The Research And Implementation Of Tire Defection System With Image Scaling Function

With the rapid growth of the automotive industry and the national attention on transportation safety, tire quality testing has become one of most concern issues of manufacturers, and it is also an effective method to assure the quality of tire. The traditional method of tire quality inspection is to observe X-ray view of a tire by workers and then according to quality standards, workers give tire quality grading and assessment reports. However, this method is very subjective, and the subjectivity may affect the accuracy of tire testing. In addition, workers easily suffer eye fatigue due to prolonged labor. Imported tire defect equipment is very expensive, and it does not apply to real domestic production, so it is very important to produce tire defect equipment which is in line with China’s actual production situation, low-cost, high-performance, ease of operation and human-computer interaction.This paper systematically introduces the self-developed tire defect testing software system. The system provides functions such as real-time transmission of X-ray images of the tires, automatic identification of defects, defect image saving, image zoom and other functions. It is an important application of computer image processing technology in industrial productions. In the system development process, we first understand the needs of users, and then make demand analysis. In outline design stage, we make right system architecture design, determining various functional modules need to be developed and the development environment. This article focuses on the design and implementation of image zooming function in the project.In the first few functional modules of tire quality inspection system, include defect detection method and image acquisition. In subsequent modules the workers may need to reconfirm the defective portion artificially to ensure the accuracy of detection algorithms and to improve tire production system subsequently. After receiving a warning signal for defect issue, workers can select any part of the X-ray tire image in the system to see the enlarged view of that portion in order to find the causes of tire quality failure happened in the production process due to technology and production operations, which can provide practical basis for product quality technical improvements.As an important function of the tire defect detection system, image scaling processing module is also the most frequent part interacting with workers, so the image quality after scaling is particularly important. We must ensure that the system can meet the demand of any multiple image scaling, but also make sure that changing the image resolution will not cause large distortion of tire pictures, otherwise, poor quality image will affect the determination of workers on the tire quality. Considering that several current image scaling algorithms are not satisfactory, this article proposed a new method to realize the image scaling function in the system. The new image scaling algorithm is based on three-dimensional surface reconstruction with edge information as constraints. Compared to traditional image scaling algorithms, our new method has obvious advantages.This paper gives full consideration to the actual application environment and operational efficiency when realizing the above functions. In this paper, we also describe the principles and process of the new algorithms in detail and compare it with other algorithms. At last, we discussed the reasons for choosing the new algorithm.