Abstract
We present a fuzzy multiscale segmentation algorithm aimed at hand images acquired by a mobile device, for biometric purposes. This algorithm is quasi-linear with the size of the image and introduces a stopping criterion that takes into account the texture of the regions and controls the level of coarsening. The algorithm yields promising results in terms of accuracy segmentation, having been compared to other well-known methods. Furthermore, its procedure is suitable for a posterior mobile implementation.
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
Li, Y., Xu, X.: Revolutionary Information System Application in Biometrics. In: International Conference on Networking and Digital Society, ICNDS 2009, May 30-31, vol. 1, pp. 297–300 (2009)
Fong, L.L., Seng, W.C.: A Comparison Study on Hand Recognition Approaches. In: International Conference of Soft Computing and Pattern Recognition, SOCPAR 2009, December 4-7, pp. 364–368 (2009)
Shirakawa, S., Nagao, T.: Evolutionary image segmentation based on multiobjective clustering. In: IEEE Congress on Evolutionary Computation, CEC 2009, May 18-21, pp. 2466–2473 (2009)
Kang, W.-X., Yang, Q.-Q., Liang, R.-P.: The Comparative Research on Image Segmentation Algorithms. In: First International Workshop on Education Technology and Computer Science, ETCS 2009, March 7-8, vol. 2, pp. 703–707 (2009)
Sharon, E., Galun, M., Sharon, D., Basri, R., Brandt, A.: Hierarchy and adaptivity in segmenting visual scenes. Macmillan Publishing Ltd., Basingstoke (2006)
Son, T.T., Mita, S., Takeuchi, A.: Road detection using segmentation by weighted aggregation based on visual information and a posteriori probability of road regions. In: IEEE International Conference on Systems, Man and Cybernetics, SMC 2008, October 12-15, pp. 3018–3025 (2008)
Sharon, E., Brandt, A., Basri, R.: Fast multiscale image segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition, Proceedings, vol. 1, pp. 70–77 (2000)
Sharon, E., Brandt, A., Basri, R.: Segmentation and boundary detection using multiscale intensity measurements. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol. 1, pp. I-469 – I-476 (2001)
Rory Tait Neilson, B.N., McDonald, S.: Image segmentation by weighted aggregation with gradient orientation histograms. In: Southern African Telecommunication Networks and Applications Conference, SATNAC (2007)
Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient graph-based image segmentation. Int. J. Computer Vision 59, 167–181 (2004)
Alpert, S., Galun, M., Basri, R., Brandt, A.: Image segmentation by probabilistic bottom-up aggregation and cue integration. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007, pp. 1–8 (June 2007)
Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 888–905 (2000)
Comaniciu, D., Meer, P., Member, S.: Mean shift: A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 603–619 (2002)
Dyer, R., Zhang, H., Möller, T.: Delaunay mesh construction. In: Proceedings of the Fifth Eurographics Symposium on Geometry Processing, SGP 2007, Aire-la-Ville, Switzerland, pp. 273–282. Eurographics Association (2007)
Vassili, V.V., Sazonov, V., Andreeva, A.: A survey on pixel-based skin color detection techniques. In: Proc. Graphicon 2003, pp. 85–92 (2003)
Hunter, R.S.: Photoelectric Color-Difference Meter. Proceedings of the Winter Meeting of the Optical Society of America, JOSA 38(7), 661 (1948)
de Berg, M., van Kreveld, M., Overmars, M., Schwarzkopf, O.: Computational Geometry: Algorithms and Applications, 3rd edn., Springer, Heidelberg (April 2008)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Addison-Wesley Longman Publishing Co., Inc., Boston (1992)
Meirav, G., Eitan, S., Basri, R., Brandt, A.: Texture segmentation by multiscale aggregation of filter responses and shape elements. In: Proceedings of the Ninth IEEE International Conference on Computer Vision, ICCV 2003, Washington, DC, USA, p. 716. IEEE Computer Society, Los Alamitos (2003)
Xiao, Q., Zhang, N., Gao, S., Li, F., Gao, Y.: Segmentation based on shape prior and graph model optimization. In: 2nd International Conference on Advanced Computer Control (ICACC), March 27-29, vol. 3, pp. 405–408 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
García-Casarrubios Muñoz, Á., Sánchez Ávila, C., de Santos Sierra, A., Guerra Casanova, J. (2010). A Mobile-Oriented Hand Segmentation Algorithm Based on Fuzzy Multiscale Aggregation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17289-2_46
Download citation
DOI: https://doi.org/10.1007/978-3-642-17289-2_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17288-5
Online ISBN: 978-3-642-17289-2
eBook Packages: Computer ScienceComputer Science (R0)