| Autor: |
Km Priyanka Singh, Dr. Pushpneel Verma, Ajay Singh |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
International Journal for Research in Applied Science and Engineering Technology. 10:1435-1438 |
| ISSN: |
2321-9653 |
| DOI: |
10.22214/ijraset.2022.46847 |
| Popis: |
Face detection is one in every of the foremost relevent application of image processing and biometric system. Artificial neural networks (ANN) are utilized in the sphere of image processing and pattern recognition. For the recognition and detection of spoofed and non-spoofed images, face spoof approach was proposed. Earlier presented support vector machine classification model is used for the detection of spoofed or non-spoofed images. within the earlier research, SVM based approach was proposed to detect the face spoof. The face spoof detection approaches involves two stages. The initial stage includes feature extraction and second stage includes classification. The features are extracted using Eigen based system. The classification is performed through SVM classifier. within the proposed approach, the KNN classifier is used in place of SVM classifier for improving the accuracy of the face spoof discovery. The performance of the proposed algorithm and also the earlier algorithm is analyzed through some comparisons among them in terms of precision and execution time. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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