Biometric personal identification based on handwriting

In this paper, we describe a new method to identify the writer of Chinese handwritten documents. There are many methods for signature verification or writer identification, but most of them require segmentation or connected component analysis. They are content dependent identification methods, as si...

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Bibliographic Details
Main Authors: Yong Zhu, Tieniu Tan, Yunhong Wang
Format: Conference Proceeding
Language:English
Subjects:
Automation
Biometrics
Feature extraction
Filtering
Flowcharts
Gabor filters
Handwriting recognition
Image segmentation
Laboratories
Pattern recognition
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Description
Summary:In this paper, we describe a new method to identify the writer of Chinese handwritten documents. There are many methods for signature verification or writer identification, but most of them require segmentation or connected component analysis. They are content dependent identification methods, as signature verification requires the writer to write the same text (e.g. his name). In our new method, we take the handwriting as an image containing some special texture, and writer identification is regarded as texture identification. This is a content independent method. We apply the well-established 2D Gabor filtering technique to extract features of such textures and a weighted Euclidean distance classifier to fulfil the identification task. Experiments are made using Chinese handwritings from 17 different people and very promising results were achieved.
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2000.906196