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34th Applied Imagery and Pattern Recognition Workshop (AIPR'05)
Content Based Object Retrieval with Image Primitive Database
Washington, DC
October 19-October 21
ISBN: 0-7695-2479-6
Jason Kinser, Geoerge Mason University
Guisong Wang, George Mason University
Content-based image retrieval is the task of recalling images from a large database that are similar to a probe image. Many schemes have been proposed and often follow the scheme of extracting information from images and classifying this information as a single entity. We propose that image segments are far more complicated and that two adjustments are necessary. The first is that pixels do not necessarily belong to a single object and the second is that image segments can not be classified as a single entity. We propose a new approach that adopts these tenets and present results indicating the feasibility of creating syntactical definitions to image objects.
Citation:
Jason Kinser, Guisong Wang, "Content Based Object Retrieval with Image Primitive Database," aipr, pp.179-183, 34th Applied Imagery and Pattern Recognition Workshop (AIPR'05), 2005
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