Enhanced correlation discrimination using binary joint transform correlation with feedback

1992 ◽  
Vol 5 (14) ◽  
pp. 752-757 ◽  
Author(s):  
M. S. Alam ◽  
M. A. Karim
Keyword(s):  
Joint Transform Correlation

Spectral fringe-adjusted joint transform correlation

2010 ◽  
Vol 49 (10) ◽  
pp. B18 ◽  
Author(s):  
Mohammad S. Alam ◽  
Shuhratchon Ochilov
Keyword(s):  
Joint Transform Correlation

Real-time joint transform correlation with photoanisotropic dye–polymer films

1994 ◽  
Vol 33 (32) ◽  
pp. 7634 ◽  
Author(s):  
Tizhi Huang ◽  
Kelvin H. Wagner
Keyword(s):  
Real Time ◽  
Polymer Films ◽  
Joint Transform Correlation

Bangla Character Recognition Using Optical Joint Transform Correlation

2013 ◽  
pp. 117-136 ◽  
Author(s):  
Mohammed Nazrul Islam ◽  
Mohammad Ataul Karim
Keyword(s):  
Character Recognition ◽  
High Speed ◽  
Target Location ◽  
Recognition Performance ◽  
False Alarms ◽  
Correlation Technique ◽  
Correlation Peak ◽  
Target Character ◽  
Joint Transform Correlation ◽  
Very High

Automatic Bangla character recognition has been a great challenge for research and development because of the huge number of characters, change of shape in a word and in conjunctive characters, and other similar reasons. An optical joint transform correlation-based technique is developed for Bangla character recognition which involves a simple architecture, but can operate at a very high speed because of optics, and offer a very high level of accuracy with negligible false alarms. The proposed correlation technique can successfully identify a target character in a given input scene by producing a single correlation peak per target at the target location. The discrimination between target and non-target correlation peaks is found to be very high even in noisy conditions. The recognition performance of the proposed technique is observed to be insensitive to the type and number of targets. Further improvement of the technique is made by incorporating a synthetic discriminant function, which is created from distorted images of the target character and hence can make the system efficiently recognize Bangla characters in different practical scenarios.

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