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CLC number: TP391.4

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Received: 2008-12-04

Revision Accepted: 2009-03-25

Crosschecked: 2009-03-25

Cited: 3

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Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.6 P.800-804

http://doi.org/10.1631/jzus.A0820842


Efficient page layout analysis on small devices


Author(s):  Eun-jung HAN, Chee-onn WONG, Kee-chul JUNG, Kyung-ho LEE, Eun-yi KIM

Affiliation(s):  Department of Naval Architecture and Ocean Engineering, Inha University, Incheon 402-751, Korea; more

Corresponding email(s):   hanej@inha.ac.kr, jungkeechul@gmail.com

Key Words:  Efficient page layout analysis, MLP-based segmentation, Mobile devices, Image segmentation, Neural network


Eun-jung HAN, Chee-onn WONG, Kee-chul JUNG, Kyung-ho LEE, Eun-yi KIM. Efficient page layout analysis on small devices[J]. Journal of Zhejiang University Science A, 2009, 10(6): 800-804.

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author="Eun-jung HAN, Chee-onn WONG, Kee-chul JUNG, Kyung-ho LEE, Eun-yi KIM",
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%T Efficient page layout analysis on small devices
%A Eun-jung HAN
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%A Kyung-ho LEE
%A Eun-yi KIM
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T1 - Efficient page layout analysis on small devices
A1 - Eun-jung HAN
A1 - Chee-onn WONG
A1 - Kee-chul JUNG
A1 - Kyung-ho LEE
A1 - Eun-yi KIM
J0 - Journal of Zhejiang University Science A
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EP - 804
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A0820842


Abstract: 
Previously we have designed and implemented new image browsing facilities to support effective offline image contents on mobile devices with limited capabilities: low bandwidth, small display, and slow processing. In this letter, we fulfill the automatic production of cartoon contents fitting small-screen display, and introduce a clustering method useful for various types of cartoon images as a prerequisite stage for preserving semantic meaning. The usage of neural networks is to properly cut the various forms of pages. Texture information that is useful for grayscale image segmentation gives us a good clue for page layout analysis using the multilayer perceptron (MLP) based x-y recursive algorithm. We also automatically frame the segment MLP using agglomerative segmentation. Our experimental results show that the combined approaches yield good results of segmentation for several cartoons.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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[2] Chen, Y., Ma, W.Y., Zhang, H.J., 2003. Detecting Web Page Structure for Adaptive Viewing on Small Form Factor Devices. Proc. 12th Int. WWW Conf., p.225-233.

[3] Etemad, K., Doermann, D.S., Chellappa, R., 1997. Multiscale segmentation of unstructured document pages using soft decision integration. IEEE Trans. Pattern Anal. Mach. Intell., 19(1):92-96.

[4] Jung, K.C., 2001. Neural network-based text location in color images. Pattern Recogn. Lett., 22(14):1503-1515.

[5] Karlson, A.K., Bederson, B.B., Giovanni, J.S., 2005. AppLens and LaunchTile: Two Designs for One-handed Thumb Use on Small Devices. Proc. SIGCHI Conf. on Human Factors in Computing Systems, p.201-210.

[6] Li, J., Gray, R.M., Olshen, R.A., 2000. Multiresolution image classification by hierarchical modeling with two-dimensional hidden Markov models. IEEE Trans. Inf. Theory, 46(5):1826-1841.

[7] Sung, K.K., Poggio, T., 1998. Example-based learning for view-based human face detection. IEEE Trans. Pattern Anal. Mach. Intell., 20(1):39-51.

[8] Wang, D., Srihari, S.N., 1989. Classification of newspaper image blocks using texture analysis. Comput. Vision Graph. Image Processing, 47(3):327-352.

[9] Yin, X., Lee, W.S., 2004. Using Link Analysis to Improve Layout on Mobile Devices. Proc. 13th Int. WWW Conf., p.338-344.

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