Indexes for performance evaluation of cameras applied to dynamic measurements

Autor: Emanuele Zappa, Giorgio Busca, Giulia Ghislanzoni
Rok vydání: 2014
Předmět:
Zdroj: Measurement. 51:182-196
ISSN: 0263-2241
DOI: 10.1016/j.measurement.2014.02.006
Popis: Thanks to technology improvements, the applications of vision-based measurement to dynamic applications have been increasing in the last years. The available image resolutions and the high grabbing frequencies allow to acquire high-speed moving object with a good scaling factor and to perform dynamic analysis of vibrating items. Uncertainty analysis of vision-based measuring devices working in almost-static conditions was widely studied in literature, but the case of dynamic measurements still needs a further analysis. The measuring performances thus depend on the well-known parameters that affect the static performances (image resolution and contrast, processing algorithm, noise, etc.) but also on other factors, above all the exposure time and the camera-object relative motion, in terms of instantaneous velocity and acceleration. In this work, a performance analysis of imaging devices applied to dynamic measurements is proposed. The analysis aims to qualify the measurement uncertainty by some indexes, proposed in this work, and designed to quantify the motion effect on the acquired images and consequently the measurement uncertainty. These indexes are based on exposure time and Spatial Frequency Response (SFR) function, which is widely applied in literature and recommended in international standards for the image quality estimation in static acquiring conditions. Appropriate developments of SFR are proposed herein to obtain information on the image quality grabbed in dynamic conditions. The effectiveness of the proposed indexes are proved by several tests, where a target is moved with an harmonic law in controlled condition (varying its frequency and amplitude) and fixing different acquisition conditions in terms of lighting settings, diaphragm aperture, exposure time, etc.
Databáze: OpenAIRE