Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Locating the eye in human face images using fractal dimensions

Locating the eye in human face images using fractal dimensions

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Add to cart
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)
Add to cart

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IEE Proceedings - Vision, Image and Signal Processing — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

IEE
Published

Facial feature extraction is an important step in many applications such as human face recognition, video conferencing, surveillance systems, human computer interfacing etc. The eye is the most important facial feature. A reliable and fast method for locating the eye pairs in an image is vital to many practical applications. A new method for locating eye pairs based on valley field detection and measurement of fractal dimensions is proposed. Possible eye candidates in an image with a complex background are identified by valley field detection. The eye candidates are then grouped to form eye pairs if their local properties for eyes are satisfied. Two eyes are matched if they have similar roughness and orientation as represented by fractal dimensions. A modified approach to estimating fractal dimensions that is less sensitive to lighting conditions and provides information about the orientation of an image under consideration is proposed. Possible eye pairs are further verified by comparing the fractal dimensions of the eye-pair window and the corresponding face region with the respective means of the fractal dimensions of the eye-pair windows and the face regions. The means of the fractal dimensions are obtained based on a number of facial images in a database. Experiments have shown that this approach is fast and reliable.

Inspec keywords: fractals; feature extraction; face recognition

Other keywords: valley field detection; complex image; image orientation; face recognition; facial feature extraction; eye location; fractal dimensions; eye pairs; human face images; eye candidates

Subjects: Image recognition; Image recognition

References

    1. 1)
      • T. SATO , M. MATSUOKA , H. TAKAYASU . Fractal image analysis of natural scenes and medical images. Fractals , 4 , 463 - 468
    2. 2)
      • TANG, Y.Y., TAO, Y.: `Feature extraction by fractal dimension', Proceedings of 5th international conference on Document analysis and recognition (ICDAR '99), 1999, p. 217–220.
    3. 3)
      • S.H. JENG , H.Y.M. LIAO , C.C. HAN , M.Y. CHERN , Y.T. LIU . Facial feature detection using geometrical face model: an efficient approach. Pattern Recognit. , 3 , 273 - 282
    4. 4)
      • K. SOBOTTKA , I. PITAS . A novel method for automatic face segmentation facial feature extraction and tracking. Signal Process., Image Commun. , 263 - 280
    5. 5)
      • YANG, G., HUANG, T.S.: `Human face detection in a scene', Proceedings of conference on Computer vision and pattern recognition (CVPR'93), 1993, p. 453–458.
    6. 6)
      • N. Sarkar , B.B. Chaudhuri . An efficient differential box-counting approach to compute fractal dimension of image. IEEE Trans. Syst. Man Cybern. , 1 , 115 - 120
    7. 7)
      • G.C. FENG , P.C. YUEN . Variance projection function and its application to eye detection for human face recognition. Pattern Recognit. Lett. , 899 - 906
    8. 8)
      • HARA, F., TANAKA, K., KOBAYASHI, H., TANGE, A.: `Automatic feature extraction of facial organs and contour', Proceedings of 6th IEEE international workshop on Robot and human communication (RO-MAN'97), 1997, p. 386–389.
    9. 9)
      • LAM, K.M., YAN, H.: `An improved method for locating and extracting the eye in human face images', Proceedings of IEEE international conference on Pattern recognition, 1996, p. 411–415.
    10. 10)
      • LAM, K.M.: `A fast approach for detecting human faces in a complex background', Proceedings of IEEE international symposium on Circuits and systems (ISCAS '98), 1998, 4, p. 85–88.
    11. 11)
      • FENG, J., LIN, W.C., CHEN, C.T.: `Fractional box-counting approach to fractal dimension estimation', Proceedings of 13th international conference on Pattern recognition, 1996, 2, p. 854–858.
    12. 12)
      • W.K. Pratt . (1978) , Digital image processing.
    13. 13)
      • P. Maragos . Tutorial on advances in morphological image processing and analysis. Opt. Eng. , 7 , 623 - 632
    14. 14)
      • K.M. LAM , H. YAN . Locating and extracting the eye in human face images. Pattern Recognit. , 5 , 771 - 779
    15. 15)
      • P.J. SAUPE , M.P. YUNKER . Fractals for the classrooms, Strategic activities.
    16. 16)
      • CHAN, K.L.: `Fractal based texture analysis', Proceedings of communications on the move conference (ICCS/ISITA '92), 1990, Singapore, 1, p. 102–106.
http://iet.metastore.ingenta.com/content/journals/10.1049/ip-vis_20010709
Loading

Related content

content/journals/10.1049/ip-vis_20010709
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address