Abstract book (pdf) - ICPR 2010

13:30-16:30, Paper ThBCT8.43
Local Binary Pattern-Based Features for Text Identification of Web Images
Jung, Insook, Chonbuk National Univ.
Oh, Il-Seok, Chonbuk National Univ.
We present a method of robustly identifying a text block in complex web images. The method is a MLP (Multi-layer perceptron)
classifier trained on LBP (Local binary patterns), wavelet and shape feature spaces. Especially, we propose adaptive
masks of LBP which responses flexibly to various character sizes. Most of previous works use fixed mask size or
multi level scales by pyramid schemes, which may have weakness in dealing with diverse size of text. Experiments carried
out on 100 web images show promising results.
13:30-16:30, Paper ThBCT8.44
Classification of Polarimetric SAR Images using Evolutionary RBF Neural Networks
Turker, Ince, Izmir Univ. of Ec.
Kiranyaz, Serkan, Tampere Univ. of Tech.
Moncef, Gabbouj, Tampere Univ. of Tech.
This paper proposes an evolutionary RBF network classifier for polar metric synthetic aperture radar ( SAR) images. The
proposed feature extraction process utilizes the full covariance matrix, the gray level co-occurrence matrix (GLCM) based
texture features, and the backscattering power (Span) combined with the H/α/A decomposition, which are projected
onto a lower dimensional feature space using principal component analysis. An experimental study is performed using
the fully polar metric San Francisco Bay data set acquired by the NASA/Jet Propulsion Laboratory Airborne SAR (AIR-
SAR) at L-band to evaluate the performance of the proposed classifier. Classification results (in terms of confusion matrix,
overall accuracy and classification map) compared to the Wish art and a recent NN-based classifiers demonstrate the effectiveness
of the proposed algorithm.
13:30-16:30, Paper ThBCT8.45
On the Use of Median String for Multi-Source Translation
González Rubio, Jesús, Univ. Pol. de Valencia
Casacuberta, Francisco, Univ. Pol. de Valencia
State-of-the-art approaches to multi-source translation involve a multimodal-like process which applies an individual
translation system to each source language. Then, the translations of the individual systems are combined to obtain a consensus
output. We propose to use the (generalised) median string as the consensus output of the individual translation systems.
Different approximations to the median string are studied as well as different approaches to improve the median
string performance when dealing with natural language strings. The proposed approaches were evaluated on the Europarl
corpus, achieving significant improvements in translation quality.
13:30-16:30, Paper ThBCT8.47
A Lip Contour Extraction Method using Localized Active Contour Model with Automatic Parameter Selection
Liu, Xin, Hong Kong Baptist Univ.
Cheung, Yiu-Ming, Hong Kong Baptist Univ.
Li, Meng, Hong Kong Baptist Univ.
Liu, Hailin, Guangdong Univ. of Technology
Lip contour extraction is crucial to the success of a lipreading system. This paper presents a lip contour extraction algorithm
using localized active contour model with the automatic selection of proper parameters. The proposed approach utilizes a
minimum-bounding ellipse as the initial evolving curve to split the local neighborhoods into the local interior region and
the local exterior region, respectively, and then compute the localized energy for evolving and extracting. This method is
robust against the uneven illumination, rotation, deformation, and the effects of teeth and tongue. Experiments show its
promising result in comparison with the existing methods.
13:30-16:30, Paper ThBCT8.48
Multimodal Sleeping Posture Classification
Huang, Weimin, I2R
Phyo Wai, Aung Aung, Inst. for Infocomm Res.
Foo, Siang Fook, Inst. for Infocomm Res.
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