Measuring fiber orientations in nonwoven web images using corner detection by Bézier fitting curves
Source abstract
Abstract
This paper describes a novel method for measuring fiber orientations in nonwoven web images by using Bézier fitting curves to detect corners of fiber edges and to separate crossing fiber edges. First, the Canny detector was adopted to extract fiber edges. Second, Bézier curve fitting was used to fit each fiber edge for calculating the curvature of every point on the edge. Third, corner points were detected by locating points where the curvatures were minimal on various edges and below the threshold to divide edges into segments for orientation calculations. Last, a formula calculating the fiber orientation statistics based on the Euclidean distance was established. The experiment results demonstrated that the proposed method is robust for analyzing different nonwoven web images, and has a high accuracy for corner detection and fiber orientation calculation.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Textile materials and evaluations · Industrial Vision Systems and Defect Detection · Image and Object Detection Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Textile Engineering, Donghua University, Shanghai, China
Key Laboratory of Textile Science & Technology, Donghua University, Shanghai, China
Department of Merchandising and Digital Retailing, University of North Texas, Denton, Texas, USA
Henan Clothing Textiles Engineering Research Center, Henan University of Engineering, Zhengzhou, Henan, China
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