Automatic color accuracy tests for camera performance comparison

Akar, Gözde
There are numerous criteria which are being used to measure camera performance and for determining such criteria, different tests are applied in different test environments. Within this framework, color accuracy testing at camera performance is one of foremost of such tests. In the scope of this paper, a method has been proposed to reduce user interaction in the color accuracy tests in the literature. At the same time, with the color constancy concept, it has been shown that color variation between the different test setups should also be considered as an important criterion on the camera performance.


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In this thesis, we propose a light-weight sparsity-based algorithm, basic thresholding classifier (BTC), for classification applications (such as face identification, hyperspectral image classification, etc.) which is capable of identifying test samples extremely rapidly and performing high classification accuracy. Originally BTC is a linear classifier which works based on the assumption that the samples of the classes of a given dataset are linearly separable. However, in practice those samples may not be ...
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Although several binary classification performance metrics have been defined, a few of them are used for performance evaluation of classifiers and performance comparison/reporting in the literature. Specifically, F1 and Accuracy (ACC) are the most known and conventionally used metrics. Despite their popularity and easy-to-understand characteristics, those metrics exhibit critical robustness issues. This paper suggests a new instrument category named 'performance indicators' and proposes a novel indicator na...
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In this paper we focus on the effect of different interface designs on the performance and cognitive workload of sensor operators (SO) during a target detection task in a simulated environment. Functional near-infrared (fNIR) spectroscopy is used to investigate whether there is a relationship between target detection performance across three SO interfaces and brain activation data obtained from the subjects’ prefrontal cortices that are associated with relevant higher-order cognitive functions such as atten...
Citation Formats
A. HASARPA and G. Akar, “Automatic color accuracy tests for camera performance comparison,” 2018, Accessed: 00, 2020. [Online]. Available: