Reciclaje de chatarra electrónica: Nuevo algoritmo para su clasificación por imágenes hiperespectrales

Artzai Picón-Ruiz; Jone Echazarra-Huguet; Arantza Bereciartua-Pérez

doi:10.6036/2886

Reciclaje de chatarra electrónica: Nuevo algoritmo para su clasificación por imágenes hiperespectrales

Translated title of the contribution: E-Waste recycling: New algorythm for hyperspectral identification

Artzai Picón-Ruiz^*, Jone Echazarra-Huguet, Arantza Bereciartua-Pérez

^*Corresponding author for this work

Computer Vision

Research output: Contribution to journal › Article › peer-review

Abstract

Waste Electrical and Electronic Equipment (WEEE) constitutes 4% of the municipal waste in Europe, being increased by 16 28% every five years. Nowadays, Europe produces 6.5 million tonnes of WEEE per year and currently 90% goes to landfill. WEEE waste is growing 3 times faster than municipal waste and this figure is expected to be increased up to 12 million tones by 2015. Applying a new technology to separate non-ferrous metal Waste from WEEE is the aim of this paper, by identifing multi-and hyper-spectral materials and inserting them in a recycling plant. This technology will overcome the shortcomings posed by current methods, which are unable to separate valuable materials very similar in colour, size or shape. For this reason, it is necessary to develop new algorithms able to distinguish among these materials and to face the timing requirements.

Translated title of the contribution	E-Waste recycling: New algorythm for hyperspectral identification
Original language	Spanish
Pages (from-to)	148-157
Number of pages	10
Journal	Dyna (Spain)
Volume	85
Issue number	2
DOIs	https://doi.org/10.6036/2886
Publication status	Published - Mar 2010

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.6036/2886

Cite this

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title = "Reciclaje de chatarra electr{\'o}nica: Nuevo algoritmo para su clasificaci{\'o}n por im{\'a}genes hiperespectrales",

abstract = "Waste Electrical and Electronic Equipment (WEEE) constitutes 4% of the municipal waste in Europe, being increased by 16 28% every five years. Nowadays, Europe produces 6.5 million tonnes of WEEE per year and currently 90% goes to landfill. WEEE waste is growing 3 times faster than municipal waste and this figure is expected to be increased up to 12 million tones by 2015. Applying a new technology to separate non-ferrous metal Waste from WEEE is the aim of this paper, by identifing multi-and hyper-spectral materials and inserting them in a recycling plant. This technology will overcome the shortcomings posed by current methods, which are unable to separate valuable materials very similar in colour, size or shape. For this reason, it is necessary to develop new algorithms able to distinguish among these materials and to face the timing requirements.",

keywords = "Hyper spectral Imaging, Image classification, Machine vision, Recycling, WEEE",

author = "Artzai Pic{\'o}n-Ruiz and Jone Echazarra-Huguet and Arantza Bereciartua-P{\'e}rez",

year = "2010",

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doi = "10.6036/2886",

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volume = "85",

pages = "148--157",

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T2 - Nuevo algoritmo para su clasificación por imágenes hiperespectrales

AU - Picón-Ruiz, Artzai

AU - Echazarra-Huguet, Jone

AU - Bereciartua-Pérez, Arantza

PY - 2010/3

Y1 - 2010/3

N2 - Waste Electrical and Electronic Equipment (WEEE) constitutes 4% of the municipal waste in Europe, being increased by 16 28% every five years. Nowadays, Europe produces 6.5 million tonnes of WEEE per year and currently 90% goes to landfill. WEEE waste is growing 3 times faster than municipal waste and this figure is expected to be increased up to 12 million tones by 2015. Applying a new technology to separate non-ferrous metal Waste from WEEE is the aim of this paper, by identifing multi-and hyper-spectral materials and inserting them in a recycling plant. This technology will overcome the shortcomings posed by current methods, which are unable to separate valuable materials very similar in colour, size or shape. For this reason, it is necessary to develop new algorithms able to distinguish among these materials and to face the timing requirements.

AB - Waste Electrical and Electronic Equipment (WEEE) constitutes 4% of the municipal waste in Europe, being increased by 16 28% every five years. Nowadays, Europe produces 6.5 million tonnes of WEEE per year and currently 90% goes to landfill. WEEE waste is growing 3 times faster than municipal waste and this figure is expected to be increased up to 12 million tones by 2015. Applying a new technology to separate non-ferrous metal Waste from WEEE is the aim of this paper, by identifing multi-and hyper-spectral materials and inserting them in a recycling plant. This technology will overcome the shortcomings posed by current methods, which are unable to separate valuable materials very similar in colour, size or shape. For this reason, it is necessary to develop new algorithms able to distinguish among these materials and to face the timing requirements.

KW - Hyper spectral Imaging

KW - Image classification

KW - Machine vision

KW - Recycling

KW - WEEE

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U2 - 10.6036/2886

DO - 10.6036/2886

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JO - Dyna (Spain)

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ER -

Reciclaje de chatarra electrónica: Nuevo algoritmo para su clasificación por imágenes hiperespectrales

Abstract

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