Augmented image histogram for image and video similarity search

Y. Chen, E. K. Wong

    Research output: Contribution to journalConference article

    Abstract

    Image histogram is an image feature widely used in content-based image retrieval and video segmentation. It is simple to compute yet very effective as a feature in detecting image-to-image similarity, or frame-to-frame dissimilarity. While the image histogram captures the global distribution of different intensities or colors well, it does not contain any information about the spatial distribution of pixels. In this paper, we propose to incorporate spatial information into the image histogram by computing features from the spatial distance between pixels belonging to the same intensity or color. In addition to the frequency count of the intensity or color, the mean, variance, and entropy of the distances are computed to form an Augmented Image Histogram. Using the new feature, we preformed experiments on a set of color images and a color video sequence. Experimental results demonstrate that the Augmented Image Histogram performs significantly better than the conventional color histogram, both in image retrieval and video shot segmentation.

    Original languageEnglish (US)
    Pages (from-to)523-532
    Number of pages10
    JournalProceedings of SPIE - The International Society for Optical Engineering
    Volume3656
    StatePublished - Jan 1 1999
    EventProceedings of the 1999 7th Conference of the Storage and Retrieval for Image and Video Databases VII - San Jose, Ca, USA
    Duration: Jan 26 1999Jan 29 1999

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    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials
    • Condensed Matter Physics
    • Computer Science Applications
    • Applied Mathematics
    • Electrical and Electronic Engineering

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