Abstract
In this paper we propose a new technique for outlines of objects detection. We exploit the set of contours computed using the image analogies principle. A set of artificial patterns are used to locate contours of any query image, each one permits the location of contours corresponding to a specific intensity variation. We studied these contours and a theoretical foundation is proposed to explain the slow motion of these contours around regions boundaries. Experiments are conducted and the obtained results are presented and discussed.
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
Alpert, S., Galun, M., Basri, R., Brandt, A.: Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (June 2007)
Ashikhmin, M.: Fast texture transfer. IEEE Computer Graphics and Applications 23(4), 38–43 (2003)
Alpert, S., Galun, M., Basri, R., Brandt, A.: Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration, In. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2007)
Arbelaez, P., Maire, M., Fowlkes, C., Malik, J.: Contour Detection and Hierarchical Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 33(5), 898–916 (2011)
Cheng, H.D., Jiang, X.H., Sun, Y., Wang, J.L.: Color image segmentation: advances and prospects. Pattern Recognition 34, 2259–2281 (2001)
Cheng, L., Vishwanathan, S.V.N., Zhang, X.: Consistent image analogies using semi-supervised learning. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008 (2008)
De Winter, J., Wagemans, J.: Segmentation of object outlines into parts: A large-scale integrative study. Cognition 99, 275–325 (2006)
Freeman, W.T., Pasztor, E.C., Carmichael, O.T.: Learning Low-Level Vision. International Journal of Computer Vision 40(1) (2000)
Hertzmann, A., Jacobs, C.E., Oliver, N., Curless, B., Seitz, S.M.: Image analogies. In: SIGGRAPH Conference Proceedings, pp. 327–340 (2001)
Hertzmann, A., Oliver, N., Curless, B., Seitz, S.M.: Curve analogies. In: Proc. 13th Eurographics Workshop on Rendering, Pisa, Italy, pp. 233–245 (2002)
Lackey, J.B., Colagrosso, M.D.: Supervised segmentation of visible human data with image analogies. In: Proceedings of the International Conference on Machine Learning; Models, Technologies and Applications (2004)
Larabi, S., Robertson, N.M.: Contour detection by image analogies. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Fowlkes, C., Wang, S., Choi, M.-H., Mantler, S., Schulze, J., Acevedo, D., Mueller, K., Papka, M. (eds.) ISVC 2012, Part II. LNCS, vol. 7432, pp. 430–439. Springer, Heidelberg (2012)
Martin, D., Fowlkes, C., Tal, D., Malik, J.: A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics. In: Proc. 8th Int’l Conf. Computer Vision (2001)
Sykora, D., Burianek, J., Zara, J.: Unsupervised colorization of black-and-white cartoons. In: Proceedings of the 3rd Int. Symp. Non-photorealistic Animation and Rendering, pp. 121–127 (2004)
Wang, G., Wong, T., Heng, P.: Deringing cartoons by image analogies. ACM Transactions on Graphics 25(4), 1360–1379 (2006)
Zhanga, H., Frittsb, J.E., Goldmana, S.A.: Image segmentation evaluation: A survey of unsupervised methods. Computer Vision and Image Understanding 110(2), 260–280 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bellili, A., Larabi, S., Robertson, N.M. (2013). Outlines of Objects Detection by Analogy. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8047. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40261-6_46
Download citation
DOI: https://doi.org/10.1007/978-3-642-40261-6_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40260-9
Online ISBN: 978-3-642-40261-6
eBook Packages: Computer ScienceComputer Science (R0)