Text-Independent Writer Identification and Verification Using Textural and Allographic Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Versatile search of scanned Arabic handwriting
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
Extraction and analysis of document examiner features from vector skeletons of grapheme ‘th'
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Feature representation selection based on Classifier Projection Space and Oracle analysis
Expert Systems with Applications: An International Journal
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The analysis of handwritten documents from the view-pointof determining their writership has great bearing onthe criminal justice system. In many cases, only a limitedamount of handwriting is available and sometimes it consistsof only numerals. Using a large number of handwrittennumeral images extracted from about 3000 samples writtenby 1000 writers, a study of the individuality of numerals foridentification/verification purposes was conducted. The individualityof numerals was studied using cluster analysis.Numerals discriminability was measured for writer verification.The study shows that some numerals present a higherdiscriminatory power and that their performances for theverification/identification tasks are very different.