Image processing-based yarn diameter detection method

Abstract

The invention discloses an image processing-based yarn diameter detection method which comprises the following steps: acquiring a clear image of detected yarns in a dark box, and calibrating a corresponding relationship between the pixels of the detected yarns and the actual size; moving the detected yarns to pass through the dark box at a constant speed, continuously acquiring a sequence image of the detected yarns and storing the image; drawing a gray change curve for each row according to each frame of the sequence image of the detected yarns, taking a small-gray part, and intercepting a gray value coordinate continuing part in the small-gray part as a yarn evenness part of the detected yarns; removing the coinciding part of the yarn evenness part of the detected yarns in each frame according to the moving speed of the detected yarns and the frame frequency of image acquisition, and generating a yarn evenness image of the detected yarns; and obtaining the diameter of the detected yarns according to the corresponding relationship between the image pixels of the detected yarns and the actual size. The method disclosed by the invention has extremely high precision and accuracy, and the detection data can be used for determining the non-uniformity comprising long fragments, short fragments and periodic change of the yarns on different lengths.

Description

technical field [0001] The invention relates to the field of yarn quality detection methods, in particular to a yarn diameter detection method based on image processing. Background technique [0002] Yarn dryness evenness is an important index to measure yarn quality, which not only determines the appearance and inner quality of textiles, but also has a great influence on the stability of textile production process. Yarn diameter is a direct indicator for evaluating yarn uniformity. Accurate and rapid determination of yarn diameter is an engineering-significant task in the textile industry. Yarn diameter is an important indicator for the calculation and modeling of all fabric parameters, which has a direct impact on the performance of some fabric tests; at the same time, because the yarn diameter is related to the penetration of air and moisture in the fabric, the performance and comfort of clothing also Depends on the yarn diameter; in addition, due to the inherent inhomog...

AI Technical Summary

Problems solved by technology

However, the count of the yarn cannot accurately characterize the diameter of the yarn, because due to the change of some parameters (such as fiber density and twist coefficient, etc.) different yarn diameters

At present, the commonly used capacitance test method detects the fiber content in the yarn, which cannot directly reflect the appearance uniformity of the yarn. At the same time, the test results are easily affected by the ambient humidity. The test distance is 8mm, so the short film cannot be detected. Inhomogeneity within the section, unable to accurately detect the yarn diameter

Images