Title :
Content based object retrieval with image primitive database
Author :
Kinser, Jason ; Wang, Guisong
Author_Institution :
Sch. of Comput. Sci., George Mason Univ., Fairfax, VA, USA
Abstract :
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.
Keywords :
content-based retrieval; image classification; image retrieval; image segmentation; visual databases; content-based image retrieval; image objects; image primitive database; image segments; information classification; syntactical definitions; Content based retrieval; Data mining; Image converters; Image databases; Image retrieval; Image segmentation; Information retrieval; Libraries; Probes; Shape;
Conference_Titel :
Applied Imagery and Pattern Recognition Workshop, 2005. Proceedings. 34th
Print_ISBN :
0-7695-2479-6
DOI :
10.1109/AIPR.2005.24