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Automatic Quantitative Letter-level Extraction of Features Used by Document Examiners |
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Editor(s): HL Teulings & AWA Van Gemmert |
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Tempe, United States of America |
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| Abstract |
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In this paper we examine tile automatic extraction of visual or structural features as used by document examiners in the comparison of handwriting samples. We have extracted between 7 and 14 different features from four letters ("y", "d", "f" and "t"). This analysis was earned out on a total of 3077 letters from 30 different writers. On average these features are extracted with about 88% accuracy and can be used to assess the similarity of different writing samples. |
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Proceedings of the 11th Conference of the International Graphonomics Society (IGS 2003), p. 291-294 |
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