Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)

By Jamshed Memon, Maira Sami, Rizwan Ahmed Khan. IEEE Access, 2020

434 citations recorded by the source corpus.

Given the ubiquity of handwritten documents in human transactions, Optical Character Recognition (OCR) of documents have invaluable practical worth. Optical character recognition is a science that enables to translate various types of documents or images into analyzable, editable and searchable data. During last decade, researchers have used artificial intelligence/machine learning tools to automatically analyze handwritten and printed documents in order to convert them into electronic format. The objective of this review paper is to summarize research that has been conducted on character recognition of handwritten documents and to provide research directions. In this Systematic Literature Review (SLR) we collected, synthesized and analyzed research articles on the topic of handwritten OCR (and closely related topics) which were published between year 2000 to 2019. We followed widely used electronic databases by following pre-defined review protocol. Articles were searched using keywords, forward reference searching and backward reference searching in order to search all the articles related to the topic. After carefully following study selection process 176 articles were selected for this SLR. This review article serves the purpose of presenting state of the art results and techniques on OCR and also provide research directions by highlighting research gaps.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/dfedc348fb9438370978525d8c4213d379936a89

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Furu Wei
2. Lei Cui
3. Tengchao Lv
4. Cha Zhang
5. Yijuan Lu
6. Florian Tramèr
7. Dinei A. F. Florêncio
8. Minghao Li

In Media Technology

1. Cha Zhang
2. Florian Tramèr
3. Reza Shokri

Citations in the corpus

• What Does it Mean for a Language Model to Preserve Privacy? (2022, background): “…language model tasks, which are the foundation of many of LM applications: part of speech (POS) tagging and parsing [25], optical character recognition (OCR) [65], automatic speech recognition [74], natural language generation [11], sentiment analysis [97], and natural language inference [9].”
• TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models (2021, background): “Handwritten Text Recognition (Memon et al. 2020) gave a systematic literature review about the modern methods for handwriting recognition.”
• VLP: A Survey on Vision-language Pre-training (2022, background): “Optical character recognition (OCR).[99, 100] OCR generally refers to extracting handwritten or printed text from images (such as street signs and photos of products) as well as documents (articles, bills, invoices, financial reports, etc.”