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Digital image enhancement by brightness and contrast manipulation using Verilog hardware description language

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 13 No. 2 (2023)

DOI
10.11591/ijece.v13i2.pp1346-1357
ISSN
2722-2578, 2088-8708
Published
2023-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

A foggy environment may cause digitally captured images to appear blurry, dim, or low in contrast. This will impact computer vision systems that rely on image information. With the need for real-time image information, such as a plate number recognition system, a simple yet effective image enhancement algorithm using a hardware implementation is very much needed to fulfil the need. To improve images that suffer from low exposure and hazy, the hardware implementations are usually based on complex algorithms. Hence, the aim of this paper is to propose a less complex enhancement algorithm for hardware implementation that is able to improve the quality of such images. The proposed method simply combines brightness and contrast manipulation to enhance the image. In order to see the performance of the proposed method, a total of 100 vehicle registration number images were collected, enhanced, and evaluated. The evaluation results were compared to two other enhancement methods quantitatively and qualitatively. Quantitative evaluation is done by evaluating the output image using peak signal-to-noise ratio and mean-square error evaluation metrics, while a survey is done to evaluate the output image qualitatively. Based on the quantitative evaluation results, our proposed method outperforms the other two enhancement methods.

Collaboration network of the authors

15 authors · 41 co-authorship links · 6 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universiti Teknologi MARA
  • Universiti Sains Malaysia
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Siti Noraini SulaimanUniversiti Teknologi MARA2
Muhammad Khusairi OsmanUniversiti Teknologi MARA2
Noor Khairiah A. KarimUniversiti Sains Malaysia2
Saiful Zaimy YahayaUniversiti Teknologi MARA1
Zakaria HussainUniversiti Teknologi MARA1
Rozan BoudvilleUniversiti Teknologi MARA1
Mohammad Nizam IbrahimUniversiti Teknologi MARA1
Yusnita Mohd AliUniversiti Teknologi MARA1
Iza Sazanita IsaUniversiti Teknologi MARA1
Mohd Firdaus AbdullahUniversiti Teknologi MARA1
Dayang Suhaida Awang DamitUniversiti Teknologi MARA1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 1 Nov 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Digital image enhancement by brightness and contrast manipulation using Verilog hardware description language</dc:title><dc:creator>Azhari, Zul Imran</dc:creator><dc:creator>Setumin, Samsul</dc:creator><dc:creator>Noorsal, Emilia</dc:creator><dc:creator>Abdullah, Mohd Hanapiah</dc:creator><dc:description>&lt;jats:p&gt;A foggy environment may cause digitally captured images to appear blurry, dim, or low in contrast. This will impact computer vision systems that rely on image information. With the need for real-time image information, such as a plate number recognition system, a simple yet effective image enhancement algorithm using a hardware implementation is very much needed to fulfil the need. To improve images that suffer from low exposure and hazy, the hardware implementations are usually based on complex algorithms. Hence, the aim of this paper is to propose a less complex enhancement algorithm for hardware implementation that is able to improve the quality of such images. The proposed method simply combines brightness and contrast manipulation to enhance the image. In order to see the performance of the proposed method, a total of 100 vehicle registration number images were collected, enhanced, and evaluated. The evaluation results were compared to two other enhancement methods quantitatively and qualitatively. Quantitative evaluation is done by evaluating the output image using peak signal-to-noise ratio and mean-square error evaluation metrics, while a survey is done to evaluate the output image qualitatively. Based on the quantitative evaluation results, our proposed method outperforms the other two enhancement methods.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2023-04-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v13i2.pp1346-1357</dc:identifier><dc:identifier>10.11591/ijece.v13i2.pp1346-1357</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 13 No 2 (2023); 1346</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/28166/16334</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>