Abstract:
:Writer characterization from images of handwriting has remained an important research problem in the handwriting recognition community that finds applications in forensics, paleography and neuropsychology. This paper presents a study to evaluate the effectiveness of an implicit shape codebook technique to recognize writer from digitized images of handwriting. The technique relies on identifying the key points in handwriting and clustering the patches around these key points to generate an implicit shape codebook. A writer is then characterized by the probability distribution of producing the codebook patterns. Experiments are carried out in text-dependent as well text-independent mode using the standard BFL and CVL databases of handwriting images. Promising identification and verification performance is reported in a number of interesting experimental scenarios.
journal_name
Forensic Sci Intjournal_title
Forensic science internationalauthors
Bennour A,Djeddi C,Gattal A,Siddiqi I,Mekhaznia Tdoi
10.1016/j.forsciint.2019.05.014subject
Has Abstractpub_date
2019-08-01 00:00:00pages
91-100eissn
0379-0738issn
1872-6283pii
S0379-0738(18)31004-1journal_volume
301pub_type
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