Abstract
According to the growth of the mobile industry, a lot of on/off-line contents are being converted into mobile contents. Although the cartoon contents especially are one of the most popular mobile contents, it is difficult to provide users with the existing on/off-line contents without any considerations due to the small size of the mobile screen. In existing methods to overcome the problem, the cartoon contents on mobile devices are manually produced by computer software such as Photoshop. In this paper, we automatically produce the cartoon contents fitting for the small screen, and introduce a clustering method useful for variety types of cartoon images as a prerequisite stage for preserving semantic meaning. Texture information which is useful for gray-scale image segmentation gives us a good clue for semantic analysis and self-organizing feature maps (SOFM) is used to cluster similar texture information. Besides we automatically segment the clustered SOFM outputs using agglomerative clustering. In our experimental results, combined approaches show good results of clustering in several cartoons.
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References
Chen, Y., Ma, W.Y., Zhang, H.J.: Detecting Web Page Structure for Adaptive Viewing on Small Form Factor Devices. In: Proceedings of the International WWW Conference, Budapest, Hungary, ACM 1-58113-680-3/03/0005, pp. 225–233 (2003)
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. Wiley-Interscience, Chichester
Vesanto, J., Alhoniemi, E.: Clustering of the Self-Organizing Map. IEEE Transaction on Neural Networks 11(3), 586–600 (2000)
Kohonen, T.: Self-organizing Maps. Springer, Heidelberg (2001)
Aria, E.H., Saradjian, M.R., Amini, J., Lucas, C.: Generalized Concurrence Matrix to Classify IRS-1D Images using Neural Network. In: Proceedings of International Society for Photogrammetry and Remote Sensing, vol. 7, pp. 117–122 (2004)
Wu, S., Chow, T.W.S.: Clustering of the Self-organizing Map using a Clustering Validity index based on Inter-cluster and Intra-cluster Density. Pattern Recognition 37, 175–188 (2004)
Yin, X., Lee, W.S.: Using Link Analysis to Improve Layout on Mobile Devices. In: Proceedings of International World Wide Web Conference, pp. 338–344 (2004)
Karlson, A.K., Bederson, B.B., Giovanni, J.S.: AppLens and LaunchTile: Two Designs for One-Handed Thumb use on Small Devices. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI, pp. 201–210. ACM, New York (2005)
Lam, H., Baudisch, P.: Summary Thumbnails: Readable Overviews for Small Screen Web Browsers. In: Proceedings of CHI 2005, Portland, OR, pp. 681–690 (2005)
Sýkora, D., Buriánek, J., Žára, J.: Segmentation of Black-and-White Cartoons. In: Proceedings of Spring Conference on Computer Graphics, pp. 245–254 (2003)
Jain, A.K., Karu, K.: Learning Texture Discrimination Masks. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(2), 195–205 (1996)
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© 2006 Springer-Verlag Berlin Heidelberg
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Han, E., Park, A., Jung, K. (2006). Automatic Cartoon Image Re-authoring Using SOFM. In: Gunsel, B., Jain, A.K., Tekalp, A.M., Sankur, B. (eds) Multimedia Content Representation, Classification and Security. MRCS 2006. Lecture Notes in Computer Science, vol 4105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11848035_54
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DOI: https://doi.org/10.1007/11848035_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-39392-4
Online ISBN: 978-3-540-39393-1
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