Abstract
Image processing technology is a popular practical technology in the computer field and has important research value for signal information processing. This article is aimed at studying the design and algorithm of image processing under cloud computing technology. This paper proposes cloud computing technology and image processing algorithms for image data processing. Among them, the material structure and performance of the system can choose a verification algorithm to achieve the final operation. Moreover, let us start with the image editing features. This article isolates software and hardware that function rationally. On this basis, the structure of a real‐time image processing system based on SOPC technology is built and the corresponding functional receiving unit is designed for real‐time image storage, editing, and viewing. Studies have shown that the design of an image processing system based on cloud computing has increased the speed of image data processing by 14%. Compared with other algorithms, this image processing algorithm has great advantages in image compression and image restoration.
Highlights
By improving computer hardware technology, larger storage devices and faster processors will enable computers to process digital images more efficiently
Conventional images based on image matrix representation are not highly efficient because they require a lot of unnecessary information and a lot of storage space
Considering the different types of unnecessary information in the image represented by the image matrix, researchers have proposed many imaging methods that can improve the performance
Summary
By improving computer hardware technology, larger storage devices and faster processors will enable computers to process digital images more efficiently. Considering the different types of unnecessary information in the image represented by the image matrix, researchers have proposed many imaging methods that can improve the performance. Through a series of image processing algorithms, they completed the threshold segmentation and feature extraction of the solder joint image; the sphericity was determined according to the area and circumference, as well as the shape parameters and eccentricity of the calculated area, paving the way for the identification of defect patterns. The proposed sensor is simulated with a single-pixel input current variation of 2 pA to 100 pA and a corresponding measurement value of 2 mV to 855 mV per pixel. They proposed a new method of pattern detection and recognition in the case of blood
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