Thesis-1994-Tao.pdf (6.86 MB)
Download fileHigh-speed pattern cutting using real-time computer vision techniques
thesis
posted on 2012-09-28, 09:16 authored by Li G. TaoThis thesis presents a study of computer vision for guiding cutting tools to
perform high-speed pattern cutting on deformable materials. Several new
concepts on establishing a computer vision system to guide a C02 laser beam
to separate lace are presented.
The aim of this study is to determine a cutting path on lace in real-time by
using computer vision techniques, which is part of an automatic lace
separation project. The purpose of this project is to replace the current lace
separation process which uses a mechanical knife or scissors.
The research on computer vision has concentrated on the following aspects:
1. A weighted incremental tracking algorithm based on a reference map is
proposed, examined and implemented. This is essential for tracking an
arbitrarily defined path across the surface of a patterned deformable
material such as lace. Two methods, a weighting function and infinite
impulse response filter, are used to cope with lateral distortions of the
input image. Three consecutive map lines matching with one image line is
introduced to cope with longitudinal distortion. A software and hardware
hybrid approach boosts the tracking speed to hnls that is 2-4 times faster
than the current mechanical method.
2. A modified Hough transform and the weighted incremental tracking
algorithm to find the start point for tracking are proposed and investigated
to enable the tracking to start from the correct position on the map.
3. In order to maintain consistent working conditions for the vision system,
the light source, camera threshold and camera scan rate synchronisation
with lace movement are studied.
Two test rigs combining the vision and cutting system have been built and
used to cut lace successfully.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Publisher
© Li Guo TaoPublication date
1994Notes
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.EThOS Persistent ID
uk.bl.ethos.558025Language
- en