Abstract
In this paper, we present a new iris detection method based on the use of watershed segmentation. The watershed transform is used for both pupil and iris detection, in combination with image quantization, aimed at reducing the number of gray levels, and image thresholding, aimed at obtaining a tentative discrimination between foreground and background. The method has been tested on the CASIA-Iris-Interval Image database.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Wildes, R.: Iris recognition: an emerging biometric technology. Proceedings of the IEEE 85(9), 1348–1363 (1997)
Daugman, J.G.: How iris recognition works. IEEE Trans. Circuits and Systems for Video Technology 14(1), 21–30 (2004)
Puhan, N.B., Sudha, N.: A novel iris database indexing method using the iris color. In: Proc. of the IEEE Conference on Industrial Electronics and Applications, pp. 1886–1891 (2008)
Special Issue on the Segmentation of visible wavelength iris images captured at-a-distance and on-the-move. Image and Vision Computing 28 (2010)
Special Issue on the Recognition of visible wavelength iris images captured at-a-distance and on-the-move. Pattern Recognition Letters 33 (2012)
http://www.idealtest.org/dbDetailForUser.do?id=4
Beucher, S., Lantuejoul, C.: Use of watersheds in contour detection. In: Proc. Int. Workshop on Image Processing, Real-Time Edge and Motion Detection/Estimation, France (1979)
Roerdink, J.B.T.M., Meijster, A.: The watershed transform: definitions, algorithms and parallelization strategies. Fundamenta Informaticae 41, 187–228 (2001)
Liao, P.-S., Chung, P.-C.: A fast algorithm for multilevel thresholding. Journal of Information Science and Engineering 17(5), 713–727 (2001)
Otsu, N.: A threshold selection method from gray-level histogram. IEEE Transactions on System Man Cybernetics 9(1), 62–66 (1979)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Ferone, A., Frucci, M., Petrosino, A., Sanniti di Baja, G. (2014). Iris Detection through Watershed Segmentation. In: Cantoni, V., Dimov, D., Tistarelli, M. (eds) Biometric Authentication. BIOMET 2014. Lecture Notes in Computer Science(), vol 8897. Springer, Cham. https://doi.org/10.1007/978-3-319-13386-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-13386-7_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13385-0
Online ISBN: 978-3-319-13386-7
eBook Packages: Computer ScienceComputer Science (R0)