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| dc.contributor.author | Almas Arshid, 01-134131-008 | |
| dc.date.accessioned | 2018-05-10T03:14:52Z | |
| dc.date.available | 2018-05-10T03:14:52Z | |
| dc.date.issued | 2017 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/6229 | |
| dc.description | Supervised by Ms. Mahwish Pervaiz | en_US |
| dc.description.abstract | This work discusses an on-going project for hands gesture recognition in computer vision systems. The proposed approach is based on the shape analysis. More specifically, the K nearest neighbour algorithm is used statistical estimation and pattern recognition of hand gestures based on contours. This project also facilitate to the deaf people they can be easily communicate with other peoples. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Bahria University Islamabad Campus | en_US |
| dc.relation.ispartofseries | BS (CS);P-01193 | |
| dc.subject | Computer Sciences. | en_US |
| dc.title | Hand Gesture Recognition | en_US |
| dc.type | Project Reports | en_US |
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BS (CS) (BUIC-FYP-E8) [1055]