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|Title:||Face detection and recognition||Other Titles:||Face detection & recognition||Authors:||Sassine, Mounir
Jabbour, Miled El
|Advisors:||Dagher, Issam||Subjects:||Human face recognition (Computer science)||Issue Date:||2015||Abstract:||
Face detection and recognition systems have proved to be of ultimate importance in the past two decades. The need of automatic recognitions and surveillance systems, the design of human-computer interface, the interest in human visual system, etc… are some of the reasons why face recognition has been one of the most appealing and significant study areas. The purpose of this project is to enhance the existing face detection system, and then to simulate an automated and miniaturized model of such a system, simulate an image processing study and finally simulate an interface for the system. First the existing system was studied in depth, i.e. the concepts, instruments, infrastructure used, critical techniques and algorithms etc… After that, different factors such as lighting, facial expression, image conditions… were studied to attain improved detection and recognition rate. The model for the operation of a face detection system was simulated using the data acquisition toolbox of MATLAB and images acquired from a unique database due to the lack of open and accessible databases. In the image processing part, the simulations included image filtering, extent study of its characteristics and PCA technique to compare the captured images with the existing Database. In the final part, a graphical user interface was created to provide a tool for the user to be able to see the results of the modeling and recognition technique, analyze the different parameters to be considered while building this system and integrating it in the face detection system to show the results. Finally, some improvements and steps for future work were suggested to make the face recognition system more efficient, accurate and more secure.
Includes bibliographical references (p.56-57).
Supervised by Dr. Issam Dagher.
|URI:||https://scholarhub.balamand.edu.lb/handle/uob/3388||Rights:||This object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holder||Ezproxy URL:||Link to full text||Type:||Project|
|Appears in Collections:||UOB Theses and Projects|
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