• Data driven feature extraction for gender classification using multi-script handwritten texts 

      Moetesum M.; Siddiqi I.; Djeddi C.; Hannad Y.; Al-Maadeed S. ( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)
      This paper presents a study on assessing the effectiveness of machine learned features to predict gender of writers from images of handwriting. Pre-trained Convolutional Neural Networks have been employed as feature ...
    • ICFHR 2018 competition on multi-script writer identification 

      Djeddi C.; Al-Maadeed S.; Siddiqi I.; Abdeljalil G.; He S.; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)
      This paper describes the ICFHR 2018 Competition on Multi-script Writer Identification with details on the competition tasks, databases employed, submitted systems, evaluation protocol and the reported results. The competition ...
    • Influence of codebook patterns on writer recognition: An experimental study 

      Djeddi C.; Siddiqi I.; Gattal A.; Al-Maadeed, Somaya; Ennaji A. ( Blackwell Publishing Ltd , 2021 , Article)
      Codebook-based writer characterization is an effective technique that has been investigated in a number of recent studies on identification and verification of writers. These methods divide a set of writing samples into ...
    • Signature Verification for Offline Skilled Forgeries Using Textural Features 

      Djeddi, C.; Siddiqi, I.; Al-Maadeed, S.; Souici-Meslati, L.; Gattal, A.; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2016 , Conference Paper)
      This study explores the effectiveness of two texturalmeasurements on signature verification for skilled forgeries. These texture features include 2D autoregressive coefficients andrun-length distributions. Signature images ...
    • Writer identification on historical documents using oriented basic image features 

      Abdeljalil G.; Djeddi C.; Siddiqi I.; Al-Maadeed S. ( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)
      This study addresses the problem of identifying the authorship of historical manuscripts, a challenging task that offers interesting applications for document examiners and paleographers. We exploit handwriting texture as ...