Machine learning & image processing for hand written digits and alphabets recognition from document image through MATLAB simulation

Autor:	Jainath Yadav, Satrughan Kumar Singh
Rok vydání:	2021
Předmět:	Soft computing Computer science business.industry Image processing Machine learning computer.software_genre Image (mathematics) Numeral system Pattern recognition (psychology) Matlab programming Matlab simulation Artificial intelligence Alphabet business computer
Zdroj:	IOP Conference Series: Materials Science and Engineering. 1084:012021
ISSN:	1757-899X 1757-8981
Popis:	Machine learning is currently playing a vital role in the next generation of the computer world. Automatic pattern recognition has become an important issue of image processing and machine learning. Handwritten digits and alphabets are not arranged in the same size, thickness, position and right direction. Therefore, to determine the issue of handwritten numerals and alphabet recognition, different classifications and complexity should be analyzed. The composition styles of different individuals affect mainly the patterns of alphabets and digits. An effective strategy is to understand the numbers and alphabets transferred from a document image and to make an orderly pattern. In this research work, a soft computing system has been developed using the MATLAB programming. This system uses machine learning algorithms that identify patterns by computerized estimation by identifying handwritten digits and alphabets from a document image. From the experimental results, we observed 96.24% average recognition accuracy of our proposed system.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ec3c0b6a925f25b29a5a9af9d163175f https://doi.org/10.1088/1757-899x/1084/1/012021 Zobrazit plný text záznamu