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

  title={Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)},
  author={Jamshed Memon and Maira Sami and Rizwan Ahmed Khan},
  journal={IEEE Access},
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… 

Handwritten and printed text separation for historical documents

To alleviate the problem of lack of data containing handwritten and machine-printed components located on the same page or even overlapping each other as well as their pixel-wise annotations, the data synthesis method proposed in [12] was applied and new datasets were generated.


This paper aims to classify an individual handwritten word so that handwritten text for English alphabets can be translated to a typed or editable form and used the Convolutional Neural Networks to accomplish this task.

Classification of Documents Extracted from Images with Optical Character Recognition Methods

Two different machine learning methods were combined to solve a real-world problem, the manuscript documents were first transferred to the computer and then classified, and three basic methods were used to realize the whole process.

Automated Marks Entry Processing in Handwritten Answer Scripts using Character Recognition Techniques

The educational system went online during the Covid-19 outbreak, which resulted in computerized test submissions, and the proposed system converts an image of a handwritten response sheet into a text document using an optical character recognition tool.

Handwriting Arabic Character Recognition Using Features Combination

This study proposed a method of new features extraction to recognize Arabic handwriting by grabbing the value of similar features among various types of font writing, to be used as a new feature of the font.

Implementation of OCR using Convolutional Neural Network (CNN): A Survey

This paper will go through the advantages and recent usage of CNN in OCR and why it’s important to use it in handwritten and printed text recognition and what subjects the authors can use this technique for.

Offline Handwritten MODI Character Recognition Using GoogLeNet and AlexNet

This paper focuses primarily on the performance evaluation of DCNN and their comparative study for MODI handwritten character recognition, and shows the effectiveness of deep learning approach on Handwritten MODI character recognition.

Online Handwritten Arabic Scripts Recognition Using Stroke-Based Class Labeling Scheme

A new method for online handwritten Arabic scripts recognition is set forward, departing from the assumption that handwritten scripts are encoded as a set of strokes, and relies first upon classifying strokes contained on the script and then recognizes the whole script.

Two Decades of Bengali Handwritten Digit Recognition: A Survey

The characteristics and inherent ambiguities of Bengali handwritten digits along with a comprehensive insight of two decades of state-of-the-art datasets and approaches towards offline BHDR have been analyzed and several real-life application-specific studies, which involve BH DR, have been discussed in detail.

A Data Entry Optical Character Recognition Tool using Convolutional Neural Networks

This conversation paints a rather complete picture of the current state of text recognition domain by laying down all of the possible issues that may arise during the OCR stages and examines OCR utilizing four different approaches.



A Novel Hybrid Optical Character Recognition Approach for Digitizing Text in Forms

This work proposes a new hybrid OCR approach recognizing handwritten and machine printed text based on neural networks in an integrated perspective and demonstrates the practical applicability of the approach using publicly available forms on which the approach could be successfully applied.

Offline Handwritten Character Recognition Techniques using Neural Network : A Review

This paper describes the techniques for converting textual content from a paper document into machine readable form and Selection of a relevant feature extraction method is probably the single most important factor in achieving high recognition performance with much better accuracy in character recognition systems.

An Unconstrained Benchmark Urdu Handwritten Sentence Database with Automatic Line Segmentation

A novel off-line sentence database of Urdu handwritten documents along with a few preprocessing and text line segmentation procedures are presented and announced.

A comprehensive survey of handwritten document benchmarks: structure, usage and evaluation

This paper is intended to provide a comprehensive survey of the handwriting databases developed during the last two decades and presents a comparison of these databases on a number of dimensions.

Recognition of Handwritten Arabic Characters using Histograms of Oriented Gradient (HOG)

Experimental results showed a great success of the recognition method compared to the state of the art techniques, where it could achieve very high recognition rates exceeding 99%.

Optical Character Recognition System for Nastalique Urdu-Like Script Languages Using Supervised Learning

There are two main techniques to convert written or printed text into digital format; one is to create an image of written/printed text, but images are large in size so they require...

Size Invariant Handwritten Character Recognition using Single Layer Feedforward Backpropagation Neural Networks

A recognition system based on neural network that follows offline handwritten characters has been proposed for Latin digits and alphabets and shows very encouraging results which are compared with the modern methods on this subject corridor.

Recognition of Tamil handwritten character using modified neural network with aid of elephant herding optimization

The proposed technique utilizes effective Tamil character recognition by means of optimal artificial neural network, which is used for recognizing the characters from scanned input digital image and converting them into machine editable form.

The optical character recognition of Urdu-like cursive scripts

On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey

The nature of handwritten language, how it is transduced into electronic data, and the basic concepts behind written language recognition algorithms are described.