Development of an efficient neural-based segmentation technique for Arabic handwriting recognition

Pattern Recognition

Volumn 43, Issue 8, 2010, Pages 2773-2798

  Al Hamad, Husam A ^a   Abu Zitar, Raed ^b  

^a QASSIM UNIVERSITY   (Saudi Arabia)

^b NEW YORK INSTITUTE OF TECHNOLOGY   (Jordan)

Author keywords

Arabic; Handwritten; Segmentation

Indexed keywords

ARABIC HANDWRITING; ARABIC SCRIPTS; BENCHMARK DATABASE; CHARACTER CLASSIFICATION; CONFIDENCE VALUES; CPU TIME; FEATURE DETECTION; FEATURE EXTRACTION TECHNIQUES; FEATURE-BASED; FUSION EQUATIONS; HAND-WRITTEN CHARACTERS; HANDWRITING RECOGNITION; HANDWRITING SEGMENTATION; HANDWRITTEN WORDS; MODIFIED DIRECTION FEATURES; OPEN PROBLEMS; SEGMENTATION ACCURACY; SEGMENTATION TECHNIQUES;

BACKPROPAGATION ALGORITHMS; FEATURE EXTRACTION; FEEDFORWARD NEURAL NETWORKS; RESEARCH;

CHARACTER RECOGNITION;

EID: 77951257543     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2010.03.005     Document Type: Article

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