Abstract
Model-based coding is a new data compression scheme for very low bit rate image transmission. It consists of image analysis, parameter transmission, and image synthesis, in which edge detection based facial feature estimation is probably one of the most essential process. As many of the existing edge detection methods are not able to produce a satisfying and efficient result for this specific coding application, we are proposing herewith a new wavelet -based facial edge detection approach. Our approach applies the coarse-to-fine strategy using discrete wavelet transform for distinct facial edge feature detection, and extract the local modulus maxima of a continuous wavelet transform as the edge candidates by choosing a suitable continuous wavelet. In terms of speed and quality of the output when used for model-based coding, experiments show, our method outperforms many of the existing edge detection approaches, such as Prewitt's method, Canny's method, Marr-Hildreth's method, etc. It makes full use of the multiresolution properties of wavelet transform and can be used in conjunction with other methods for extremely low bit rate transmission of videophone pictures.
This research was supported by Hong Kong Telecom Institute of Information Technology under grant HKTIIT93/94.EG02
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Prewitt, J.M.S., “Object Enhancement and Extraction. In Picture Processing and Psychopictorics,” B.S. Lipkin and A. Rosenfeld (Eds.), New York: Academic Press, 1970.
Haralick, R.M., stermberg, S.R., and Zhuang, X., “Image Analysis Using Mathematical Morphology,” IEEE Trans. PAMI, Vol. 9, pp. 532–550, 1987.
Canny, J, “A Computational Approach to Edge Detection,” IEEE Trans. PAMI, Vol.8, pp. 679–698, 1986.
D. Marr and E. Hildreth, “Theory of Edge Detection,” Proc. R. Soc.Lond. B, Vol. 207, pp.187–217, 1980.
Roberts, L.G, “Machine Perception of Three-Dimensional Solids,” In Optical and Electro-Optical Information Processing, J.P. Tippett et al. (Eds.), Cambridge, MA: MIT Press, 1965.
Atkinson, J, Campbell F.W, “The Effect of Phase on the Perception of Compound Gratings. Vision Res,” Vol. 14, pp. 159–162, 1974.
Voorhees, H. and T. Poggio, “Detecting Textons and Texture Boundaries in Natural Images,” Proc. First. Internat. Conf. on Computer Vision, London, England, pp. 250–258, June 1987.
Liu Jian Feng, Qi Fei Hu, “A Wavelet Transform Approach to Image Edge Detection and Denoising,” ICNNSP'95, to be held in Nan Jing.
Liu Jian Feng, Qi Fei Hu, “A Wavelet Transform Approach to Image Spacial Filtering,” Journal of Shanghai Jiao Tong University, Vol. 6, 1995 (to be published).
Pearson, D. E., “Developments in Model-Based Video Coding,” Proceedings of the IEEE. Vol.83, No. 6, pp. 892–906, 1995.
M. Vetterli and C. Herley, “Wavelets and Filter Banks: Theory and Design,” IEEE Trans. SP, Vol. 40, pp. 2207–2232, Sept. 1992.
S.G. Mallat, “A Theory for Multiresolution Signal Decomposition: The Wavelet Transform,” IEEE Trans. PAMI, Vol. 11, No. 7, pp. 674–693, 1989.
Barrow, H.G., Tenenbaum, J.M., Bolles, R.C., and Wolf, H.C., “Parametric Correspondence and Chamfer Matching: Two New Techniques for Image Matching,” Proc. 5th Int. Joint Conf. on Artificial Intelligence, Cambridge, DSA, pp. 659–663, 1977.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1996 Springer-Verlag London Limited
About this paper
Cite this paper
Liu, JF., Lee, J.CM. (1996). An efficient wavelet-based facial edge detection approach in model-based coding. In: Berger, MO., Deriche, R., Herlin, I., Jaffré, J., Morel, JM. (eds) ICAOS '96. Lecture Notes in Control and Information Sciences, vol 219. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-76076-8_147
Download citation
DOI: https://doi.org/10.1007/3-540-76076-8_147
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76076-4
Online ISBN: 978-3-540-40945-8
eBook Packages: Springer Book Archive