Sports Action Recognition Based on Image Processing Technology and Analysis of the Development of Sports Industry Pattern

The current era is an information age, and society is turning to the information age. The image processing technology is also widely used in various fields, and the technology of sports action recognition based on image processing technology can also be said to be appropriate. This article uses a spatial visual feature analysis algorithm to implement it. To implement this algorithm, a series of work such as image collection, feature extraction, and action recognition must be completed first and then implemented through texture functions and other related functions. This algorithm can be used to complete the image-based sports action recognition technology at the minimum time cost. This algorithm can help sportsmen better complete training and standardize movements to a certain extent. As for the development of China’s current sports industry structure, it is also steadily improving. The people’s love for sports is getting stronger and stronger, which also makes the development of China’s sports industry still benefit a lot.

Application of Visual Sensing Image Processing Technology under Digital Twins to the Intelligent Logistics System

Since the founding of the People’s Republic of China, the advantages of logistics are neglected, and the scale operation and the welfare in the industry are difficult to achieve due to the influence of the economic system and social environment. Therefore, a new intelligent logistics distribution management system based on machine vision and visual sensor image processing technology is constructed to respond to the shortcomings of the traditional system, including slow efficiency, huge cost, complex data, and low degree of informatization. Through the analysis and research on the visual sensor image processing technology and the order processing, receipt management, distribution management, scheduling management, and return management that affect logistics distribution, a simulation experiment is used to verify that the visual sensor image processing technology is rigorous, intelligent, and efficient and has high precision. The intelligent logistics distribution management system can effectively solve the problems existing in the traditional logistics distribution management. The experimental results show that the visual sensor image processing technology can collect and analyze the target image and effectively track and monitor it in the logistics distribution process. The average distribution precision of the intelligent logistics distribution management system reaches more than 99.5%, which is greatly improved compared with 90% of the traditional logistics distribution. And it can greatly improve the distribution efficiency, which increases by about 26.5%. The study realizes the information management of the logistics system and automatically completes all the work according to the designed program, so that the real-time dynamic distribution can be transmitted to the urban logistics distribution at any time.

Intelligent Segmentation and Recognition Method of Breast Cancer Based on Digital Image Processing Technology

With the development of digital image technology, judging diseases by medical image plays an important role in medical diagnosis. Mammography is the most effective imaging examination method for breast cancer at present. Intelligent segmentation and identification of breast cancer images and judging their size and classification by digital image processing technology can promote the development of clinical medicine. This paper introduces the preprocessing technology of breast cancer pathological image and medical image recognition technology of breast cancer. In order to improve the segmentation accuracy of image processing and optimize, the segmentation recognition ability in digital mammography was improved. Based on the technical basis of pathological image analysis of breast cancer, the architecture of intelligent segmentation and recognition system for breast cancer was constructed, and each functional module of intelligent system was introduced in detail. Based on digital image processing technology, filtering technology is used to reduce dryness and improve the clarity of the image. Public datasets INBreast and DDSM-BCRP were used to verify system’s performance, and it was tested on the breast cancer image test set. The experiment shows that the comprehensive performance of the intelligent segmentation and recognition system can realize the segmentation and recognition of breast cancer and has higher accuracy and interpretability, which is helpful to improve the diagnosis of doctors.

Discussion on Teaching Method of Digital Image Processing Technology Based on PBL

A required course for students majoring in digital media technology, computer science and technology, or artificial intelligence is “digital image processing technology.” Aviation, medical image processing, intelligent manufacturing, and many more fields may benefit from the knowledge and skills gained in this course. It contains the qualities of “many conceptions, numerous principles, and various formulae,” according to the curriculum. As a result, traditional teaching techniques only pay attention to the explanation of theoretical information, which may easily lead students to create uninteresting feelings; they have abandoned the in-depth investigation and learning of the course material. The PBL approach is used to provide an interest-driven and problem-solving-driven grounded teaching technique that naturally connects the theoretical foundation with real-world examples and problems. We utilize case teaching to assist students better comprehend theoretical information and to teach them how to apply theoretical knowledge to actual difficulties they encounter in their lives. During the course of many semesters of practice, we discovered that our teaching approaches are quite popular with students. The deployment of a teaching style focused on problem-based learning has resulted in significant improvements in students’ learning initiative, practical ability, and innovative ability.

Digital Image Processing Technology in Design and Development of Automatic Sorting System for Energy Meter Recovery

In order to solve the problems of low sorting efficiency and poor quality caused by manual sorting in traditional electricity meter recovery, this study adopts digital image processing technology to construct an automatic sorting system for electricity meter recovery based on artificial neural network. Firstly, the basic requirements of system construction are analyzed in detail, and then the principle and method of image recognition of artificial neural network are introduced in detail. On this basis, an overall framework of automatic sorting of electricity meter recovery is constructed. Finally, the functional modules are designed and applied, and Azure database is built through SQL Server platform, so as to realize the system application of this research. The final application shows that the automatic sorting system constructed by this study has simple interface and easy operation, which can greatly improve the efficiency and quality of the electricity meter recycling and sorting, and has certain practical significance for the development of the state grid industry.

ITLCS Based on OpenCV Image Processing Technology

With the rapid growth of the number of motor vehicles in the city, traffic congestion is more serious every day, part of it is caused by the coding delay with the red light on, not real traffic jams, now we need a control system that can really change the traffic flow. In this paper, ITLCS (intelligent traffic signal control system) based on OpenCV image processing technology is proposed to adjust the timing of traffic signal according to road density, instead of setting a level that is balanced with other lanes, so that high-load traffic lanes can be used for a long time. The camera facing the roadway in the system takes pictures of the driving route, then takes pictures of the driving density of pedestrians and vehicles, and compares each image through processing technology, after the system is processed, the traffic light signal timing can be adjusted immediately, which greatly reduces the time spent on the inactive green light and can effectively deal with the traffic congestion problem.