Handwriting Recognition of Diverse Languages
Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.7, No. 4)Publication Date: 2018-04-30
Authors : Mihir Shah; Sahil Mehta; Pranav Mody; Akhil Sen Roy; Sunil P. Khachane;
Page : 109-114
Keywords : Optical Character Recognition (OCR); k- Nearest Neighbour (k-NN); Binary Large Objects (BLOBS); Graphical User Interface (GUI); Portable Network Graphics (.png);
Abstract
Online Handwriting Recognition for Diverse Languages is a system which is used to recognize digital as well as handwritten inputs. In this paper we will compare two different methods which we used to serve the above purpose. The two methods are K-Nearest Neighbour(KNN) and Tesseract OCR. We begin this paper by introducing the main purpose of this paper which will include a summary of both KNN as well as Tesseract OCR (Optical Character Recognition). After that we will describe in detail the working of both methods, compare them according to their recognition accuracy. This system will also help in Licence plate number recognition, image extraction from images, extracting text from other types of documents, etc.
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Last modified: 2018-04-26 21:41:34