normal and defects of Chenille Yarn （collected by the backlight source）
Description
This dataset collects samples of different kinds of defective and normal chenille yarn images for the same batch of chenille yarn made of polyester material, aiming to facilitate the task of recognizing and classifying chenille yarn defects in computer vision and machine learning algorithms. This dataset consists of a total of 2500 images of 5 major chenille yarn defects and 2500 normal chenille yarn images, totaling 5000 images. It is captured by an industrial camera in the state of chenille yarn movement. In this case, the surface light source was set on the backside of the chenille yarn. The purpose of the classification aims to differentiate between defective and normal chenille yarns on the premise that the classification of chenille yarn defects should be improved as much as possible at the same time, in order to achieve factory production monitoring and to realize smart factories. In summary, this dataset is a valuable resource for researchers and practitioners for the task of detecting chenille yarn yarn defects in the textile industry. pages, metadata, and a readable format, but is not yet the final version of record. This version will undergo additional proofreading, typesetting, and review before it is published as a final version. However, we are providing this version to give you an early look at the article. Please note that errors may be discovered during the production process which may affect the content of the article. Please note that errors may be discovered during the production process which may affect the content of the article.
Files
Steps to reproduce
We have designed a defect detection system. The defect detection system is composed of the winding mechanism and the image acquisition and analysis system. As for the winding mechanism, there is a three-phase motor with 380 V controlled by the frequency transformer, which will adjust the moving speed for Chenille yarn to go through the image acquisition area by the help of a winding roller and a yarn guider. The image acquisition and analysis system consists of a light-emitting diode (LED) surface backlight source, a CMOS camera and a computer which can display and analysis for the detected defects. The surface backlight source is JH-FL211111-W with the dimension of 211mm×111mm, and the light modulator is JH-ZPV60-2C with the max power of 60 watt. In our application, the power for the surface backlight source will be set to 50 watts by the light modulator. As for the image acquisition area, the distance between the camera and the yarn is about 37.4 mm. The length of the yarn acquired by the camera is about 60 mm, and the image pixel is 400×2000.