Paper
15 January 1997 Spatial encoding using differences of global features
Alexander Dimai
Author Affiliations +
Abstract
While histogram or global feature approaches are powerful methods to encode image information for retrieval purposes, they suffer from a complete lack of spatial information. One possibility to overcome this drawback is the storage of the feature vectors of subregions. However, this increases the size of the index vector. The paper suggests to store only the differences of the features between a region and its subregions, instead the whole feature vector of subregions. This introduced distance is called inter hierarchical distance (IHD). A new index, which combines the IHD and global color feature of the whole image, is suggested. The subregions are gained by a fixed tessellation. Experimental results, using an image database with more than 12'000 color images, are presented. The retrieval power of the combined index is as powerful as an index which is 2.5 times larger in size and just needs global color features. The IHD is invariant to linear color transformation, which ensures a more stable performance of the index under gamma corrections.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alexander Dimai "Spatial encoding using differences of global features", Proc. SPIE 3022, Storage and Retrieval for Image and Video Databases V, (15 January 1997); https://doi.org/10.1117/12.263423
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CITATIONS
Cited by 13 scholarly publications and 2 patents.
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KEYWORDS
Image retrieval

Databases

Feature extraction

Computer programming

Image storage

Detection and tracking algorithms

Distance measurement

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