Sorting of cotton impurities by X-ray detection: an effective screening method based on gray value

 

Abstract: This paper introduces the principle and method of cotton impurity sorting by X-ray detection technology, and focuses on the effective screening strategy of cotton impurity based on gray value. By collecting X-ray images and analyzing the gray difference between cotton and impurities, the impurities can be identified and sorted effectively. The experimental results show that this method can significantly improve the accuracy and efficiency of cotton quality detection, and provide effective technical support for cotton processing industry.

Key words: X-ray detection; Cotton impurities; Gray value; Sorting technique

 

I. Introduction

 

As an important textile raw material, the quality of cotton directly affects the quality and market competitiveness of textiles. In the process of cotton processing, the existence of impurities will seriously affect the quality of cotton and processing efficiency. Therefore, the effective detection and sorting of impurities in cotton is the key link to improve the quality of cotton. In recent years, with the rapid development of computer technology and image processing technology, X-ray detection technology has been widely used in the field of cotton impurity sorting. The purpose of this paper is to discuss the application of X-ray detection technology based on gray value in cotton impurity sorting, in order to provide a new idea and method for improving cotton quality detection level.

 

Second, the application principle of X-ray detection technology in cotton impurity sorting

 

X-ray inspection technology is a technology that uses X-rays to penetrate matter and produce images. In the sorting of cotton impurities, X-ray detection technology penetrates cotton samples by emitting X-rays, and different substances have different absorption and scattering degrees of X-rays, thus forming different gray images on the detector. By analyzing these grayscale images, impurities in cotton can be identified and sorted.

 

3. Effective screening method based on gray value

 

Image acquisition and processing

Firstly, cotton samples are scanned by X-ray detection equipment to obtain gray image of cotton samples. In the process of image acquisition, attention should be paid to maintaining the flatness and uniformity of the sample to ensure the accuracy and consistency of the image. Then, the gray image is preprocessed, including denoising, smoothing and so on, to improve the quality and stability of the image.

Gray value analysis

Through the analysis of the gray image after pretreatment, it can be found that there are obvious differences in gray values between cotton and impurities. In general, the gray value of cotton is relatively uniform and relatively low, while the gray value of impurities varies depending on the type and size. Therefore, impurities in cotton can be identified and sorted according to the difference in gray values.

 

Impurity identification and sorting

Based on the analysis results of gray values, a suitable threshold can be set to identify impurities in cotton. The impurity region can be separated from cotton by comparing the gray value of pixels with the threshold value. Then, the impurity region is extracted from the original image by image segmentation technology, and it is labeled and located. Finally, the labeled impurities are sorted and removed by a robotic arm or other automated equipment.

 

Iv. Experiment and result analysis

 

In order to verify the effectiveness of X-ray detection technology based on gray value in cotton impurity sorting, we conducted a series of experiments. In the experiment, we selected different kinds and contents of cotton samples, and used X-ray detection equipment to scan them and collect images. Then, the image is processed by gray value analysis and impurity recognition algorithm, and the impurity sorting result is obtained.

 

The experimental results show that the X-ray detection technology based on gray value can accurately identify the impurities in cotton and carry out effective sorting. Compared with the traditional manual sorting method, this method has higher accuracy and efficiency. At the same time, by adjusting the threshold value and optimizing the algorithm parameters, the accuracy of impurity identification and the effect of sorting can be further improved.

 

V. Discussion and prospect

 

Although the X-ray detection technology based on gray value has made some achievements in cotton impurity sorting, there are still some problems and challenges that need to be solved. First of all, different types and contents of impurities may have different effects on the gray value, so the algorithm needs to be further improved to adapt to different situations. Secondly, the cost and maintenance cost of X-ray inspection equipment is high, which limits its application in some small cotton processing enterprises. In the future, we can consider reducing the cost of equipment and improving the stability of equipment to promote the application of this technology.

 

In addition, with the development of artificial intelligence technologies such as deep learning, these technologies can be considered to be introduced into cotton impurity sorting. By training deep learning models to identify and analyze impurity features in X-ray images, it is expected to further improve the accuracy and efficiency of impurity recognition.

 

Vi. Conclusion

 

This paper introduces the application of X-ray detection technology based on gray value in cotton impurity sorting. By collecting and analyzing the gray value of X-ray images, impurities in cotton can be identified and sorted effectively. The experimental results show that the method has high accuracy and efficiency, and provides an effective technical support for cotton processing industry. In the future, with the continuous development and improvement of technology, it is believed that this method will play a greater role in the field of cotton impurity sorting.