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Encouraged by these results we developed a parallel algorithm for color constancy.
We have used genetic programming to evolve an algorithm for color constancy.
The utilization of a grey-world color constancy image processing algorithm positively affected the classification accuracy for binary classifiers.
For a test image, a color constancy algorithm is selected according to the inference process and the rules previously defined.
The new technique is compared against the alternative approach of preprocessing the images with a color constancy procedure before entering the saliency system.
The ability to compute color constant descriptors of objects in view irrespective of the light illuminating the scene is called color constancy.
Specifically, we trained the convolutional neural network to solve the problem by casting the color constancy problem as an illumination classification problem.
This work presents a novel technique for embedding color constancy into a saliency-based system for detecting potential landmarks in outdoor environments.
This work introduces a fuzzy rule-based system operating as a selector of color constancy algorithms for the enhancement of dark images.
In accordance with the actual content of an image, the system selects among three color constancy algorithms, the White-Patch, the Gray-World and the Gray-Edge.
We understand relatively well how several processes in the cortical visual areas that support recognition capabilities take place, such as orientation discrimination and color constancy.
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Ha Thuy Vy
MA of Applied Linguistic, Maquarie University, Australia