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Title: Robust active vision industrial CAD parts recognition system

Authors: Tushar Jain; Meenu; H.K. Sardana

Addresses: Mechanical Engineering Department, NIT Kurukshetra, India ' Mechanical Engineering Department, NIT Kurukshetra, India ' CSIO, Chandigarh, India

Abstract: In automated assembly systems the machine parts identification is entirely different from simple object recognition; moreover the ability of humans to differentiate between correct and not correct machine parts is better but it is a difficult task for a machine. In general, with fast moving machine parts on the conveyor manual defect detection by human inspectors is impractical. Also it is expensive, inaccurate, subjective, eye straining and causes other health issues to quality control inspectors. A computer vision-based non-contact inspection technique is developed with image processing methods by considering these problems, for defect detection in industrial machine parts. The present work will help the industrial robot used in assembly process and industrial inspection systems. In this paper features-based industrial object detection techniques are implemented in MATLAB to recognise the presence of the industrial CAD parts in the query image. In the end the actual industrial tool images are also used to show the accuracy and robustness of the proposed machine vision system for industrial manufacturing automation.

Keywords: active vision; industrial CAD parts; image processing; parts recognition; feature-based algorithms; intelligent systems; robotics.

DOI: 10.1504/IJIMR.2018.090942

International Journal of Intelligent Machines and Robotics, 2018 Vol.1 No.1, pp.16 - 33

Received: 14 Jan 2017
Accepted: 08 Feb 2017

Published online: 04 Apr 2018 *

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