۱- Introduction

۲- Camera, image and color models

۳- Image processing techniques

۴- Application 1: Wheel rim detection

۵- Application 2: Automatic 3-D crankshaft verification system

۶- Application 3: Wheel alignment measuring system

۷- Application 4: Stereo visual odometry for mobile robotics

۸- Conclusion

References

Abstract

Modern applications of industrial automation and robotics are increasingly relying on image processing techniques. This paper shows ways in which image processing can be applied to solve actual problems in robotics and instrumentation. The paper starts by presenting the fundamentals of camera models, digital acquisition of images and selected processing techniques, followed by examples of applications of such knowledge. Four examples of image processing applications are shown: rim detection in automotive wheel images, dimensional verification of crankshafts, measurement of wheel alignment angles of a car and a stereo visual odometry algorithm for mobile robotics. The examples not only illustrate the uses of different image processing techniques, but may also inspire the development of new robotic and industrial automation products.

Introduction

The engineering community is experiencing a dramatic growth in application of image processing as a tool to perform non-intrusive precision measurement, autonomous robot navigation or reliable verification of industrial automation processes. Image acquisition and processing techniques are familiar to physics, computer, electrical and mechanical engineering sciences for a relatively long time. Specialized literature on this field is usually dedicated to specific aspects such as the geometry of camera projections and computer vision [1–۵], image acquisition and processing [6], or either the scientific and industrial applications of image processing and analysis [7]. This paper is both a review and a tutorial of applied image processing in industrial automation, aimed at researchers, postgraduate students and engineers. Digital images can be associated with geometric properties of objects, such as shapes and dimensions, which enables a myriad of applications and developments. In order to exploit such possibilities, the paper provides insight into some of the key techniques associated with image acquisition, processing and analysis. Theoretical aspects on the geometry of perspective projection, camera calibration, epipolar geometry and stereo image correspondence are further elaborated with regards to technical details. Such a mathematical framework is the core for the use of cameras as measuring devices in photogrammetry. Four applications of image processing are shown through examples in actual robotics and instrumentation scenarios: rim detection in automotive wheel images; dimensional verification of crankshafts; measurement of the wheel alignment angles of a car, and a stereo visual odometry algorithm for mobile robotics. The examples are innovative concepts that can inspire a wider range of image-related applications. Each example considers four aspects: (1) a motivation; (2) an explicit description of the system setup and calibration; (3) mathematical rationale and references to first principles that explicit the assumptions behind each application; (4) empirical results and discussion.