Abstract book (pdf) - ICPR 2010

opportunities in literary analyses of Ottoman poetry where the majority of it is in handwritten form. In this study, we propose
a matching criterion and method, Red if Extraction using Contour Segments (RECS) using the proposed matching criterion,
that detects redifs in handwritten Ottoman literary texts using only visual analysis. Our method provides a success rate of
0.682 in a test collection of 100 poems.
13:30-16:30,Paper TuBCT9.24
Analysis of Local Features for Handwritten Character Recognition
Uchida, Seiichi, Kyushu Univ.
Liwicki, Marcus, DFKI
This paper investigates a part-based recognition method of handwritten digits. In the proposed method, the global structure
of digit patterns is discarded by representing each pattern by just a set of local feature vectors. The method is then comprised
of two steps. First, each of J local feature vectors of a target pattern is recognized into one of ten categories (``0’’—``9’’) by
the nearest neighbor discrimination with a large database of reference vectors. Second, the category of the target pattern is
determined by the majority voting on the J local recognition results. Despite a pessimistic expectation, we have reached
recognition rates much higher than 90% for the task of digit recognition.
13:30-16:30,Paper TuBCT9.25
Detect Visual Spoofing in Unicode-Based Text
Qiu, Bite, City Univ. of Hong Kong
Fang, Ning, City Univ. of Hong Kong
Liu, Wenyin, City U of HK
Visual spoofing in Unicode-based text is anticipated as a severe web security problem in the near future as more and more
Unicode-based web documents will be used. In this paper, to detect whether a suspicious Unicode character in a word is
visual spoofing or not, the context of the suspicious character is utilized by employing a Bayesian framework. Specifically,
two contexts are taken into consideration: simple context and general context. Simple context of a suspicious character is
the word where the character exists while general context consists of all homoglyphs of the character within Universal Character
Set (UCS). Three decision rules are designed and used jointly for convicting a suspicious character. Preliminary evaluations
and user study show that the proposed approach can detect Unicode-based visual spoofing with high effectiveness
and efficiency.
13:30-16:30,Paper TuBCT9.26
Comparing Several Techniques for Offline Recognition of Printed Mathematical Symbols
Álvaro, Francisco, Inst. Tecnológico de Informática
Sánchez, Joan Andreu, Univ. Pol. De Valencia
Automatic recognition of printed mathematical symbols is a fundamental problem for recognition of mathematical expressions.
Several classification techniques has been previously used, but there are very few works that compare different classification
techniques on the same database and with the same experimental conditions. In this work we have tested classical
and novelty classification techniques for mathematical symbol recognition on two databases.
13:30-16:30,Paper TuBCT9.27
Symbol Classification using Dynamic Aligned Shape Descriptor
Fornés, Alicia Computer Vision Center
Escalera, Sergio UB
Llados, Josep Computer Vision Center
Valveny, Ernest Univ. Autònoma de Barcelona
Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps
or noise. In this paper, we propose a new descriptor and distance computation for coping with the problem of symbol recognition
in the domain of Graphical Document Image Analysis. The proposed D-Shape descriptor encodes the arrangement information
of object parts in a circular structure, allowing different levels of distortion. The classification is performed using
a cyclic Dynamic Time Warping based method, allowing distortions and rotation. The methodology has been validated on
different data sets, showing very high recognition rates.
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