Textured Image Retrieval by the Modal Analysis of Quantized Spectral Point Patterns

In this work we explore the modal correspondence method of Shapiro and Brady to match points set by comparing the eigenvectors of a pairwise point proximity matrix for peak cluster centers in the power spectrum. We use a variant of the Carcassoni, Ribeiro and Handcok method to perform recognition. T...

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Bibliographic Details
Published in16th IEEE International Conference on Tools with Artificial Intelligence pp. 771 - 773
Main Authors Barcelos, C.A.Z., Ferreira, M.J.R., Rodrigues, M.L.
Format Conference Proceeding
LanguageEnglish
Published Los Alamitos CA IEEE 2004
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Computer vision
Eigenvalues and eigenfunctions
Exact sciences and technology
Frequency
Image recognition
Image retrieval
Modal analysis
Noise robustness
Pattern recognition
Pattern recognition. Digital image processing. Computational geometry
Quantization
Invariant
Proximity
Modal analysis
Texturation
Image processing
Image retrieval
Information retrieval
Spectral analysis
Image analysis
Size effect
Pattern analysis
Artificial intelligence
Power spectrum
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Summary:In this work we explore the modal correspondence method of Shapiro and Brady to match points set by comparing the eigenvectors of a pairwise point proximity matrix for peak cluster centers in the power spectrum. We use a variant of the Carcassoni, Ribeiro and Handcok method to perform recognition. The new technique developed is invariant to rotational, scaling transformations, and is robust in the presence of noise.
ISBN:9780769522364
076952236X
ISSN:1082-3409
2375-0197
DOI:10.1109/ICTAI.2004.113