Paper
23 December 1999 Color compact descriptor for fast image and video segment retrieval
Santhana Krishnamachari, Mohamed Abdel-Mottaleb
Author Affiliations +
Proceedings Volume 3972, Storage and Retrieval for Media Databases 2000; (1999) https://doi.org/10.1117/12.373592
Event: Electronic Imaging, 2000, San Jose, CA, United States
Abstract
Histograms are the most prevalently used representation for the color content of images and video. An elaborate representation of the histograms requires specifying the color centers of the histogram bins and the count of the number of image pixels with that color. Such an elaborate representation, though expressive, may not be necessary for some tasks in image search, filtering and retrieval. A qualitative representation of the histogram is sufficient for many applications. Such as representation will be compact and greatly simplify the storage and transmission of the image representation. It will also reduce the computational complexity of search and filtering algorithms without adversely affecting the quality. We present such a compact binary descriptor for color representation. This descriptor is the quantized Haar transform coefficients of the color histogram. We show the use of this descriptor for browsing large image databases without the need for computationally expensive clustering algorithms. The compact nature of the descriptor and the associated simple similarity measure allows searching over a database of about four hours of video in less than 5-6 seconds without the use of any sophisticated indexing scheme.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Santhana Krishnamachari and Mohamed Abdel-Mottaleb "Color compact descriptor for fast image and video segment retrieval", Proc. SPIE 3972, Storage and Retrieval for Media Databases 2000, (23 December 1999); https://doi.org/10.1117/12.373592
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Cited by 4 scholarly publications.
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KEYWORDS
Video

Binary data

Image segmentation

Databases

Image retrieval

Image filtering

Quantization

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