Open AccessPROCESSING IMAGES OF SALES RECEIPTS FOR ISOLATING AND RECOGNISING TEXT INFORMATION
Author(s) -
A. S. Nazdryukhin,
I. N. Khramtsov,
A. N. Tushev
Publication year - 2020
Publication title -
vestnik dagestanskogo gosudarstvennogo tehničeskogo universiteta. tehničeskie nauki
Language(s) - English
Resource type - Journals
eISSN - 2542-095X
pISSN - 2073-6185
DOI - 10.21822/2073-6185-2019-46-4-113-122
Subject(s) - receipt , computer science , optical character recognition , artificial intelligence , image processing , image (mathematics) , computer vision , closing (real estate) , pattern recognition (psychology) , world wide web , political science , law
Objectives . This article presents an application for the processing of scanned images of sales receipts for subsequent extraction of text information using the Tesseract OCR Engine. Such an application is useful for maintaining a family budget or for accounting in small companies. The main problem of receipt recognition is the low quality of ink and printing paper, which results in creasing and tears, as well as the rapid fading of printed characters. Methods . The study is based on a number of algorithms based on mathematical morphology methods for opening, closing and morphological gradient operations, as well as image conversion, which can significantly improve the final recognition of characters by Tesseract. Results . In order to solve this problem, a special image normalisation algorithm is proposed, which includes locating a receipt on an image, processing the received image section, removing image capture and carrier defects, as well as point processing for restoring missing characters. The developed application supports increased recognition accuracy of text information when using Tesseract OCR. Conclusion . The developed system recognises characters with fairly high accuracy, demonstrates a result that is better than that obtained when using the unmodified Tesseract method, but which is still inferior to the recognition accuracy of ABBY FineReader. Methods are also been proposed aimed at improving the developed algorithm.