Date of Award

Fall 2011

Degree Type

Thesis

Degree Name

Master of Applied Science (MASc)

Department

Electrical and Computer Engineering

Supervisor

David Capson

Co-Supervisor

Derek Schuurman

Language

English

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 maxi-mum purity while maintaining high throughput. This thesis proposes a method toautomatically sort two materials: Polycoat containers and Polyethylene terephtha-late (PET) bottles. This method utilizes a visible light camera and does not relyon Near-Infrared spectrometry. A high-speed method to automatically locate re-gions that likely contain these materials within the image and remove them from thebackground is presented. These regions are merged into whole containers and are classified as either a Polycoat container or PET bottle. This is accomplished using alinear support vector machine (SVM) trained on the histogram of pixel intensities. Anovel graph theoretic based region growing technique is proposed and experimental results are provided to characterize the system. The proposed method obtained a93% recognition rate while running in real-time on an FPGA.

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