We have located links that may give you full text access.
JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
Categorizing natural color distributions.
Vision Research 2018 October
The natural objects that we are surrounded with virtually always contain many different shades of color, yet the visual system usually categorizes them into a single color category. We examined various image statistics and their role in categorizing the color of leaves. Our subjects categorized photographs of autumn leaves and versions that were manipulated, including: randomly repositioned pixels, leaves uniformly colored with their mean color, leaves that were made by reflecting the original leaves' chromaticity distribution about their mean ("flipped leaves"), and simple patches colored with the mean colors of the original leaves. We trained a linear classifier with a set of image statistics in order to predict the category that each object was assigned to. Our results show that the mean hue of an object is highly predictive of the natural object's color category (>90% accuracy) and observers' choices are consistent with their use of unique yellow as a decision boundary for classification. The flipped leaves produced consistent changes in color categorization that are possibly explained by an interaction between the color distributions and the texture of the leaves.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app