A High-Speed Real-Time Sorting Method for Fabric Material and Color Based on Spectral-RGB Feature Fusion.

Xin Ru, Yang Chen, Xiu Chen, Changjiang Wan, Jiapeng Chen

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

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1 · What the graph read from it

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2 · The registry

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xin RuCollege of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.

Yang ChenCollege of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.

Xiu ChenZhejiang Sci-Tech University Longgang Research Institute Co., Ltd., Wenzhou 325000, China.

Changjiang WanCollege of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.

Jiapeng ChenCollege of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.

Funding

Zhejiang Province 2023R5212Zhejiang Province 2024C01133Zhejiang Province 2024SJCZX0027Zhejiang Province SQ2023YFB3200093

6 · The paper itself

Abstract

A method for simultaneous classification of fabric material and color based on hyperspectral imaging and visual detection is proposed. Fabric material classification is performed using hyperspectral imaging (HSI) combined with a one-dimensional convolutional neural network (1D-CNN), while fabric color recognition is achieved using an red-green-blue (RGB) camera and a color classification model. Material and color features from the same fabric sample are matched to realize synchronous classification. Experiments were conducted on three fabric materials (cotton, polyester, and cotton-polyester blend) and eight colors. At a conveyor speed of 1 m/s, the sorting success rates reach 95.0% for cotton, 97.5% for polyester, and 85.0% for cotton-polyester blended fabrics. The proposed method demonstrates reliable performance for single-material fabrics and good industrial applicability for automated fabric sorting.

Indexed as

automated recyclingconvolutional neural networksfabric material classificationhyperspectral imagingintelligent manufacturingvision-based classificationwaste textile sorting

Identifiers

PMID41829483

DOI10.3390/s26051521

PMCPMC12987357

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.