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Color Vision

Color Vision

Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.

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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

A color extraction algorithm by segmentation.

QingE Wu¹, Zhenggaoyuan Fang², Zhichao Song²

¹School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China. wqe969699@163.com.

Scientific Reports

|December 1, 2023

Summary

This summary is machine-generated.

This study introduces a novel color feature extraction algorithm using segmentation. The proposed method offers improved accuracy and speed for color segmentation tasks compared to existing techniques.

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Area of Science:

Computer Vision
Image Processing
Pattern Recognition

Background:

Existing image processing algorithms for feature extraction are often gray-image-based and limited to one-dimensional parameters.
Accurate and efficient color feature extraction is crucial for various application domains.

Purpose of the Study:

To propose a novel, fast, and accurate color feature extraction algorithm based on segmentation.
To evaluate the performance of the proposed algorithm against existing methods under diverse color distributions.

Main Methods:

Development of a segmentation-based color extraction algorithm.
Integration of segmentation and feature extraction techniques.
Location method for region of interest in fuzzy color image preprocessing.

Main Results:

The proposed algorithm demonstrates superior accuracy and reduced extraction time compared to existing methods.
The algorithm exhibits enhanced anti-interference ability and better performance on divergent color edges.
Experimental results validate the advantages of the segmentation algorithm for color segmentation.

Conclusions:

The developed segmentation-based color extraction algorithm offers significant improvements over current approaches.
This research provides a new perspective for color feature extraction with important theoretical and practical implications.