Distortion-invariant face recognition using multiple phase-shifted reference-based joint transform correlation technique

2011 ◽  
Author(s):  
Mohammed Nazrul Islam ◽  
K. Vijayan Asari ◽  
Mohammad A. Karim
Keyword(s):  
Face Recognition ◽  
Correlation Technique ◽  
Multiple Phase ◽  
Joint Transform Correlation

Long range face recognition using shifted phase joint transform correlation technique

2009 ◽  
Author(s):  
Trisha Ahmed ◽  
Mohammed Nazrul Islam ◽  
K. Vijayan Asari ◽  
Mohammad A. Karim
Keyword(s):  
Face Recognition ◽  
Long Range ◽  
Correlation Technique ◽  
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.

scholarly journals ASSAS: An automatic smart students attendance system based on normalized cross-correlation

2021 ◽  
Vol 10 (2) ◽  
pp. 732-741
Author(s):  
Ruaa H. Ali Al-Mallah ◽  
Dheyaa Alhelal ◽  
Razan Abdulhammed
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Cross Correlation ◽  
Correlation Technique ◽  
Human Being ◽  
Roll Call ◽  
Student Attendance ◽  
Normalized Cross Correlation ◽  
Two Phases ◽  
Cross Correlation Technique

A smart student attendance system (SSAS) is presented in this paper. The system is divided into two phases: hardware and software. The Hardware phase is implemented based on Arduino's camera while the software phase is achieved by using image processing with face recognition depended on the cross-correlation technique. In comparison with traditional attendance systems, roll call, and sign-in sheet, the proposed system is faster and more reliable (because there is no action needed by a human being who by its nature makes mistakes). At the same time, it is cheaper when compared with other automatic attendance systems. The proposed system provides a faster, cheaper and reachable system for an automatic smart student attendance that monitors and generates attendance report automatically.

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