Translator Disclaimer
Paper
17 December 1998 Augmented image histogram for image and video similarity search
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
PROCEEDINGS
10 PAGES


SHARE
Advertisement
Advertisement
RELATED CONTENT

Content-based image retrieval and high-level representations
Proceedings of SPIE (December 20 2001)
Case for image querying through image spots
Proceedings of SPIE (January 01 2001)
Content based image and video retrieval
Proceedings of SPIE (February 26 2010)
Automatic annotation of image and video using semantics
Proceedings of SPIE (February 26 2010)

Back to Top