Adaptive illumination through spatial modulation of light intensity and image inversion

The paper introduces the concept of spatial modulation of light intensity in the context of vision-based quality control, with the aim to improve image quality, measurable by indices such as image contrast and Tenengrad, so as to enhance the level of confidence of the diagnosis performed by image processing. The proposed technique is based on the projection of spatially modulated light intensity distribution by a digital light projector that allows an arbitrary light distribution to be projected on the target. The projected spatial distribution of light is determined by implementing an algorithm based on image inversion: the image acquired by the camera under uniform illumination is inverted and it is then used to modulate the light spatial distribution for projection. The process is repeated iteratively with the purpose to enhance image quality until convergence. The technique proves particularly valuable to avoid saturation from reflecting surfaces, which are often found in industrial practice. The procedure is tested and validated both by a numerical model and by an experimental validation, referring to a significant problem for the washing machine manufacturing industry. The use of image quality estimators confirms the effectiveness of the method.

[1]  Shree K. Nayar,et al.  High dynamic range imaging: spatially varying pixel exposures , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[2]  Lei Wang,et al.  Design of Machine Vision Applications in Detection of Defects in High-Speed Bar Copper , 2010, 2010 International Conference on E-Product E-Service and E-Entertainment.

[3]  Gian Luca Foresti,et al.  Adaptive camera regulation for investigation of real scenes , 1996, IEEE Trans. Ind. Electron..

[4]  Zhao-Bang Pu,et al.  Design of self-adapting illumination in the vision measuring system , 2003, Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).

[5]  Alexander Hornberg.  Handbook of Machine Vision , 2006 .

[6]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[7]  Keith Ridgway,et al.  Study of Lighting Solutions in Machine Vision Applications for Automated Assembly Operations , 2011 .

[8]  Antônio Otávio Fernandes,et al.  Machine vision applications and development aspects , 2011, 2011 9th IEEE International Conference on Control and Automation (ICCA).

[9]  Mathias Fink,et al.  Acoustic time-reversal mirrors , 2001 .

[10]  Jay Martin Tenenbaum,et al.  Accommodation in computer vision , 1971 .

[11]  Anthony Rowe,et al.  Fast reactive control for illumination through rain and snow , 2012, 2012 IEEE International Conference on Computational Photography (ICCP).

[12]  Li Xin,et al.  The application of machine vision in inspecting position-control accuracy of motor control systems , 2001, ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501).

[13]  Zhaohui Jiang,et al.  The study of illumination compensation correction algorithm , 2011, 2011 International Conference on Electronics, Communications and Control (ICECC).

[14]  P. Corbell.  Adaptive Illumination Patterns for Radar Applications , 2012 .

[15]  L. J. Hornbeck,et al.  Digital Light Processing and MEMS: an overview , 1996, Digest IEEE/Leos 1996 Summer Topical Meeting. Advanced Applications of Lasers in Materials and Processing.

[16]  Paolo Castellini,et al.  System for measuring the coordinates of tire surfaces in transient conditions when rolling over obstacles: description of the system and performance analysis. , 2008, The Review of scientific instruments.

[17]  D. Gweon,et al.  Cross structured illumination for high speed high resolution line scanning confocal microscopy , 2010 .

[18]  Dae-Gab Gweon,et al.  Design and analysis of a cross-type structured-illumination confocal microscope for high speed and high resolution , 2012 .

[19]  Jiancheng Jia,et al.  A Machine Vision Application for Industrial Assembly Inspection , 2009, 2009 Second International Conference on Machine Vision.