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Multiresolution Object-of-Interest Detection

By For Images With, Jia Li, James Ze, Wang Robert, M. Gray and Gio Wiederhold


This paper describes a novel multiresolution image segmentation algorithm for separating sharply focused objects-of-interest from other foreground or background objects in low depth of #eld #DOF# images, such as sports, telephoto, macro, and microscopic images. The algorithm takes a multiscale context-dependent approach to segment images basedonfeatures extracted from wavelet coe#cients in high frequency bands. The algorithm is fully automatic in that all parameters are image independent. Experiments with the algorithm on more than 100 low DOF images have shown results close to the human segmentation of these images. Besides high accuracy, the algorithm also provides high speed. A 768#512 pixel image can besegmented within two seconds on a Pentium Pro 300MHz PC

Publisher: e) (f
Year: 1999
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
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