DocumentCode
759821
Title
Object matching using deformable templates
Author
Jain, Anil K. ; Zhong, Yu ; Lakshmanan, Sridhar
Author_Institution
Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI, USA
Volume
18
Issue
3
fYear
1996
fDate
3/1/1996 12:00:00 AM
Firstpage
267
Lastpage
278
Abstract
We propose a general object localization and retrieval scheme based on object shape using deformable templates. Prior knowledge of an object shape is described by a prototype template which consists of the representative contour/edges, and a set of probabilistic deformation transformations on the template. A Bayesian scheme, which is based on this prior knowledge and the edge information in the input image, is employed to find a match between the deformed template and objects in the image. Computational efficiency is achieved via a coarse-to-fine implementation of the matching algorithm. Our method has been applied to retrieve objects with a variety of shapes from images with complex background. The proposed scheme is invariant to location, rotation, and moderate scale changes of the template
Keywords
Bayes methods; image matching; image segmentation; object recognition; probability; visual databases; Bayesian scheme; deformable templates; edge information; image database; image segmentation; object localization; object matching; object shape; optimisation; probabilistic deformation; Bayesian methods; Computational efficiency; Computer science; Image databases; Image retrieval; Image segmentation; Information retrieval; Object recognition; Prototypes; Shape;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.485555
Filename
485555
Link To Document