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A New Technique for Quantitative Analysis of Hair Loss in Mice Using Grayscale Analysis

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Published on: March 9, 2015

Yarn Color Measurement Method Based on Digital Photography.

Jinxing Liang^1,2, Guanghao Wu¹, Ke Yang¹

¹School of Computer Science and Artificial Intelligence, Wuhan Textile University, Wuhan 430200, China.

Journal of Imaging

|August 27, 2025

Summary

This summary is machine-generated.

This study introduces a digital photography method for yarn color measurement, improving consistency with human vision. The new technique offers a more accurate alternative to traditional spectrophotometry for textiles.

Keywords:

K-means clustering photographic colorimetry psychophysical experiment skeleton extraction spectrophotometry texture weighting yarn color measurement

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Area of Science:

Textile Science
Colorimetry
Digital Imaging

Background:

Traditional spectrophotometry for yarn color measurement faces challenges with winding techniques and consistency with human visual perception.
Existing photographic methods may not fully capture the nuances of yarn color as perceived by humans.
Accurate and visually consistent color measurement is crucial for the textile industry.

Purpose of the Study:

To propose and validate a novel yarn color measurement method using digital photography.
To enhance the consistency of yarn color measurements with human visual perception.
To address the limitations of spectrophotometry in capturing visually accurate textile colors.

Main Methods:

A photographic colorimetry system captures digital images of single yarns.
K-means clustering and skeletonization algorithms segment yarn and extract its centerline.
Spectral reconstruction and nonlinear texture-adaptive weighting are applied for accurate color calculation.

Main Results:

The proposed digital photography method demonstrated superior alignment with human visual perception compared to spectrophotometry and other photographic methods.
Psychophysical experiments validated the method's accuracy across various yarn colors.
The study highlighted discrepancies between spectrophotometric data and human perception of yarn color.

Conclusions:

The developed digital photography method provides a more visually consistent approach to yarn color measurement.
This research offers a methodological foundation for creating textile color measurement tools that better match human perception.
The findings underscore the need for advanced color measurement techniques in the textile industry.