International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Thermal Face Recognition using Principal Component Analysis |
|---|---|
| ABSTRACT | This study proposes a method to improve face recognition performance by using thermal images along with Principal Component Analysis (PCA). In thermal-based recognition, infrared sensors record the unique heat patterns generated by the human face, allowing accurate identification even in darkness or visually challenging conditions. PCA is applied to reduce the dimensionality of these images, ensuring that essential facial information is retained while removing redundant data. The experimental results indicate that the approach remains effective under varying illumination, facial expressions, and head positions. Overall, the outcomes demonstrate that PCA can significantly enhance the reliability and security of thermal-image-based biometric systems. |
| AUTHOR | KOMAL GADEKAR, DR.S.N.KAKARWAL, VARSHA MALI |
| VOLUME | 176 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1311080 |
| pdf/80_Thermal Face Recognition using Principal.pdf | |
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