Name
Abstract | ||
|---|---|---|
Face recognition technology is an application technology of information security, which is a kind of multi-disciplinary technology, such as comprehensive mathematics, pattern recognition, and biological characteristics. With the development of technology applications, the requirements for accuracy and anti-counterfeiting of face recognition are also increasing. In this paper, the K-mean algorithm is used to analyze the face features. Firstly, the biometric features of the face are extracted, and then the K-mean method is used to cluster the face features. Lastly, the SVM method is used to classify. The results show that the K-mean method can achieve high recognition performance with fewer feature numbers. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s13640-018-0313-7 | EURASIP Journal on Image and Video Processing |
Keywords | Field | DocType |
Face recognition,K-mean,Support vector machine (SVM) | k-means clustering,Computer vision,Facial recognition system,Pattern recognition,Computer science,Support vector machine,Algorithm,Information security,Feature extraction,Artificial intelligence,Biometrics | Journal |
Volume | Issue | ISSN |
2018 | 1 | 1687-5281 |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pengcheng Wei | 1 | 22 | 8.72 |
| Zhen Zhou | 2 | 30 | 12.87 |
| Li Li | 3 | 0 | 0.68 |
| Jiao Jiang | 4 | 0 | 0.68 |