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ICDAR
2011
IEEE

Offline Writer Identification Using K-Adjacent Segments

8 years 6 months ago
Offline Writer Identification Using K-Adjacent Segments
— This paper presents a method for performing offline writer identification by using K-adjacent segment (KAS) features in a bag-of-features framework to model a user’s handwriting. This approach achieves a top 1 recognition rate of 93% on the benchmark IAM English handwriting dataset, which outperforms current state of the art features. Results further demonstrate that identification performance improves as the number of training samples increase, and additionally, that the performance of the KAS features extend to Arabic handwriting found in the MADCAT dataset. Writer Identification; Handwriting; Codebook; Local Features; Document Forensics; K-Adjacent Segments
Rajiv Jain, David S. Doermann
Added 24 Dec 2011
Updated 24 Dec 2011
Type Journal
Year 2011
Where ICDAR
Authors Rajiv Jain, David S. Doermann
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