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All Journal Scientific: Journal of Computer Science and Informatics
Rosyid, Romadhoni
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Computer Science & IT

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Improving the Quality of Optical Character Recognition (OCR) Based on Neural Network with the Image Enhancement Process Sutriawan, Sutriawan; Kurniawan, Ade; Rosyid, Romadhoni
Scientific: Journal of Computer Science and Informatics Vol. 1 No. 2 (2024): Juli 2024
Publisher : Universitas Muhammadiyah Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34304/scientific.v1i2.334

Abstract

OCR (Optical Character Recognition) is an effective solution for the process of converting printed documents to digital documents. The problem that arises in the process of computer document recognition is the level of accuracy is very dependent on the quality of the input and the porosity of the character pattern. In this study we tried to research how the most optimal way to read characters on shopping receipts. Physically notes or shopping receipts are easily faded and prone to noise so they are difficult to read. Even after the scan process the resulting output is increasingly difficult to read. So that to do the text recognition (OCR) process will produce a low level of accuracy. To improve the accuracy of the OCR process, it is necessary to improve the quality of the results of the receipt scan before the OCR process is carried out. Image quality improvement (image enhancement) is one of the steps taken in image processing and pattern recognition. The Image Enhancement method used is Noise Removal and Contrast Stretching.
Co-Authors Ade Kurniawan Sutriawan Sutriawan