Paper
17 December 1998 Augmented image histogram for image and video similarity search
Yu Chen, Edward K. Wong
Author Affiliations +
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 performed 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 the image retrieval and video shot segmentation.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yu Chen and Edward K. Wong "Augmented image histogram for image and video similarity search", Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); https://doi.org/10.1117/12.333872
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CITATIONS
Cited by 21 scholarly publications.
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KEYWORDS
Video

Image retrieval

Image segmentation

Databases

Feature extraction

Content based image retrieval

Image processing

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