Identification and ranking of relevant image content

Mustafa Jaber; Eli Saber; Sohail Dianat; Mark Shaw; Ranjit Bhaskar

doi:10.1117/12.753609

3 March 2008 Identification and ranking of relevant image content

Mustafa Jaber, Eli Saber, Sohail Dianat, Mark Shaw, Ranjit Bhaskar

Author Affiliations +

Proceedings Volume 6812, Image Processing: Algorithms and Systems VI; 68120I (2008) https://doi.org/10.1117/12.753609
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

In this paper, we present an image understanding algorithm for automatically identifying and ranking different image regions into several levels of importance. Given a color image, specialized maps for classifying image content namely: weighted similarity, weighted homogeneity, image contrast and memory colors are generated and combined to provide a metric for perceptual importance classification. Further analysis yields a region ranking map which sorts the image content into different levels of significance. The algorithm was tested on a large database of color images that consists of the Berkeley segmentation dataset as well as many other internal images. Experimental results show that our technique matches human manual ranking with 90% efficiency. Applications of the proposed algorithm include image rendering, classification, indexing and retrieval.

Citation Download Citation

Mustafa Jaber, Eli Saber, Sohail Dianat, Mark Shaw, and Ranjit Bhaskar "Identification and ranking of relevant image content", Proc. SPIE 6812, Image Processing: Algorithms and Systems VI, 68120I (3 March 2008); https://doi.org/10.1117/12.753609

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