NICE: A Computational Solution to Close the Gap from Colour Perception to Colour Categorization

The segmentation of visible electromagnetic radiation into chromatic categories by the human visual system has been extensively studied from a perceptual point of view, resulting in several colour appearance models. However, there is currently a void when it comes to relate these results to the phys...

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Bibliographic Details
Published in:PloS one 2016-03, Vol.11 (3), p.e0149538-e0149538
Main Authors: Parraga, C Alejandro, Akbarinia, Arash
Format: Article
Language:English
Subjects:
Adolescent
Adult
Algorithms
Biology and Life Sciences
Brain mapping
Classification
Color
Color Perception - physiology
Color vision
Computational biology
Computational neuroscience
Computer applications
Computer Simulation
Electromagnetic radiation
Ellipsoids
Feasibility studies
Female
Humans
Image processing
Image segmentation
Information processing
Innovations
Labeling
Labelling
Male
Medicine and Health Sciences
Models, Neurological
Neurosciences
Photoreceptors
Physical Sciences
Physiology
Psychological aspects
Psychophysics
Radiation
Segmentation
Social Sciences
Testing
Visual cortex
Visual Cortex - physiology
Visual perception
Visual signals
Visual system
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Summary:The segmentation of visible electromagnetic radiation into chromatic categories by the human visual system has been extensively studied from a perceptual point of view, resulting in several colour appearance models. However, there is currently a void when it comes to relate these results to the physiological mechanisms that are known to shape the pre-cortical and cortical visual pathway. This work intends to begin to fill this void by proposing a new physiologically plausible model of colour categorization based on Neural Isoresponsive Colour Ellipsoids (NICE) in the cone-contrast space defined by the main directions of the visual signals entering the visual cortex. The model was adjusted to fit psychophysical measures that concentrate on the categorical boundaries and are consistent with the ellipsoidal isoresponse surfaces of visual cortical neurons. By revealing the shape of such categorical colour regions, our measures allow for a more precise and parsimonious description, connecting well-known early visual processing mechanisms to the less understood phenomenon of colour categorization. To test the feasibility of our method we applied it to exemplary images and a popular ground-truth chart obtaining labelling results that are better than those of current state-of-the-art algorithms.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0149538