DocumentCode :
3058125
Title :
Address block location on envelopes using Gabor filters: supervised method
Author :
Jain, Anil K. ; Bhattacharjee, Sushil K.
Author_Institution :
Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI, USA
fYear :
1992
fDate :
30 Aug-3 Sep 1992
Firstpage :
264
Lastpage :
267
Abstract :
The authors have implemented a texture-based supervised segmentation method to identify potential destination address blocks in envelope images. Texture features are computed by using a set of even symmetric Gabor filters. A one-layer neural network classifier is used to classify pixels into text and non-text categories using four texture features. The authors also present a simple heuristic to select the correct destination address block from among several candidates identified. The method works well on several envelope images
Keywords :
filters; image recognition; image segmentation; mailing systems; neural nets; postal services; Gabor filters; address block location; envelope images; heuristic; image recognition; one-layer neural network classifier; postal automation; supervised classification; texture features; texture-based supervised segmentation; Automation; Computer science; Frequency; Gabor filters; Histograms; Image segmentation; Machine vision; Neural networks; Optical character recognition software; Postal services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2915-0
Type :
conf
DOI :
10.1109/ICPR.1992.201769
Filename :
201769
Link To Document :
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