Face Recognition Based on Improved SIFT Algorithm
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 1
Abstract
People are usually identified by their faces. Developments in the past few decades have enabled human to automatically do the identification process.Now, face recognition process employs the advanced statistical science and matching methods. Improvements and innovations in face recognition technology during 10 to 15 past years have propelled it to the current status. Due to the wide application of face recognition algorithms in many practical systems, including security control systems, human–computer interaction systems, etc., algorithms with high success rate are highly interested in research areas in recent years.Most of suggested algorithms are about correctly identifying face photos and assigning them to a person in the database. This study focuses on face recognition based on improved SIFT algorithm. Results indicate the superiority of the proposed algorithm over the SIFT.To evaluate the proposed algorithm, it is applied on ORL database and then compared to other face detection algorithms including Gabor, GPCA, GLDA, LBP, GLDP, KGWRCM, and SIFT. The results obtained from various tests show that the proposed algorithm reveals accuracy of 98.75% and run time of 4.3 seconds which is shorter. The new improved algorithm is more efficient and more accurate than other algorithms.
Authors and Affiliations
EHSAN SADEGHIPOUR, NASROLLAH SAHRAGARD
Keywords
Related Articles
- EP ID EP148942
- DOI 10.14569/IJACSA.2016.070175
- Views 117
- Downloads 0
The Examination of Using Business Intelligence Systems by Enterprises in Hungary
Data are one of the key elements in corporate decision-making, without them, the decision-making process cannot be imagined. As a consequence, different analytical tools are needed that allow the efficient use of data, i...
Mortality Prediction based on Imbalanced New Born and Perinatal Period Data
This study was carried out by the New York State Department of Health, between 2012 and 2016. This experiment relates to six supervised machine learning methods: Support Vector Machine (SVM), Logistic Regression (LR), Gr...
Medical Image Inpainting with RBF Interpolation Technique
Inpainting is a method for repairing damaged images or to remove unwanted parts of an image. While this process has been performed by professional artists in the past, today, the use of this technology is emerging in the...
E-learning in Higher Educational Institutions in Kuwait: Experiences and Challenges
E-learning as an organizational activity started in the developed countries, and as such, the adoption models and experiences in the developed countries are taken as a benchmark in the literature. This paper investigated...
RSECM: Robust Search Engine using Context-based Mining for Educational Big Data
With an accelerating growth in the educational sector along with the aid of ICT and cloud-based services, there is a consistent rise of educational big data, where storage and processing become the prime matter of challe...