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Identification of Image Edge Using Quantum Canny Edge Detection Algorithm

Journal of ICT Research and Applications (JICTRA) · Vol. 13 No. 2 (2019) · pp. 133–144

DOI
10.5614/itbj.ict.res.appl.2019.13.2.4
ISSN
2338-5499, 2337-5787
Published
2019-09-30
Publisher
DRI - ITB
Language
eng

Abstract

Identification of image edges using edge detection is done to obtain images that are sharp and clear. The selection of the edge detection algorithm will affect the result. Canny operators have an advantage compared to other edge detection operators because of their ability to detect not only strong edges but also weak edges. Until now, Canny edge detection has been done using classical computing where data are expressed in bits, 0 or 1. This paper proposes the identification of image edges using a quantum Canny edge detection algorithm, where data are expressed in the form of quantum bits (qubits). Besides 0 or 1, a value can also be 0 and 1 simultaneously so there will be many more possible values that can be obtained. There are three stages in the proposed method, namely the input image stage, the preprocessing stage, and the quantum edge detection stage. Visually, the results show that quantum Canny edge detection can detect more edges compared to classic Canny edge detection, with an average increase of 4.05%.

Keywords

Collaboration network of the authors

4 authors · 6 co-authorship links

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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.

Metadata source: OAI-PMH (metadata jurnal) https://journals.itb.ac.id/index.php/jictra/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Identification of Image Edge Using Quantum Canny Edge Detection Algorithm</dc:title>
	<dc:creator>Sundani, Dini</dc:creator>
	<dc:creator>Widiyanto, Sigit</dc:creator>
	<dc:creator>Karyanti, Yuli</dc:creator>
	<dc:creator>Wardani, Dini Tri</dc:creator>
	<dc:subject xml:lang="en-US">Canny</dc:subject>
	<dc:subject xml:lang="en-US">edge</dc:subject>
	<dc:subject xml:lang="en-US">edge detection</dc:subject>
	<dc:subject xml:lang="en-US">image</dc:subject>
	<dc:subject xml:lang="en-US">quantum</dc:subject>
	<dc:subject xml:lang="en-US">qubit</dc:subject>
	<dc:description xml:lang="en-US">Identification of image edges using edge detection is done to obtain images that are sharp and clear. The selection of the edge detection algorithm will affect the result. Canny operators have an advantage compared to other edge detection operators because of their ability to detect not only strong edges but also weak edges. Until now, Canny edge detection has been done using classical computing where data are expressed in bits, 0 or 1. This paper proposes the identification of image edges using a quantum Canny edge detection algorithm, where data are expressed in the form of quantum bits (qubits). Besides 0 or 1, a value can also be 0 and 1 simultaneously so there will be many more possible values that can be obtained. There are three stages in the proposed method, namely the input image stage, the preprocessing stage, and the quantum edge detection stage. Visually, the results show that quantum Canny edge detection can detect more edges compared to classic Canny edge detection, with an average increase of 4.05%. </dc:description>
	<dc:publisher xml:lang="en-US">DRI - ITB</dc:publisher>
	<dc:date>2019-09-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.itb.ac.id/index.php/jictra/article/view/9386</dc:identifier>
	<dc:identifier>10.5614/itbj.ict.res.appl.2019.13.2.4</dc:identifier>
	<dc:source xml:lang="en-US">Journal of ICT Research and Applications; Vol. 13 No. 2 (2019); 133-144</dc:source>
	<dc:source>2338-5499</dc:source>
	<dc:source>2337-5787</dc:source>
	<dc:source>10.5614/itbj.ict.res.appl.2019.13.2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jictra/article/view/9386/4334</dc:relation>
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