Abstract
Alpha matting refers to the problem of softly extracting the foreground from an image.To solve the matting problem initialized with a trimap (a partition of the image into three regions: foreground, background and unknown pixels), an approach based on artificial immune network is proposed in this paper.The method firstly uses Artificial Immune Network(aiNet) to map the color feature for unknown region, attaining the color subset both on the foreground and background color distributions,then estimate the alpha matte for unknown region, and finally apply guided filter to improve the matting results. Experiments on several different image data sets show that the proposed method produces high-quality matting results.
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.
Similar content being viewed by others
References
Porter, T., Duff, T.: Compositing digital images. In: 11th Annual Conference on Computer Graphics and Interactive Techniques, pp. 253–259. ACM Press, New York (1984)
Jue, W., Cohen, M.F.: Image and Video Matting: A Survey. Computer Graphics and Vision 3 (2007)
Ruzon, M.A., Tomasi, C.: Alpha estimation in natural images. In: Computer Vision and Pattern Recognition, pp. 18–25. IEEE Press, New York (2000)
Chuang, Y., Curless, B., Salesin, D., Szeliski, R.: A bayesian approach to digital matting. In: Computer Vision and Pattern Recognition, pp. 264–271. IEEE Press, New York (2001)
Rhemann, C., Rother, C., Gelautz, M.: Improving color modeling for alpha matting. In: BMVC (2008)
Wang, J., Cohen, M.: Optimized color sampling for robust matting. In: Computer Vision and Pattern Recognition, pp. 1–8. IEEE Press, New York (2007)
Gastal, E.S.L., Oliveira, M.M.: Shared sampling for real-time alpha matting. Computer Graphics Forum, 575–584 (2010)
Bai, X., Sapiro, G.: A geodesic framework for fast interactive image and video segmentation and matting. In: 10th IEEE International Conference on Computer Vision, pp. 1–8. IEEE Press, New York (2007)
Rother, C., Kolmogorov, V., Blake, A.: Grabcut - interactive foreground extraction using iterated graph cut. In: Proceedings of ACM SIGGRAPH, pp. 309–314. ACM Press, New York (2004)
Sun, J., Jia, J., Tang, C.K., Shum, H.Y.: Poisson matting. In: Proceedings of ACM SIGGRAPH, pp. 315–321. ACM Press, New York (2004)
Zheng, Y., Kambhamettu, C., Yu, J., Bauer, T., Steiner, K.: Fuzzymatte:A computationally efficient scheme for interactive matting. In: Computer Vision and Pattern Recognition, pp. 1–8. IEEE Press, New York (2008)
Levin, A., Lischinski, D., Weiss, Y.: A closed form solution to natural image matting. In: Pattern Analysis and Machine Intelligence, pp. 228–242. IEEE Press, New York (2008)
Levin, A., Ravacha, A., Lischinski, D.: Spectral matting. In: Computer Vision and Pattern Recognition, pp. 1–8. IEEE Press, New York (2007)
Wang, J., Cohen, M.: Optimized color sampling for robust matting. In: Computer Vision and Pattern Recognition, pp. 1–8. IEEE Press, New York (2007)
He, K., Sun, J., Tang, X.: Guided Image Filtering. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6311, pp. 1–14. Springer, Heidelberg (2010)
Hart, E., Timmis, J.: Application areas of AIS: the past, the present and the future. Applied Soft Computing, 191–201 (2008)
Castro, L.N., Timmis, J.I.: Artificial immune systems as a novel soft computing paradigm. Soft Computing, 526–544 (2003)
Ge, H., Yan, X.: A Modified Artificial Immune Network for Feature Extracting. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds.) ICSI 2011, Part I. LNCS, vol. 6728, pp. 408–415. Springer, Heidelberg (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hao, Z., Liu, J., Yan, X., Wen, W., Cai, R. (2012). Alpha Matting Using Artificial Immune Network. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30976-2_36
Download citation
DOI: https://doi.org/10.1007/978-3-642-30976-2_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30975-5
Online ISBN: 978-3-642-30976-2
eBook Packages: Computer ScienceComputer Science (R0)