Algorithm for predicting the length of each color fiber in mixed-wool fiber assemblies based on the transmission image. Issue 3 (February 2020)

• Record Type: Journal Article
• Authors: Chen, Lijun; Shen, Hua; Heng, Chong; Wang, Fumei
• Is Part Of: Textile research journal. Volume 90:Issue 3/4(2020)
• Page Start: 357
• Page End: 366
• Publication Date: 2020-02
• Subjects: mixed wool fiber assemblies -- RGB -- Beer-Lambert -- color transmission image -- fiber relative linear density curve; Textile industry -- Periodicals; Textile fabrics -- Periodicals; Textile research -- Periodicals; Textiles et tissus -- Industrie et commerce -- Périodiques; Textiles et tissus -- Périodiques; Textiles et tissus -- Recherche -- Périodiques; Electronic journals; 677.005
• DOI: 10.1177/0040517519866936
• Languages: English
• ISSNs: 0040-5175

Abstract

A color-separation algorithm was proposed to predict the length of each color fiber in mixed-wool fiber assemblies based on a red, green, and blue transmission image. In this work, mixed-wool fiber assemblies consisted of different color wool fibers and a digital color image was obtained by a scanner. The relative thickness of the fiber assemblies was measured based on the Beer-Lambert theory. The color-separation formula was constructed to calculate the quantity of each color fiber at every point of the mixed-wool top to achieve the relative linear density curve and the average length. A series of systematic experiments demonstrated high consistency with the reference relative linear density curve and average length and confirmed the validity of the color-separation formula. This algorithm could be used for quality detection and control of mixed-wool tops. It could be also extended to uniformity detection of other mixed-color fiber assemblies.