Research on fast segmentation and correction algorithm of object surface damage image based on machine vision
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DOI: 10.25236/icmmct.2022.042
Corresponding Author
Zou Wangping
Abstract
As an important field of image processing, traditional image interpolation algorithm is widely used at present. Compared with the learning based image interpolation algorithm, the traditional image interpolation algorithm has the advantages of low algorithm complexity and fast processing speed. Many commercial software, such as Microsoft office and Adobe Photoshop, integrate traditional image interpolation algorithms such as nearest neighbor interpolation, bilinear interpolation and bicubic interpolation for image scaling. In addition, this technology is also widely used by many printer drivers. The research goal of this paper is how to further improve the interpolation accuracy and improve the quality of interpolated image while maintaining the processing speed advantage of traditional image interpolation algorithm. This paper mainly studies the bicubic interpolation algorithm, which is the most widely used in the traditional interpolation algorithm. There are two implementation methods of bicubic interpolation algorithm in application, which are 16 point ordinary bicubic interpolation algorithm and 16 point convolution bicubic interpolation algorithm. The difference between them is that they solve the interpolation kernel in different ways.
Keywords
rapid orientation, Bicubic image interpolation, Image processing, Image quality, Image restoration