A review on existing learning techniques applied in solving optical character recognition problem. (10th June 2021)

• Record Type: Journal Article
• Authors: Sonthi, Vijaya Krishna; Nagarajan, S.; Krishnaraj, N.
• Is Part Of: International journal of innovative computing and applications. Volume 12:Number 4(2021)
• Page Start: 183
• Page End: 188
• Publication Date: 2021-06-10
• Subjects: machine learning -- deep learning -- optical character recognition -- pattern recognition -- image processing; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

Optical character recognition is treated as the classical problem in image processing that can be widely used for application areas related to computer vision. This process is highly dependent on the languages, as well as various formats of information like hand written/printed/sculptured documents as input. The chief operations that can be performed while handling this task are training the system and predicting the characters based on the trained knowledge. Conventionally, classification and regression mechanisms are used for this purpose. Due to the recent advents in technological progress, the same mechanism was served with the help of modern machine learning and deep learning concepts. The main agenda of this paper is to create awareness among the researchers by discussing existing mechanisms related to solve optical character recognition using various machine learning and deep learning concepts.