Abstract book (pdf) - ICPR 2010

14:10-14:30, Paper WeBT6.3
Script Identification – a Han & Roman Script Perspective
Chanda, Sukalpa, GJØVIK Univ. Coll.
Pal, Umapada, Indian Statistical Inst.
Franke, Katrin, Gjøvik Univ. Coll.
Kimura, Fumitaka, Mie Univ.
All Han-based scripts (Chinese, Japanese, and Korean) possess similar visual characteristics. Hence system development
for identification of Chinese, Japanese and Korean scripts from a single document page is quite challenging. It is noted
that a Han-based document page might also have Roman script in them. A multi-script OCR system dealing with Chinese,
Japanese, Korean, and Roman scripts, demands identification of scripts before execution of respective OCR modules. We
propose a system to address this problem using directional features along with a Gaussian Kernel-based Support Vector
Machine. We got promising results of 98.39% script identification accuracy at character level and 99.85% at block level,
when no rejection was considered.
14:30-14:50, Paper WeBT6.4
Robust 1D Barcode Recognition on Mobile Devices
Rocholl, Johann, Stuttgart Univ.
Klenk, Sebastian, Stuttgart Univ.
Heidemann, Gunther, Stuttgart Univ.
In the following we will describe a novel method for decoding linear barcodes from blurry camera images. Our goal was
to develop a algorithm that can be used on mobile devices to recognize product numbers from EAN or UPC barcodes.
14:50-15:10, Paper WeBT6.5
Fast Logo Detection and Recognition in Document Images
Li, Zhe, Siemens AG
Schulte-Austum, Matthias, Siemens AG
Neschen, Martin, Recosys GmbH
The scientific significance of automatic logo detection and recognition is more and more growing because of the increasing
requirements of intelligent document image analysis and retrieval. In this paper, we introduce a system architecture which
is aiming at segmentation-free and layout-independent logo detection and recognition. Along with the unique logo feature
design, a novel way to ensure the geometrical relationships among the features, and different optimizations in the recognition
process, this system can achieve improvements concerning both the recognition performance and the running time.
The experimental results on several sets of real-word documents demonstrate the effectiveness of our approach.
WeBT7 Dolmabahçe Hall C
Classification in Biomedicine Regular Session
Session chair: Gurcan, Metin (Ohio State Univ.)
13:30-13:50, Paper WeBT7.1
Joint Independent Component Analysis of Brain Perfusion and Structural Magnetic Resonance Images in Dementia
Tosun, Duygu, Center for Imaging Neurodegenerative Diseases
Rosen, Howard, UCSF
Miller, Bruce L., UCSF
Weiner, Michael W., UCSF
Schuff, Norbert, UCSF
Magnetic Resonance Imaging (MRI) provides various imaging modes to study the brain. We tested the benefits of joint
analysis of multimodality MRI data using joint independent components analysis (jICA) in comparison to unimodality
analyses. Specifically, we designed a jICA to decompose the joint distributions of multimodality MRI data across image
voxels and subjects into independent components that explain joint variations between image modalities across subjects.
We applied jICA to structural and perfusion-weighted MRI data from 12 patients diagnosed with behavioral variant front
temporal dementia (bvFTD), a type of dementia, and 12 healthy elderly individuals. While unimodality analyses showed
widespread brain atrophy and hypoperfusion in the patients, jICA further revealed links between atrophy and hypoperfusion
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