Real Time Human Identification Systems “Face Recognition
| dc.contributor.advisor | Tarapiah, Saed | |
| dc.contributor.author | Hawamda, Aya | |
| dc.contributor.author | Al-Haj, Waed | |
| dc.date.accessioned | 2019-07-22T09:47:25Z | |
| dc.date.available | 2019-07-22T09:47:25Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Nowadays, Real time human identification systems are important for security, surveillance and biometric applications. Usually it is desirable to detect, track and recognize persons in public areas such as airports, shopping centers, in areas with restricted access such as private offices, houses etc. Human identification can be performed by analyzing its biometric information, such as fingerprints, face, iris, Palm prints, palm veins etc. However, for fast and convenient person recognition, still the most suitable biometric parameter is facial information. And as the number of thefts and identity fraud has become a serious issue. There is a need for an efficient and cost effective face recognition system .The scope of this project is to develop a security access control application based on face recognition, such as an application that records the attendance and absence of employees in a company or an application that restricts access to certain high secret rooms in a company or bank. In order to achieve a higher accuracy and effectiveness we use Open CV libraries and python computer language. Training and identification is done in Raspberry Pi which itself is a minicomputer of a credit card size and is of a very low price. With the use of this kit, we aim at making the system cost effective and easy to use, with high performance. The results reveal that the proposed system can be used for face detection even from poor quality images and shows excellent performance efficiency. Depending on the time available, we will develop the project by adding more other human identification to increase the security and reduce the possibility of fraud on the system. | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.11888/14453 | |
| dc.language.iso | en_US | en_US |
| dc.title | Real Time Human Identification Systems “Face Recognition | en_US |
| dc.type | Graduation Project | en_US |
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