Abstract
Face detection in complex background are vulnerable to light or other factors. This paper presents one face positioning algorithm based on the gradient direction. Firstly, smoothly preprocess the original image, then get the enhanced edge of grayscale image using sobel operator, binaries image, and finally set the position at the horizontal and vertical level with the characteristics of gradient direction of the binarized image. Experiments show that the algorithm for face recognition in complex background and positioning is fast and efficient. It also has the same effect on multiple face images of people.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Li, Q., Yin, J., Li, J.: Gray Face Detection Based on Grads Information. Journal of University of Jinan (Science and Technology) 21(4), 341–344 (2007)
Liu, Z., Gao, G., Yu, L.: One Fast and Effective Method of Facial Features Localization. Application Research of Computers 17(12), 19–20 (2000)
Shi, Y., Cai, Z.: Face Datecting Based on Grads Couple Featrue of Eyes. Computer Engineering and Application 26, 27–30 (2005)
Li, S., Xiong, H., et al.: Robust Face Detection In Complex Background. Mini-Micro Systems 21(7), 719–721 (2000)
Juell, P., Marsh, R.: A hierarchical neural network for human face detection. Pattern Recognition 29(5), 781–787 (1996)
Yu, Y., Yan, Y.: Algorithm Study of Face Detection and Location in Video Sequence. Computer Technology and Development (2), 33–38 (2009)
Lan, Z., Cao, J., Liang, S.: Face positioning Algorithm in Video Sequences with Complex Background. Computer Science 35(6), 42–48 (2008)
Yan, J.: Digital Image Processing (MATLAB Printing), pp. 32–56. Academic Press, Beijing (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag GmbH Berlin Heidelberg
About this paper
Cite this paper
Yunjuan, L., Hongyu, F., Lijun, Z., Qinglin, M. (2012). Gradient Direction Based Human Face Positioning Algorithm Applied in Complex Background. In: Kim, H. (eds) Advances in Technology and Management. Advances in Intelligent and Soft Computing, vol 165. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29637-6_49
Download citation
DOI: https://doi.org/10.1007/978-3-642-29637-6_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29636-9
Online ISBN: 978-3-642-29637-6
eBook Packages: EngineeringEngineering (R0)