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Proceedings Paper

Investigation into the use of smartphone as a machine vision device for engineering metrology and flaw detection, with focus on drilling
Author(s): Vikram Razdan; Richard Bateman
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Paper Abstract

This study investigates the use of a Smartphone and its camera vision capabilities in Engineering metrology and flaw detection, with a view to develop a low cost alternative to Machine vision systems which are out of range for small scale manufacturers. A Smartphone has to provide a similar level of accuracy as Machine Vision devices like Smart cameras. The objective set out was to develop an App on an Android Smartphone, incorporating advanced Computer vision algorithms written in java code. The App could then be used for recording measurements of Twist Drill bits and hole geometry, and analysing the results for accuracy. A detailed literature review was carried out for in-depth study of Machine vision systems and their capabilities, including a comparison between the HTC One X Android Smartphone and the Teledyne Dalsa BOA Smart camera. A review of the existing metrology Apps in the market was also undertaken. In addition, the drilling operation was evaluated to establish key measurement parameters of a twist Drill bit, especially flank wear and diameter. The methodology covers software development of the Android App, including the use of image processing algorithms like Gaussian Blur, Sobel and Canny available from OpenCV software library, as well as designing and developing the experimental set-up for carrying out the measurements. The results obtained from the experimental set-up were analysed for geometry of Twist Drill bits and holes, including diametrical measurements and flaw detection. The results show that Smartphones like the HTC One X have the processing power and the camera capability to carry out metrological tasks, although dimensional accuracy achievable from the Smartphone App is below the level provided by Machine vision devices like Smart cameras. A Smartphone with mechanical attachments, capable of image processing and having a reasonable level of accuracy in dimensional measurement, has the potential to become a handy low-cost Machine vision system for small scale manufacturers, especially in field metrology and flaw detection.

Paper Details

Date Published: 22 June 2015
PDF: 18 pages
Proc. SPIE 9530, Automated Visual Inspection and Machine Vision, 95300C (22 June 2015); doi: 10.1117/12.2183081
Show Author Affiliations
Vikram Razdan, Brunel Univ. (United Kingdom)
Richard Bateman, Brunel Univ. (United Kingdom)

Published in SPIE Proceedings Vol. 9530:
Automated Visual Inspection and Machine Vision
Jürgen Beyerer; Fernando Puente León, Editor(s)

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