Face Recognition using SVM with the Help of Kernel Characteristics Function
This project focuses on building a face recognition system using the Labeled Faces in the Wild (LFW) dataset.The dataset includes diverse facial images of individuals across various age groups, such as kids, women, men, and the elderly. The model employs a Support Vector Machine (SVM) with a radial...
Saved in:
| Published in | International journal for research in applied science and engineering technology Vol. 11; no. 12; pp. 793 - 797 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
31.12.2023
|
| Online Access | Get full text |
| ISSN | 2321-9653 2321-9653 |
| DOI | 10.22214/ijraset.2023.57436 |
Cover
| Summary: | This project focuses on building a face recognition system using the Labeled Faces in the Wild (LFW) dataset.The dataset includes diverse facial images of individuals across various age groups, such as kids, women, men, and the elderly. The model employs a Support Vector Machine (SVM) with a radial basis function (RBF) kernel for effective classification. Preprocessing techniques like normalization, grayscale conversion, and face alignment enhance the dataset's quality. The system's performance is assessed using accuracy, precision, recall metrics, and a Receiver Operating Characteristic (ROC) curve. The project aims to create a reliable and versatile face recognition solution applicable in security, authentication, and surveillance scenarios |
|---|---|
| ISSN: | 2321-9653 2321-9653 |
| DOI: | 10.22214/ijraset.2023.57436 |