Directional features in online handwriting recognition

PATTERN RECOGNITION

卷:39

Article

Bahlmann, C

关键词: feature selection;    directional data;    distribution on a circle;    multivariate semi-wrapped Gaussian distribution;    online handwriting recognition;    UNIPEN online handwriting database;   

DOI  :  10.1016/j.patcog.2005.05.012

来源: Elsevier

【 摘 要 】

The selection of valuable features is crucial in pattern recognition. In this paper we deal with the issue that part of features originate from directional instead of common linear data. Both for directional and linear data a theory for a statistical modeling exists. However, none of these theories gives an integrated solution to problems, where linear and directional variables are to be combined in a single, multivariate probability density function. We describe a general approach for a unified statistical modeling, given the constraint that variances of the circular variables are small. The method is practically evaluated in the context of our online handwriting recognition system frog on hand and the so-called tangent slope angle feature. Recognition results are compared with two alternative modeling approaches. The proposed solution gives significant improvements in recognition accuracy, computational speed and memory requirements. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

【 授权许可】

Free