Abstract
This paper proposes a novel image retrieval system called MOSIR, developed for mobile phones. This system enables the user to find similar images and information related to the photos taken with the user’s mobile phone at any time. It overcomes the problem originating from small display panels and limited control keys. Similar images are then retrieved by extracting edge-based and color-layout features. Region-based queries are also processed by detecting salient regions and extracting their features. The system uses both self-defined e-mail and web application software to provide flexible image searching, and it overcomes security problems. A new user interface is designed in Flash Lite to display the results in different sizes and contexts. The method provides satisfactory results. This mobile system proved to be useful for finding images and semantically connected information while the user was on the move.
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.
References
Kutics, A., Nakagawa, A., Shindoh, K.: Use of Adaptive Still Image Descriptors for Annotation of Video Frames. In: Kamel, M.S., Campilho, A. (eds.) ICIAR 2007. LNCS, vol. 4633, pp. 686–697. Springer, Heidelberg (2007)
Kutics, A., Nakagawa, A.: Naming of Image Regions for User-Friendly Image Retrieval. In: Campilho, A., Kamel, M.S. (eds.) ICIAR 2006. LNCS, vol. 4141, pp. 612–623. Springer, Heidelberg (2006)
Naito, M., Hoashi, K., Matsumoto, K., Shishibori, M., Kita, K., Kutics, A., Nakagawa, A., Sugaya, F., Nakajima, Y.: High-Level Feature Extraction Experiments for TRECVID 2007. In: TRECVID 2007, NIST (2007)
Wang, F., Lu, W., Liu, J., Shah, M., Xu, D.: Automatic Video Annotation with Adaptive Number of Key Words. In: IEEE International Conference on Pattern Recognition (ICPR), pp. 1–4 (2008)
Barnard, K., Duygulu, P., Forsyth, D., de Freitas, N., Blei, D.M., Jordan, M.I.: Matching Words and Pictures. ACM Journal of Machine Learning Research 3, 1107–1135 (2003)
Abe, T., Takada, T., Kawamura, H., Yasuno, T., Sonehara, N.: Image-Identification Methods for Camera-Equipped Mobile Phones. In: IEEE International Conference on Mobile Data Management, pp. 372–376 (2007)
Hub, A., Blank, D., Henrich, A., Muller, W.: Picadomo: Faceted Image Browsing for Mobile Devices. In: IEEE International Workshop on Content-Based Multimedia Indexing, pp. 249–254 (2009)
He, R., Liu, K., Xiong, N., Zhu, Y.: Garment Image Retrieval on the Web with Ubiquitous Camera-Phone. In: IEEE Asia-Pacific Services Computing Conference, pp. 1584–1589 (2008)
Zhou, Y., Fan, X., Xie, X., Gong, Y., Ma, W.: Inquiring of the Sights from the Web via Camera Mobiles. In: IEEE International Conference on Multimedia and Expo., pp. 661–664 (2006)
Hare, J.S., Lewis, P.H.: Content-based image retrieval using a mobile device as a novel interface. In: SPIE Storage and Retrieval Methods and Applications for Multimedia, San Jose, California, USA, vol. 5682, pp. 64–75 (2005)
Kiranyaz, S., Caglar, K., Guldogan, O., Karaoglu, E.: MUVIS: A Multimedia Browsing, Indexing and Retrieval Framework. In: Proceedings of Third International Workshop on Content Based Multimedia Indexing CBMI 2003, Rennes, France, pp. 22–24 (September 2003)
Guldogan, O., Gabbouj, M.: Content-based image indexing and retrieval framework on symbian based mobile platform. In: Proceedings of European Signal Processing Conference, EUSIPCO 2005 (2005)
Kutics, A., Nakagawa, A.: Detecting Prominent Objects for Image Retrieval. In: IEEE International Conference on Image Processing (ICIP), Part 3, pp. 445–448 (2005)
Manjunath, B.S., Ohm, J., Vasudevan, V.V., Yamada, A.: Color and Texture Descriptors. IEEE Transactions on Circuits and Systems for Video Technology 11(6), 703–715 (2001)
Kasutani, E., Yamada, A.: The MPEG-7 color layout descriptor: a compact image feature description for high-speed image/video segment retrieval. In: Proceedings of International Conference on Image Processing, vol. 1, pp. 674–677 (2001)
Canny, J.: A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8, 679–698 (1986)
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
Nakagawa, A., Kutics, A., Phyu, K.H., Sato, H., Furukawa, T., Koiduka, K. (2010). MOSIR: Image and Segment-Based Retrieval for Mobile Phones. In: Qiu, G., Lam, K.M., Kiya, H., Xue, XY., Kuo, CC.J., Lew, M.S. (eds) Advances in Multimedia Information Processing - PCM 2010. PCM 2010. Lecture Notes in Computer Science, vol 6298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15696-0_48
Download citation
DOI: https://doi.org/10.1007/978-3-642-15696-0_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15695-3
Online ISBN: 978-3-642-15696-0
eBook Packages: Computer ScienceComputer Science (R0)