January 29, 2024 Dataset Open Access

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

Dublin Core Export

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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Arbash, Elias</dc:creator>
  <dc:creator>Fuchs, Margret</dc:creator>
  <dc:creator>Rasti, Behnood</dc:creator>
  <dc:creator>Lorenz, Sandra</dc:creator>
  <dc:creator>Ghamisi, Pedram</dc:creator>
  <dc:creator>Gloaguen, Richard</dc:creator>
  <dc:date>2024-01-29</dc:date>
  <dc:description>PCB-Vision Dataset

Description:

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.

Data Format


	RGB Images: .png files
	PCB Masks: .jpg files
	HSI Data: Each hyperspectral data cube is accompanied by a data file and a .hdr file.


Folder Organization


	PCBVision
	
		HSI/
		
			53 subfolders (one for each PCB)
			'General_masks' folder for 'General' segmentation ground truth
			'Monoseg_masks' folder for 'Monoseg' segmentation ground truth
			'PCB_Masks' folder for masks of the 53 PCBs in the hyperspectral cube
		
		
		RGB/
		
			53 .jpg images
			'General' folder for RGB images 'General' segmentation ground truth
			'Monoseg_masks' folder for RGB images 'Monoseg' segmentation ground truth
		
		
	
	


Data Classes in Masks


	Masks (both 'General' and 'Monoseg') contain 1 to 4 segmentation classes:
	
		0: "Others"
		1: "IC"
		2: "Capacitors"
		3: "Connectors"
	
	


Code Repository

To facilitate reading and working with the data, Python codes are available on the GitHub repository:

https://github.com/hifexplo/PCBVision

Citation

If you use this dataset, please cite the following article:

Word:

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

Latex:

@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} }

Contact

For further information or inquiries, please visit our website:

https://www.iexplo.space/

Contact Email: e.arbash@hzdr.de</dc:description>
  <dc:identifier>https://rodare.hzdr.de/record/2704</dc:identifier>
  <dc:identifier>10.14278/rodare.2704</dc:identifier>
  <dc:identifier>oai:rodare.hzdr.de:2704</dc:identifier>
  <dc:relation>doi:10.48550/arXiv.2401.06528</dc:relation>
  <dc:relation>url:https://www.hzdr.de/publications/Publ-38529</dc:relation>
  <dc:relation>url:https://www.hzdr.de/publications/Publ-38684</dc:relation>
  <dc:relation>url:https://www.hzdr.de/publications/Publ-38529</dc:relation>
  <dc:relation>doi:10.14278/rodare.2703</dc:relation>
  <dc:relation>url:https://rodare.hzdr.de/communities/hzdr</dc:relation>
  <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>circular economy</dc:subject>
  <dc:subject>automated data processing</dc:subject>
  <dc:subject>optical sensors</dc:subject>
  <dc:subject>recycling</dc:subject>
  <dc:subject>e-waste</dc:subject>
  <dc:subject>printed circuit board</dc:subject>
  <dc:subject>hyperspectral</dc:subject>
  <dc:subject>dataset</dc:subject>
  <dc:subject>RGB</dc:subject>
  <dc:subject>conveyor belt</dc:subject>
  <dc:subject>sensors</dc:subject>
  <dc:subject>machine learning</dc:subject>
  <dc:subject>deep learning</dc:subject>
  <dc:subject>PCBVision</dc:subject>
  <dc:subject>open-source data</dc:subject>
  <dc:subject>digitalization</dc:subject>
  <dc:title>PCB-Vision: A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>