TY - CHAP
T1 - Physically-accurate synthetic images for machine vision design
AU - Parker, Johne' M.
AU - Lee, Kok Meng
PY - 1996
Y1 - 1996
N2 - In machine vision applications, accuracy of the image far outweighs image appearance. This paper presents physically-accurate image synthesis as a flexible, practical tool for examining a large number of hardware/software configuration combinations for a wide range of parts. Synthetic images can efficiently be used to study the effects of vision system design parameters on image accuracy, providing insight into the accuracy and efficiency of image-processing algorithms in determining part location and orientation for specific applications, as well as reducing the number of hardware prototype configurations to be built and evaluated. We present results illustrating that physically accurate, rather than photo-realistic, synthesis methods are necessary to sufficiently simulate captured image gray-scale values. The usefulness of physically-accurate synthetic images in evaluating the effect of conditions in the manufacturing environment on captured images is also investigated. The prevalent factor investigated in this study is the effect of illumination: the significance of ambient lighting effects on the captured image and, therefore, on camera calibration was shown; if not fully understood, these effects can introduce apparent error in calibration results. While synthetic images cannot fully compensate for the real environment, they can be efficiently used to study the effects of ambient lighting and other important parameters, such as true part and environment reflectance, on image accuracy. We conclude with an evaluation of results and recommendations for improving the accuracy of the synthesis methodology.
AB - In machine vision applications, accuracy of the image far outweighs image appearance. This paper presents physically-accurate image synthesis as a flexible, practical tool for examining a large number of hardware/software configuration combinations for a wide range of parts. Synthetic images can efficiently be used to study the effects of vision system design parameters on image accuracy, providing insight into the accuracy and efficiency of image-processing algorithms in determining part location and orientation for specific applications, as well as reducing the number of hardware prototype configurations to be built and evaluated. We present results illustrating that physically accurate, rather than photo-realistic, synthesis methods are necessary to sufficiently simulate captured image gray-scale values. The usefulness of physically-accurate synthetic images in evaluating the effect of conditions in the manufacturing environment on captured images is also investigated. The prevalent factor investigated in this study is the effect of illumination: the significance of ambient lighting effects on the captured image and, therefore, on camera calibration was shown; if not fully understood, these effects can introduce apparent error in calibration results. While synthetic images cannot fully compensate for the real environment, they can be efficiently used to study the effects of ambient lighting and other important parameters, such as true part and environment reflectance, on image accuracy. We conclude with an evaluation of results and recommendations for improving the accuracy of the synthesis methodology.
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M3 - Chapter
AN - SCOPUS:0030392531
T3 - Proceedings of the Japan/USA Symposium on Flexible Automation
SP - 937
EP - 943
BT - Proceedings of the Japan/USA Symposium on Flexible Automation
A2 - Stelson, K.
A2 - Oba, F.
T2 - Proceedings of the 1996 Japan-USA Symposium on Flexible Automation. Part 2 (of 2)
Y2 - 7 July 1996 through 10 July 1996
ER -