Paper
30 August 2002 Content-based image retrieval by interest-point matching and geometric hashing
Chiou-Ting Hsu, Ming-chou Shih
Author Affiliations +
Abstract
This paper presents a content-based image retrieval technique based on interest points matching and geometric hashing. We estimate points with significant luminance variations as interest points. A small region around the interest point is located as an image patch. Low-level features are extracted to describe each image patch. To provide geometric invariant image matching, we index the image patches into a 2-D hash table by geometric hashing technique. Thus, the matching is invariant to global and local geometric transforms. In addition, since we use the image patch to capture the local information, the indexing can effectively handle partial matching. We formulate a matching criterion by weighted voting technique to incorporate the spatial interrelationship into consideration. We have performed a series of experiments to confirm the effectiveness of our method. Images are globally transformed and locally manipulated to examine the efficiency of our indexing scheme. Experimental results indicate satisfactory retrieval in the case of partial matching and geometric transformation.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chiou-Ting Hsu and Ming-chou Shih "Content-based image retrieval by interest-point matching and geometric hashing", Proc. SPIE 4925, Electronic Imaging and Multimedia Technology III, (30 August 2002); https://doi.org/10.1117/12.481572
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Image retrieval

Databases

Content based image retrieval

Image processing

Feature extraction

Transform theory

Distortion

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