DocumentCode :
1974981
Title :
Towards real-time sorting of recyclable goods using support vector machines
Author :
House, Bryan W. ; Capson, David W. ; Schuurman, Derek C.
Author_Institution :
Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, ON, Canada
fYear :
2011
fDate :
16-18 May 2011
Firstpage :
1
Lastpage :
6
Abstract :
The amount of recyclable material being processed worldwide is increasing. There is a demand for new technologies that can quickly sort these materials for maximum purity while maintaining high throughput. This paper proposes a method to automatically sort two materials: polycoat containers and PET (Polyethylene Terephthalate) bottles. This method utilizes a visible light camera and does not rely on Near-Infrared spectrometry. This paper proposes a high-speed method to automatically locate regions that likely contain these materials within the image and removes them from the background. These regions are merged into whole containers and are classified as either a polycoat container or PET bottle. This is accomplished using a linear support vector machine (SVM) trained on the histogram of pixel intensities. The proposed method obtained a 93% recognition rate, and is able to run at high frames rates in real-time using a field-programmable gate array.
Keywords :
bottles; field programmable gate arrays; image classification; learning (artificial intelligence); materials handling; plastic products; recycling; support vector machines; waste recovery; PET bottles; SVM; field programmable gate array; high-speed method; linear support vector machine; pixel intensities; polycoat containers; polyethylene terephthalate; real-time recyclable goods sorting; recognition rate; recyclable material processing; visible light camera; Containers; Field programmable gate arrays; Histograms; Materials; Pixel; Positron emission tomography; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sustainable Systems and Technology (ISSST), 2011 IEEE International Symposium on
Conference_Location :
Chicago, IL
ISSN :
2157-524X
Print_ISBN :
978-1-61284-394-0
Type :
conf
DOI :
10.1109/ISSST.2011.5936845
Filename :
5936845
Link To Document :
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