A vision based method for automated measurement of circular fiber cross-sections. (1st October 2020)

• Record Type: Journal Article
• Authors: Huang, Shiluo; Jin, Wei; Ye, Ming; Liu, Zheng; Yu, Bingwen; Ying, Yangwei; Zhang, Xuchen; Mu, Ying
• Is Part Of: Measurement. Volume 162(2020)
• Publication Date: 2020-10-01
• Subjects: Circular fiber cross-section -- Hough Transform -- Edge selection -- Diameter measurement -- Microscopic image; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2020.107913
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: A hybrid method is proposed for fiber cross-section measurement. The proposed method utilizes both pixel wise and arc wise information. Experimental results are evaluated with varied size accuracy requirement. The proposed method reaches a high size accuracy in the experiment. Abstract: There are many synthetic fibers with circular cross-sections, and characteristics of the fiber cross-sections have a major influence on the fiber properties. Direct measurements made with microscopic techniques on the fiber cross-sections can output maximum information on transverse dimensions. However, measuring parameters of the fiber sections in the microscopic images is a laborious task. In this paper, a hybrid method based on machine vision is proposed to measure the diameter and ellipticity of the circular fiber cross-sections. The hybrid method consists of modified Circle Hough Transform (CHT) and edge tracing algorithm, and the two sub-algorithms are performed successively. The modified CHT is used for detection and initial measurement of the fiber sections. Then the results are refined by the edge tracing algorithm, outputting elliptical results along with the ellipticity information of each fiber section. Experimental results show that the proposed method outperforms existing methods in circular fiber cross-section measurement.