Hybrid Facial Features with Application in Person Identification

Authors

  • Boonchana Purahong Department of Computer Engineering, Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand
  • Vanvisa Chutchavong Department of Computer Engineering, Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand
  • Hisayuki Aoyama Department of Mechanical and Intelligent Systems Engineering, University of Electro-Communications, Japan
  • Chuchart Pintavirooj Departmet of Biomedical Engineering, Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand

DOI:

https://doi.org/10.13052/jmm1550-4646.161212

Keywords:

Geometric invariance, person identification, face identification, hybrid facial feature, facial image.

Abstract

This paper presents the hybrid facial feature with identification and verification based on facial images. A query facial image had been taken under different conditions of the facial image of the same person (as the query). The query facial image database was constructed. We have used the technique of three-dimensional (3D) Dlib facial landmarks using a direct linear transform technique. A set of absolute affine invariance had been constructed from a series of the 3D landmark quadruplets, which make the facial identification robust to affine geometric transformation. These 3D facial features serve as a coarse feature depending on each individual facial structure. The construct of the 2D detail features represents the edge facial image confined between the 2D Dlib landmarks. The similarity of the 2D feature is achieved by aligning the 2D query edge image against that of the reference edge image. The geometric transformation matrix is estimated from the 2D Dlib landmarks, where correspondence is well established. An identification/verification cost function using a combination of local 2D facial features and global 3D facial features is utilized to verify and identify a query facial image against a candidate facial image(s). The performance of the algorithm yielding an area of 99.97% perfect classification is represented as a value under the receiver operating characteristic (ROC) curve.  

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Author Biographies

Boonchana Purahong, Department of Computer Engineering, Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand

Boonchana Purahong received his M.Eng. degree in information engineering from the King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand. He has joined the department of computer engineering, faculty of engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand. He is currently an associate professor and interested in pattern recognition and image processing.

Vanvisa Chutchavong, Department of Computer Engineering, Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand

Vanvisa Chutchavong received her Ph.D. degree in electrical engineering from the King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand. She has joined the department of computer engineering, faculty of engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand. She is currently an associate professor and interested in the filter circuit.

Hisayuki Aoyama, Department of Mechanical and Intelligent Systems Engineering, University of Electro-Communications, Japan

Hisayuki Aoyama received his Ph.D. degree in informatics and engineering from the Tokyo Institute of Technology, Tokyo, Japan. Currently, he is working as a professor in the Department of Mechanical Engineering and Intelligent Systems, Graduate School of Informatics and Engineering. He is interested in micro/precision engineering and micrometrology as well as its industrial and biomedical applications.

Chuchart Pintavirooj, Departmet of Biomedical Engineering, Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Thailand

Chuchart Pintavirooj received his B.Sc. and M.Sc. degrees from the Mahidol University, Bangkok, Thailand in 1985 and 1989, respectively. In 1995, he received another master’s degree in biomedical engineering from the Worcester Polytechnic Institute, MA, USA. In 2000, he earned a Ph.D. degree in biomedical engineering from the Drexel University, Philadelphia, USA. He joined the Department of Biomedical Engineering, Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand. He is currently an associate professor. His research interests include image reconstruction, image classification, and image restoration.

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http://dlib.net/

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Published

2020-08-24

How to Cite

Purahong, B., Chutchavong, V., Aoyama, H., & Pintavirooj, C. (2020). Hybrid Facial Features with Application in Person Identification. Journal of Mobile Multimedia, 16(1-2), 245–266. https://doi.org/10.13052/jmm1550-4646.161212

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Section

Smart Innovative Technology for Future Industry and Multimedia Applications

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