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Author (up) C. Alejandro Parraga; Arash Akbarinia edit   pdf
doi  openurl
  Title NICE: A Computational Solution to Close the Gap from Colour Perception to Colour Categorization Type Journal Article
  Year 2016 Publication PLoS One Abbreviated Journal Plos  
  Volume 11 Issue 3 Pages e0149538  
  Keywords  
  Abstract 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.  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes NEUROBIT; 600.068 Approved no  
  Call Number Admin @ si @ PaA2016a Serial 2747  
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