Currently, handling the enormous assortment of handwriting styles is a big issue in society, and we face more challenges. Blind people are applique a lot of questions reading the material, and any people noted the details in check for paying money books, which are not understandable. Handwritten content recognition is an main task in the field of countenance processing. It is very main to recognise handwritten individualities that are available on faraway of paper, such as pin codes, place names, forensics, suffused forms, and cheque books and traditional papers. In this view, this work has existed framed to process the in manuscript English characters in the form of representations and, with the help of machine learning algorithms, in manuscript text was thought. This work will be very useful even for suburb people the one are struggling to express the text in the document. Using the real time basic document file that was collected, imitation was done utilizing machine learning algorithms, and the results were conferred.
Author(s) Details:
B. Premalatha,
Department of Electronics and Communication
Engineering Coimbatore Institute of Technology, Coimbatore, Tamilnadu, India.
K.
M. Priya,
Department
of Electronics and Communication Engineering Coimbatore Institute of
Technology, Coimbatore, Tamilnadu, India.
T. Yathavi,
Department of Electronics and Communication Engineering Coimbatore
Institute of Technology, Coimbatore, Tamilnadu, India.
Please see the link here: https://stm.bookpi.org/RHMCS-V9/article/view/10418
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