DocumentCode :
301186
Title :
Fast image search using a multiscale stochastic model
Author :
Sista, Srinivas ; Bouman, Charles A. ; Allebach, Jan P.
Author_Institution :
Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
Volume :
2
fYear :
1995
fDate :
23-26 Oct 1995
Firstpage :
225
Abstract :
Searching an image for the occurrence of a pattern or a template is an essential step in a number of image processing applications. We propose a new multiresolution matching criterion based on the generalized log likelihood ratio. We also developed a multiscale search technique which facilitates finding the best solution by searching a small subset of the entire set of possible template locations. The search technique is designed to keep the amount of computation at each resolution approximately the same. The results obtained on our example images demonstrate the robustness and accuracy of the matching criterion along with a speed-up of over two orders of magnitude by the search technique
Keywords :
image matching; image resolution; maximum likelihood detection; search problems; stochastic processes; accuracy; fast image search; formal detection theory; generalized log likelihood ratio; image processing applications; multiresolution matching criterion; multiscale search technique; multiscale stochastic model; pattern occurrence; resolution; robustness; template locations; Computer applications; Frequency; Image processing; Image sampling; Image segmentation; Inspection; Manuals; Mutual information; Robustness; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1995. Proceedings., International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-7310-9
Type :
conf
DOI :
10.1109/ICIP.1995.537455
Filename :
537455
Link To Document :
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