Adaptive test bench for characterizing image processing sensors

Lisa Radtke; Ilja Graf-Batuchtin; Maik Rosenberger; Gunther Notni

doi:10.1117/12.2304874

14 May 2018 Adaptive test bench for characterizing image processing sensors

Lisa Radtke, Ilja Graf-Batuchtin, Maik Rosenberger, Gunther Notni

Proceedings Volume 10656, Image Sensing Technologies: Materials, Devices, Systems, and Applications V; 106561R (2018) https://doi.org/10.1117/12.2304874
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

Abstract

The Group for Quality Assurance and Industrial Image Processing has built a new experimental setup to characterize cameras and image sensors according to EMVA1288 standard. Next to the investigation of SLN (Sensitivity-Linearity- Noise) and spatial non-uniformities, the new test bench also provides an examination of the temperature dependence of sensors. The temperature dependent dark current produces an undesirable signal which affects the image quality negative and thus has to be known. It is caused by thermally induced electrons and increases linearly with exposure time as well as exponentially with temperature. To measure the dark current, it is necessary to vary and determine the temperature of the sensor. This was made possible by a climate chamber with a Peltier element, which enables a heating and cooling of the camera. An infrared sensor allows a contact-free detection of the actual camera temperature. Furthermore, the light source was improved for the new test bench. With the installed custom light source and integration sphere a homogeneous irradiation up to 97% is ensured. This way better results in tests were achieved. The light source with variable filter housing enables the use of monochromatically light in a wavelength range of 350 – 1700nm. A live monitoring of the irradiation during the image capturing is possible. A MATLAB script assists in the configuration of the camera, the measurement and the data storage. The user is guided step by step through the program. At the end of the measurements an automated evaluation follows, which illustrates graphs and parameters in a streamlined and print-ready format.

Citation Download Citation

Lisa Radtke, Ilja Graf-Batuchtin, Maik Rosenberger, and Gunther Notni "Adaptive test bench for characterizing image processing sensors", Proc. SPIE 10656, Image Sensing Technologies: Materials, Devices, Systems, and Applications V, 106561R (14 May 2018); https://doi.org/10.1117/12.2304874

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