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المؤلفAl-Maadeed,Somaya
المؤلفFerjani F.
المؤلفElloumi S.
المؤلفHassaine A.
المؤلفJaoua A.
تاريخ الإتاحة2022-05-19T10:23:15Z
تاريخ النشر2013
اسم المنشور2013 7th IEEE GCC Conference and Exhibition, GCC 2013
المصدرScopus
المعرّفhttp://dx.doi.org/10.1109/IEEEGCC.2013.6705761
معرّف المصادر الموحدhttp://hdl.handle.net/10576/31159
الملخصIn forensics, the handedness detection or the classification of writers into left or right-handed helps investigators focusing more on a certain category of suspects. However, only a few studies have been carried out in this field. Classification of handwriting into a demographic category is generally performed in two steps: feature extraction and classification. In this study, we propose a system which extract characterizing features from handwritings and use those features to perform the classification of handwritings with regards to handedness. Classification rates are reported on the QUWI dataset, reaching almost 70% for Left and right Handwriting.
اللغةen
الناشرIEEE
الموضوعCategory Classification
Chain codes
Directional feature
Handwriting analysis
Writer identification
Character recognition
Exhibitions
Feature extraction
Population statistics
Classification (of information)
العنوانAutomatic handedness detection from off-line handwriting
النوعConference Paper
الصفحات119-124


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