Character and numeral recognition for non-Indic and Indic scripts: a survey

被引:46
|
作者
Kumar, Munish [1 ]
Jindal, M. K. [2 ]
Sharma, R. K. [3 ]
Jindal, Simpel Rani [4 ]
机构
[1] GZS Campus Coll Engn & Technol, Dept Comp Applicat, Bathinda, Punjab, India
[2] Panjab Univ, Reg Ctr, Dept Comp Sci & Applicat, Muktsar, Punjab, India
[3] Thapar Univ, Dept Comp Sci & Engn, Patiala, Punjab, India
[4] Yadavindra Coll Engn, Comp Sci & Engn, Bathinda, Punjab, India
关键词
OCR; Character recognition; Non-Indic scripts; Indic scripts; JAPANESE TEXT RECOGNITION; HANDWRITING RECOGNITION; ONLINE; OCR; SEGMENTATION; EXTRACTION; FUSION; BANGLA; SYSTEM;
D O I
10.1007/s10462-017-9607-x
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A collection of different scripts is employed in writing languages throughout the world. Character and numeral recognition of a particular script is a key area in the field of pattern recognition. In this paper, we have presented a comprehensive survey on character and numeral recognition of non-Indic and Indic scripts. Many researchers have done work on character and numeral recognition from the most recent couple of years. In perspective of this, few strategies for character/numeral have been developed so far. There are an immense number of frameworks available for printed and handwritten character recognition for non-Indic scripts. But, only a limited number of systems are offered for character/numeral recognition of Indic scripts. However, few endeavors have been made on the recognition of Bangla, Devanagari, Gurmukhi, Kannada, Oriya and Tamil scripts. In this paper, we have additionally examined major challenges/issues for character/numeral recognition. The efforts in two directions (non-Indic and Indic scripts) are reflected in this paper. When compared with non-Indic scripts, the research on character recognition of Indic scripts has not achieved that perfection yet. The techniques used for recognition of non-Indic scripts may be used for recognition of Indic scripts (printed/handwritten text) and vice versa to improve the recognition rates. It is also noticed that the research in this field is quietly thin and still more research is to be done, particularly in the case of handwritten Indic scripts documents.
引用
收藏
页码:2235 / 2261
页数:27
相关论文
共 50 条
  • [32] Handwritten Word Spotting in Indic Scripts using Foreground and Background Information
    Das, Ayan
    Bhunia, Ayan Kumar
    Roy, Partha Pratim
    Pal, Umapada
    PROCEEDINGS 3RD IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION ACPR 2015, 2015, : 426 - 430
  • [33] Scene text recognition: an Indic perspectiveScene text recognition: an Indic perspectiveV. P. Vijayan et al.
    Vasanthan P. Vijayan
    Sukalpa Chanda
    David Doermann
    Narayanan C. Krishnan
    International Journal on Document Analysis and Recognition (IJDAR), 2025, 28 (1): : 31 - 40
  • [34] Handwritten Indic scripts recognition using neuro-evolutionary adaptive PSO based convolutional neural networks
    Sharma, Reya
    Kaushik, Baijnath
    SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES, 2022, 47 (01):
  • [35] Handwritten Indic scripts recognition using neuro-evolutionary adaptive PSO based convolutional neural networks
    Reya Sharma
    Baijnath Kaushik
    Sādhanā, 2022, 47
  • [36] A Thresholded Gabor-CNN Based Writer Identification System for Indic Scripts
    Mridha, M. F.
    Ohi, Abu Quwsar
    Shin, Jungpil
    Kabir, Muhammad Mohsin
    Monowar, Muhammad Mostafa
    Hamid, Md. Abdul
    IEEE ACCESS, 2021, 9 : 132329 - 132341
  • [37] A SURVEY OF EARLY MIDDLE INDIC - GERMAN - HINUBER,OV
    WRIGHT, JC
    JOURNAL OF THE ROYAL ASIATIC SOCIETY, 1987, (02): : 349 - 349
  • [38] HMM-Based Lexicon-Driven and Lexicon-Free Word Recognition for Online Handwritten Indic Scripts
    Bharath, A.
    Madhvanath, Sriganesh
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2012, 34 (04) : 670 - 682
  • [39] Indic script family and its offline handwriting recognition for characters/digits and words: a comprehensive survey
    Sukhdeep Singh
    Anuj Sharma
    Vinod Kumar Chauhan
    Artificial Intelligence Review, 2023, 56 : 3003 - 3055
  • [40] Generation of synthetic training data for handwritten Indic script recognition
    Gaur, Shivansh
    Sonkar, Siddhant
    Roy, Partha Pratim
    2015 13TH IAPR INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR), 2015, : 491 - 495