A Comparative Evaluation of Dotted Raster-Stereography and Feature-Based Techniques for Automated Face Recognition
| Autor: | Syed Faisal Ali, Fauzan Saeed, S. Talha Ahsan, Muhammad Wasim, Lubaid Ahmed |
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| Rok vydání: | 2018 |
| Předmět: |
General Computer Science
business.industry Computer science Volume (computing) Pattern recognition 02 engineering and technology computer.file_format Facial recognition system Domain (software engineering) Comparative evaluation 0202 electrical engineering electronic engineering information engineering Feature (machine learning) Feature based 020201 artificial intelligence & image processing Artificial intelligence Sensitivity (control systems) Raster graphics business computer |
| Zdroj: | International Journal of Advanced Computer Science and Applications. 9 |
| ISSN: | 2156-5570 2158-107X |
| DOI: | 10.14569/ijacsa.2018.090640 |
| Popis: | Automated face recognition systems are fast becoming a need for security-related applications. Development of a fool-proof and efficient face recognition system is a challenging domain for researchers. This paper presents comparative evaluation of two candidate techniques for automated face recognition application, viz. dotted Raster-stereography and feature-based system. The relevant performance parameters — accuracy, precision, sensitivity and specificity – measured for the two techniques using IPRL Database of images are reported. The results suggest that dotted Raster-stereography based face recognition system has better accuracy, precision, sensitivity and specificity, and hence is a preferred choice as compared with feature-based system for such sensitive applications where high face recognition accuracy is required. On the other hand, feature-based technique is faster in terms of the training and testing times required. Hence such applications where volume of face recognition work is large and high speed is required with some compromise in accuracy being acceptable then feature-based technique may also be the technique of choice. |
| Databáze: | OpenAIRE |
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