Master'sOpen Access

Comparison of face recognition principal component analysis and linear discriminant analysis methods in image processing in android mobile application

2019
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Advisor: Dr. Öğr. Üyesi Ege Kipman

Abstract (EN)

In today's technology, image processing takes up an important place and it is seen in many different areas. Face recognition that makes our lives easier; In the health sector, employee monitoring systems, industrial areas, defense industry is used in such areas and needs are increasing day by day. The input and output information of the employees is now kept by face recognition systems, images for the plate identification, speed limit controls in traffic are processed, and most of the diseases in the health sector are determined by image processing systems. In this way, the workload is reduced, stability and reliability are increased. Processes that can last for weeks, months or even years without using image processing methods are now reduced to minutes and seconds. As these systems are trained, error rates decrease and they become more stable day by day. In this study, the facial recognition of image processing methods; This is a mobile application on the two different methods implemented and compared with each other in terms of performance, the results were tried to be examined.

Author

Dr. Cem Tanrıkut

How to Cite

Cem Tanrıkut (Master Thesis). Comparison of face recognition principal component analysis and linear discriminant analysis methods in image processing in android mobile application, 2019, İstanbul Beykent University.

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