication classification
E1.1 Full written paper - refereedEditor/Contributor(s)
[Unknown]Title of proceedings
ICASSP 2008 : Proceedings of the 2008 IEEE International Conference on Acoustics, Speech and Signal ProcessingUsage metrics
Read the peer-reviewed publication
Categories
Keywords
content based image retrieval (CBIR)feature extractionmatching algorithmHough transformimage databaseScience & TechnologyTechnologyLife Sciences & BiomedicineAcousticsComputer Science, Artificial IntelligenceComputer Science, CyberneticsEngineering, BiomedicalEngineering, Electrical & ElectronicMathematical & Computational BiologyImaging Science & Photographic TechnologyRadiology, Nuclear Medicine & Medical ImagingTelecommunicationsComputer ScienceEngineeringcontent based image retrieval (CBIR)feature extractionmatching algorithmHough transformFILTERS