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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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Citations:  Bibtex RefMan EndNote GB/T7714

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


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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A1 - Chee-onn WONG
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DOI - 10.1631/jzus.A0820842

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


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