Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지
DOI QR코드

DOI QR Code

Face classification and analysis based on geometrical feature of face

얼굴의 기하학적 특징정보 기반의 얼굴 특징자 분류 및 해석 시스템

  • Received : 2012.02.22
  • Accepted : 2012.03.23
  • Published : 2012.07.31
Download PDF
⟨ Previous Next ⟩

Abstract

This paper proposes an algorithm to classify and analyze facial features such as eyebrow, eye, mouth and chin based on the geometric features of the face. As a preprocessing process to classify and analyze the facial features, the algorithm extracts the facial features such as eyebrow, eye, nose, mouth and chin. From the extracted facial features, it detects the shape and form information and the ratio of distance between the features and formulated them to evaluation functions to classify 12 eyebrows types, 3 eyes types, 9 mouth types and 4 chine types. Using these facial features, it analyzes a face. The face analysis algorithm contains the information about pixel distribution and gradient of each feature. In other words, the algorithm analyzes a face by comparing such information about the features.

본 논문에서는 얼굴의 기하학적 특징정보를 기반으로 하여 얼굴의 특징자인 눈썹, 눈, 입, 턱선의 분류 및 해석 알고리즘을 제안하였다. 먼저, 얼굴 특징정보의 분류와 해석을 하기위한 전처리 과정으로 얼굴 특징자들의 눈, 코, 입, 눈썹, 턱선을 추출하기위해 얼굴 특징자 추출 알고리즘을 적용하여 얼굴 특징자들을 추출하게 된다. 추출한 얼굴 특징자들의 형태 정보와 모양정보 및 특징자들 간의 거리비율을 검출하여 이를 평가함수화 하고, 3가지의 눈 타입, 9가지의 입 타입, 12가지의 눈썹 타입 그리고 4가지의 턱선 타입의 분류를 하게 된다. 이렇게 분류된 얼굴 특징자들을 이용하여 얼굴을 해석하게 된다. 얼굴해석 알고리즘은 각각의 특징자들에 대한 고유의 특징자들의 내부구간의 화소분포 정보와 기울기 정보를 가지고 있다. 따라서 특징자들 간의 정보를 이용하여 얼굴을 해석할 수 있었다.

Keywords

References

  1. H. P. Graf, T. Chen, E. Petajan, and E. Cosatto. "Locating faces and facial parts." In International Workshop on Face Gesture Recognition, pp. 41-46, Zurich, 1995.
  2. Peter L. Hallinan, Gaile G. Gordon, A. L. Yuille Peter Giblin and David Mumford ,"Two-and Three-Dimensional Patterns of the Face", pp. 201-216, 1999.
  3. Aysegul Gunduz and Hamid Krim, "Facial Feature Extraction Using Topological Methods", IEEE Proc. International Conference On Image Processing, vol. 3-2, pp. 909-912, 2003.
  4. Jung Hoon Kim, Kyeong Hoon Do, Eung Joo Lee, "Automatic Face Identification System Using Adaptive Face Region Detection and Facial Feature Vector Classification", ITC-CSCC02, July 16-19, 2002.
  5. Juan Jose de Dios and Narciso Grcia, "Face Detection Based on A New Color Space YCgCr", Proc. IEEE Conf. International Conference On Image Processing, vol. 3-2, pp. 909-912, 2003.
  6. M. H. Yang, N.Ahuja, "Detecting Human Facein Color Images", Proc, of the int, Conference on Image Processing (ICIP'98), pp. 632-636. 1998.
  7. Stan Birchfield, "Elliptical Head Tracking Using Intensity Gradients and Color Histogram," CVPR, 1998.
  8. Nicolas EVENO, Alice CAPLIER, Pierre-yves COULON, "Jumping Snakes and Parametric Model for Lip Segmentation", Proc. IEEE Conf. International Conference On Image Processing, vol. 3-2, pp. 909-912, 2003.
  9. E. J. Lee,"Face Recognition System Using Color and Geometric Feature Analysis," Joun'l. of I.S.P.S, vol. 1, no.2, pp.42-49, 2000.
  10. Brian Scassellati, "Eye Finding via Face Detection for a Foveated, Active Vision System," In Proceedings of the American Association of artificial Intelligence, 1998.
  11. Chun-Hung Lin and Ja-Ling Wu. "Automatic Facial Feature Extraction by Generic algorithms", IEEE Trans. Image Processing, Vol. 8, NO.6, pp. 834-845, June 1999. https://doi.org/10.1109/83.766860
  12. Q. R. Chen, W.K. Cham and H. T. Tsui, "A Method for Estimating and Accurately Extracting the Eyebrow in Human Face Image", Proc. IEEE Conf. International Conference On Image Processing, vol. 3/2, pp. 793-796, 2002.

Cited by

  1. Face Classification Using Cascade Facial Detection and Convolutional Neural Network vol.26, pp.1, 2016, https://doi.org/10.5391/JKIIS.2016.26.1.070
  2. 고차원 국부이진패턴과 결합베이시안 알고리즘을 이용한 얼굴인증 임베디드 시스템 구현 vol.21, pp.9, 2017, https://doi.org/10.6109/jkiice.2017.21.9.1674