A Comparative Study of Persian/Arabic Handwritten Character Recognition

被引：6

作者：

Alaei, Alireza ^{[1
]}

Pal, Umapada ^{[2
]}

Nagabhushan, P. ^{[1
]}

机构：

[1] Univ Mysore, Dept Studies Comp Sci, Mysore 570006, Karnataka, India

[2] Indian Stat Inst, Comp Vision & Pattern Recognit Unit, Kolkata 108, India

来源：

13TH INTERNATIONAL CONFERENCE ON FRONTIERS IN HANDWRITING RECOGNITION (ICFHR 2012) | 2012年

关键词：

Persian/Arabic Character Recognition; Handwriting Recognition; Under-sampled bitmaps; Chain Code; Gradient Features; Shadow Features;

D O I：

10.1109/ICFHR.2012.152

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In recent years, many techniques for the recognition of Persian/Arabic handwritten documents have been proposed by researchers. To test the promises of different features extraction and classification methods and to provide a new benchmark for future research, in this paper a comparative study of Persian/Arabic handwritten character recognition using different feature sets and classifiers is presented. Feature sets used in this study are computed based on gradient, directional chain code, shadow, under-sampled bitmap, intersection/junction/endpoint, and line-fitting information. Support Vector Machines (SVMs), Nearest Neighbour (NN), k-Nearest Neighbour (k-NN) are used as different classifiers. We evaluated the proposed systems on a standard dataset of Persian handwritten characters. Using 36682 samples for training, we tested the proposed recognition systems on other 15338 samples and their detailed results are reported. The best correct recognition of 96.91% is obtained in this comparative study.

引用

页码：123 / 128

页数：6

共 50 条

[21] Recognition of Arabic handwritten words using contextual character models
El-Hajj, Ramy
Mokbel, Chafic
Ukforman-Sulm, Laurence
DOCUMENT RECOGNITION AND RETRIEVAL XV, 2008, 6815
[22] A Survey on Arabic Optical Character Recognition and an Isolated Handwritten Arabic Character Recognition Algorithm using Encoded Freeman Chain Code
Althobaiti, Hassan
Lu, Chao
2017 51ST ANNUAL CONFERENCE ON INFORMATION SCIENCES AND SYSTEMS (CISS), 2017,
[23] Comparative Study of Part-Based Handwritten Character Recognition Methods
Song, Wang
Uchida, Seiichi
Liwicki, Marcus
11TH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR 2011), 2011, : 814 - 818
[24] Persian handwritten digit, character and word recognition using deep learning
Mahdi Bonyani
Simindokht Jahangard
Morteza Daneshmand
International Journal on Document Analysis and Recognition (IJDAR), 2021, 24 : 133 - 143
[25] Persian handwritten digit, character and word recognition using deep learning
Bonyani, Mahdi
Jahangard, Simindokht
Daneshmand, Morteza
INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION, 2021, 24 (1-2) : 133 - 143
[26] A New Approach to Feature Selection in Handwritten Farsi/Arabic Character Recognition
Shayegan, Mohammad Amin
Chan, Chee Seng
2012 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE APPLICATIONS AND TECHNOLOGIES (ACSAT), 2012, : 506 - 511
[27] Optical character recognition of handwritten Arabic using hidden Markov models
Aulama, Mohannad M.
Natsheh, Asem M.
Abandah, Gheith A.
Olama, Mohammed M.
OPTICAL PATTERN RECOGNITION XXII, 2011, 8055
[28] Optical Character Recognition of Arabic Handwritten Characters using Neural Network
Hussien, Rana S.
Elkhidir, Azza A.
Elnourani, Mohamed G.
2015 INTERNATIONAL CONFERENCE ON COMPUTING, CONTROL, NETWORKING, ELECTRONICS AND EMBEDDED SYSTEMS ENGINEERING (ICCNEEE), 2015, : 456 - 461
[29] Improving Handwritten Arabic Character Recognition by Modeling Human Handwriting Distortions
Shatnawi, Maad
Abdallah, Sherief
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 2016, 15 (01)
[30] Incorporating a new relational feature in Arabic online handwritten character recognition
Izadi, Sara
Suen, Ching Y.
VISAPP 2008: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 1, 2008, : 559 - 562

← 1 2 3 4 5 →