A Survey on Arabic Handwritten Character Recognition

被引：0
|
作者：
Ali A.A.A. [1 ,2 ]
Suresha M. [2 ]
Ahmed H.A.M. [3 ]
机构：
[1] Taiz University, Taiz
[2] Kuvempu University, Shimoga
[3] Thissufal, Ibb
来源：
SN Computer Science | 2020年 / 1卷 / 3期
关键词：
Artificial neural network; Character recognition of Arabic handwritten; Freeman chain code; Fuzzy systems; Genetic algorithms; Hidden Markov model; Neural network; Support vector machine;
D O I：
10.1007/s42979-020-00168-1
中图分类号：
学科分类号：
摘要：
There are much heavy studies on handwritten character recognition (HCR) for nearly previous four decades. The research on some of the common script like Arabic, Indian and Chinese has been done. This manuscript presents a survey of character recognition on Arabic script, and most of the popular published paper methods are summarized and also analyzed different methods for building a robust system of HCR and included some future research on recognition direction of handwritten character. The paper analyzed and presented various algorithms with respect to preprocessing methods, segmentation methods, feature extraction methods and various classification approaches of the Arabic character recognition. © 2020, Springer Nature Singapore Pte Ltd.
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