January 29, 2024 Dataset Open Access

Arbash, Elias; Fuchs, Margret; Rasti, Behnood; Lorenz, Sandra; Ghamisi, Pedram; Gloaguen, Richard

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  <identifier identifierType="DOI">10.14278/rodare.2704</identifier>
  <creators>
    <creator>
      <creatorName>Arbash, Elias</creatorName>
      <givenName>Elias</givenName>
      <familyName>Arbash</familyName>
      <affiliation>Helmholtz Institute Freiberg for Resource Technology</affiliation>
    </creator>
    <creator>
      <creatorName>Fuchs, Margret</creatorName>
      <givenName>Margret</givenName>
      <familyName>Fuchs</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7210-1132</nameIdentifier>
      <affiliation>Helmholtz Institute Freiberg for Resource Technology</affiliation>
    </creator>
    <creator>
      <creatorName>Rasti, Behnood</creatorName>
      <givenName>Behnood</givenName>
      <familyName>Rasti</familyName>
    </creator>
    <creator>
      <creatorName>Lorenz, Sandra</creatorName>
      <givenName>Sandra</givenName>
      <familyName>Lorenz</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-8464-2331</nameIdentifier>
      <affiliation>Helmholtz Institute Freiberg for Resource Technology</affiliation>
    </creator>
    <creator>
      <creatorName>Ghamisi, Pedram</creatorName>
      <givenName>Pedram</givenName>
      <familyName>Ghamisi</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-1203-741X</nameIdentifier>
      <affiliation>Helmholtz Institute Freiberg for Resource Technology</affiliation>
    </creator>
    <creator>
      <creatorName>Gloaguen, Richard</creatorName>
      <givenName>Richard</givenName>
      <familyName>Gloaguen</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-4383-473X</nameIdentifier>
      <affiliation>Helmholtz Institute Freiberg for Resource Technology</affiliation>
    </creator>
  </creators>
  <titles>
    <title>PCB-Vision: A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards</title>
  </titles>
  <publisher>Rodare</publisher>
  <publicationYear>2024</publicationYear>
  <subjects>
    <subject>circular economy</subject>
    <subject>automated data processing</subject>
    <subject>optical sensors</subject>
    <subject>recycling</subject>
    <subject>e-waste</subject>
    <subject>printed circuit board</subject>
    <subject>hyperspectral</subject>
    <subject>dataset</subject>
    <subject>RGB</subject>
    <subject>conveyor belt</subject>
    <subject>sensors</subject>
    <subject>machine learning</subject>
    <subject>deep learning</subject>
    <subject>PCBVision</subject>
    <subject>open-source data</subject>
    <subject>digitalization</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2024-01-29</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://rodare.hzdr.de/record/2704</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsSupplementTo">10.48550/arXiv.2401.06528</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://www.hzdr.de/publications/Publ-38529</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsIdenticalTo">https://www.hzdr.de/publications/Publ-38684</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsReferencedBy">https://www.hzdr.de/publications/Publ-38529</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.14278/rodare.2703</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://rodare.hzdr.de/communities/hzdr</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://rodare.hzdr.de/communities/rodare</relatedIdentifier>
  </relatedIdentifiers>
  <version>1</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;&lt;strong&gt;PCB-Vision Dataset&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;Description:&lt;/p&gt;

&lt;p&gt;The PCB-Vision dataset is a multiscene RGB-Hyperspectral benchmark dataset comprising 53 Printed Circuit Boards (PCBs). The RGB images are collected using a Teledyne Dalsa C4020 camera on a conveyor belt, while hyperspectral images (HSI) are acquired with a Specim FX10 spectrometer. The HSI data contains 224 bands in the VNIR range [400 - 1000]nm.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Data Format&lt;/strong&gt;&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;RGB Images: .png files&lt;/li&gt;
	&lt;li&gt;PCB Masks: .jpg files&lt;/li&gt;
	&lt;li&gt;HSI Data: Each hyperspectral data cube is accompanied by a data file and a .hdr file.&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;&lt;strong&gt;Folder Organization&lt;/strong&gt;&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;PCBVision
	&lt;ul&gt;
		&lt;li&gt;HSI/
		&lt;ul&gt;
			&lt;li&gt;53 subfolders (one for each PCB)&lt;/li&gt;
			&lt;li&gt;&amp;#39;General_masks&amp;#39; folder for &amp;#39;General&amp;#39; segmentation ground truth&lt;/li&gt;
			&lt;li&gt;&amp;#39;Monoseg_masks&amp;#39; folder for &amp;#39;Monoseg&amp;#39; segmentation ground truth&lt;/li&gt;
			&lt;li&gt;&amp;#39;PCB_Masks&amp;#39; folder for masks of the 53 PCBs in the hyperspectral cube&lt;/li&gt;
		&lt;/ul&gt;
		&lt;/li&gt;
		&lt;li&gt;RGB/
		&lt;ul&gt;
			&lt;li&gt;53 .jpg images&lt;/li&gt;
			&lt;li&gt;&amp;#39;General&amp;#39;&amp;nbsp;folder for RGB images &amp;#39;General&amp;#39; segmentation ground truth&lt;/li&gt;
			&lt;li&gt;&amp;#39;Monoseg_masks&amp;#39; folder for RGB images &amp;#39;Monoseg&amp;#39; segmentation ground truth&lt;/li&gt;
		&lt;/ul&gt;
		&lt;/li&gt;
	&lt;/ul&gt;
	&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;&lt;strong&gt;Data Classes in Masks&lt;/strong&gt;&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;Masks (both &amp;#39;General&amp;#39; and &amp;#39;Monoseg&amp;#39;) contain 1 to 4 segmentation classes:
	&lt;ul&gt;
		&lt;li&gt;0: &amp;quot;Others&amp;quot;&lt;/li&gt;
		&lt;li&gt;1: &amp;quot;IC&amp;quot;&lt;/li&gt;
		&lt;li&gt;2: &amp;quot;Capacitors&amp;quot;&lt;/li&gt;
		&lt;li&gt;3: &amp;quot;Connectors&amp;quot;&lt;/li&gt;
	&lt;/ul&gt;
	&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;&lt;strong&gt;Code Repository&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;To facilitate reading and working with the data, Python codes are available on the GitHub repository:&lt;/p&gt;

&lt;p&gt;https://github.com/hifexplo/PCBVision&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Citation&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;If you use this dataset, please cite the following article:&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Word&lt;/strong&gt;:&lt;/p&gt;

&lt;p&gt;Arbash, Elias, Fuchs, Margret, Rasti, Behnood, Lorenz, Sandra, Ghamisi, Pedram, &amp;amp; Gloaguen, Richard. (2024). PCB-Vision: A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards (Version 1) [Data set]. Rodare. &lt;a href="http://doi.org/10.14278/rodare.2704"&gt;http://doi.org/10.14278/rodare.2704&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Latex:&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;@article{arbash2024pcb, title={PCB-Vision: A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards}, author={Arbash, Elias and Fuchs, Margret and Rasti, Behnood and Lorenz, Sandra and Ghamisi, Pedram and Gloaguen, Richard}, journal={arXiv preprint arXiv:2401.06528}, year={2024} }&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Contact&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;For further information or inquiries, please visit our website:&lt;/p&gt;

&lt;p&gt;https://www.iexplo.space/&lt;/p&gt;

&lt;p&gt;Contact Email: e.arbash@hzdr.de&lt;/p&gt;</description>
  </descriptions>
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