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| dc.contributor.author | Najam Ul Islam, 01-235181-044 | |
| dc.contributor.author | Mohsin Khan, 01-235181-027 | |
| dc.date.accessioned | 2022-06-21T07:20:46Z | |
| dc.date.available | 2022-06-21T07:20:46Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/12861 | |
| dc.description | Supervised by Ms. Zubaria Inayat | en_US |
| dc.description.abstract | Due to increasing number of theft crimes more and more people are concerned regarding their safety. We have seen huge trends of using safety cameras to ensure the safety and security. However, many times we’ve observed the culprits could not be caught even if the record/footages available and the authorities remain unable to identify the criminals. In cases when the criminals do get identified the process takes too much time which allows the culprits to flee the country. Face Recognition & Criminal Identification (FRCI) can be used to identify the credentials of the person in front of the camera in real-time. FRCI uses the Haar Cascade Classifier for face detection and Principal Component Analysis (PCA) for face recognition. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Computer Sciences BUIC | en_US |
| dc.relation.ispartofseries | BS (IT);MFN-P 10482 | |
| dc.subject | Criminal Identification | en_US |
| dc.subject | Principal Component Analysis | en_US |
| dc.title | Face Recognition & Criminal Identification (FRCI) | en_US |
| dc.type | Project Reports | en_US |
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BS-IT (IC-FYP) [127]