X-ray detection of cotton impurity sorting system: Application of digital image processing technology and gray recognition

 

With the rapid development of the textile industry, the quality requirements of cotton raw materials are increasingly strict. Impurities in cotton not only affect the performance of the fiber, but also can lead to textile machinery failures and reduce production efficiency. Therefore, an efficient and accurate cotton impurity sorting system has become an important demand for the development of the industry. In recent years, the cotton impurity sorting system based on X-ray detection technology has gradually attracted attention, especially the application of digital image processing technology and gray recognition algorithm, which makes the sorting system more intelligent and efficient.

First, X-ray detection of cotton impurities sorting system basic principle

 

X-ray detection Cotton impurity sorting system uses X-ray to penetrate the cotton, and receives the X-ray signal after penetration through the detector, which is converted into a digital image. In these digital images, cotton fibers and impurities show different gray values depending on the degree of X-ray absorption. Through digital image processing technology and gray recognition algorithm, the system can accurately identify and sort the impurities in cotton.

 

Second, the application of digital image processing technology in the system

 

Digital image processing technology is one of the core of the sorting system for detecting cotton impurities by X-ray. Through the steps of pre-processing, feature extraction and classification recognition of acquired X-ray images, the impurities can be automatically sorted.

Pre-processing: The acquired X-ray images are denoised and enhanced to improve image quality and lay a foundation for subsequent feature extraction and recognition.

 

Feature extraction: The feature information of cotton fiber and impurities, such as shape, size and gray value, is extracted by edge detection, morphological analysis and other methods.

Classification and recognition: Based on the extracted feature information, machine learning algorithm or deep learning algorithm is used to classify and recognize cotton fibers and impurities in the image. By training and optimizing the model, the recognition accuracy and efficiency are improved.

 

Third, application of gray recognition algorithm in the system

 

Gray recognition algorithm is another key technology in X-ray detection of cotton impurity sorting system. Due to the difference of gray values between cotton fiber and impurities, impurities can be accurately identified by gray recognition algorithm.

 

Gray threshold segmentation: According to the gray distribution characteristics of cotton fiber and impurities, the appropriate gray threshold is set, and the pixels in the image are divided into two categories: cotton fiber and impurities. This method is simple and easy, but the selection of threshold has great influence on the recognition result.

 

Gray statistical analysis: Through statistical analysis of the gray histogram of the image, find out the gray distribution law of cotton fiber and impurities, and then realize the identification of impurities. This method is more accurate, but requires more computation.

 

Gray recognition based on machine learning: Machine learning algorithm is used to train a large number of samples to learn the gray characteristics of cotton fibers and impurities, so as to achieve automatic recognition of new samples. This method has high recognition accuracy and generalization ability, but it needs a lot of annotation data and computing resources.

Fourth, system advantages and prospects

 

The X-ray detection cotton impurity sorting system adopts digital image processing technology and gray recognition algorithm, which has the advantages of high automation, high recognition accuracy and fast sorting efficiency. In the future, with the continuous progress of technology and the continuous optimization of algorithms, the performance of the system will be further improved, providing strong support for the development of the textile industry.

 

In short, the X-ray detection cotton impurity sorting system combines digital image processing technology and gray recognition algorithm to realize the automatic identification and sorting of impurities in cotton. The application of this technology will help improve the quality of cotton raw materials, reduce production costs, and promote the sustainable development of the textile industry.