Histogram Equalization Implementation in the Preprocessing Phase on Optical Character Recognition

A 2014 report from Digital Marketing Philippines stated that the number of web applications with visual content as their main product has increased significantly. Image processing technology has also undergone significant growth. One example of this is optical character recognition (OCR), which...

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Main Authors: Peter Pangestu, Dennis Gunawan, Seng Hansun
Format: Article
Language:English
Published: Universitas Indonesia 2017-10-01
Series:International Journal of Technology
Subjects:
Online Access:http://ijtech.eng.ui.ac.id/article/view/877
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spelling doaj-f118a265acac4e13b2938cb24369390b2020-11-24T20:42:08ZengUniversitas IndonesiaInternational Journal of Technology2086-96142087-21002017-10-018594795610.14716/ijtech.v8i5.877877Histogram Equalization Implementation in the Preprocessing Phase on Optical Character RecognitionPeter Pangestu0Dennis Gunawan1Seng Hansun2Computer Science Study Program, Faculty of Engineering and Informatics Universitas Multimedia Nusantara, Jl. Scientia Boulevard, Gading Serpong, Tangerang, Banten 15811, IndonesiaComputer Science Study Program, Faculty of Engineering and Informatics Universitas Multimedia Nusantara, Jl. Scientia Boulevard, Gading Serpong, Tangerang, Banten 15811, IndonesiaComputer Science Study Program, Faculty of Engineering and Informatics Universitas Multimedia Nusantara, Jl. Scientia Boulevard, Gading Serpong, Tangerang, Banten 15811, IndonesiaA 2014 report from Digital Marketing Philippines stated that the number of web applications with visual content as their main product has increased significantly. Image processing technology has also undergone significant growth. One example of this is optical character recognition (OCR), which can convert the text on an image to plain text. However, a problem occurs when the image has low contrast and low exposure, which potentially results in information being hidden in the image. To address this problem, histogram equalization is used to enhance the image’s contrast so the hidden information can be shown. Similar to X-ray scanning used in the medical field, histogram equalization processes scanned images that have low brightness and low contrast. In this study, histogram equalization was successfully implemented using OCR preprocessing. The test was done with a dataset that contains dark background images with low light text; the successful outcome resulted in the ability to show 74.95% of the information hidden in the image.http://ijtech.eng.ui.ac.id/article/view/877Contrast enhancementHistogram equalizationImage processingInformation hidingOptical character recognition
collection DOAJ
language English
format Article
sources DOAJ
author Peter Pangestu
Dennis Gunawan
Seng Hansun
spellingShingle Peter Pangestu
Dennis Gunawan
Seng Hansun
Histogram Equalization Implementation in the Preprocessing Phase on Optical Character Recognition
International Journal of Technology
Contrast enhancement
Histogram equalization
Image processing
Information hiding
Optical character recognition
author_facet Peter Pangestu
Dennis Gunawan
Seng Hansun
author_sort Peter Pangestu
title Histogram Equalization Implementation in the Preprocessing Phase on Optical Character Recognition
title_short Histogram Equalization Implementation in the Preprocessing Phase on Optical Character Recognition
title_full Histogram Equalization Implementation in the Preprocessing Phase on Optical Character Recognition
title_fullStr Histogram Equalization Implementation in the Preprocessing Phase on Optical Character Recognition
title_full_unstemmed Histogram Equalization Implementation in the Preprocessing Phase on Optical Character Recognition
title_sort histogram equalization implementation in the preprocessing phase on optical character recognition
publisher Universitas Indonesia
series International Journal of Technology
issn 2086-9614
2087-2100
publishDate 2017-10-01
description A 2014 report from Digital Marketing Philippines stated that the number of web applications with visual content as their main product has increased significantly. Image processing technology has also undergone significant growth. One example of this is optical character recognition (OCR), which can convert the text on an image to plain text. However, a problem occurs when the image has low contrast and low exposure, which potentially results in information being hidden in the image. To address this problem, histogram equalization is used to enhance the image’s contrast so the hidden information can be shown. Similar to X-ray scanning used in the medical field, histogram equalization processes scanned images that have low brightness and low contrast. In this study, histogram equalization was successfully implemented using OCR preprocessing. The test was done with a dataset that contains dark background images with low light text; the successful outcome resulted in the ability to show 74.95% of the information hidden in the image.
topic Contrast enhancement
Histogram equalization
Image processing
Information hiding
Optical character recognition
url http://ijtech.eng.ui.ac.id/article/view/877
work_keys_str_mv AT peterpangestu histogramequalizationimplementationinthepreprocessingphaseonopticalcharacterrecognition
AT dennisgunawan histogramequalizationimplementationinthepreprocessingphaseonopticalcharacterrecognition
AT senghansun histogramequalizationimplementationinthepreprocessingphaseonopticalcharacterrecognition
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