Affiliations: Information Center, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou, China
Correspondence:
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Corresponding author: Yuan Ji, Information Center, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou 550002, China. E-mail: annulus64@yeah.net.
Abstract: In order to solve the problems of large error and low performance of traditional progressive image model matching information checking methods, an automatic progressive image model matching information checking method based on machine learning is proposed. The generation method of progressive image is analyzed, and the target image sample is obtained. On this basis, machine learning algorithm is used to segment progressive image samples. In each image segmentation part, crawler technology is used to automatically collect progressive image model matching information, and under the constraint of image model matching information checking standard, automatic checking of progressive image model matching information is realized from geometric structure, image content and other aspects. Experimental results show that the verification error of the design method is reduced by 0.687 Mb, and the quality of progressive image is improved.
Keywords: Machine learning, progressive, image model matching, information checking, neural network, cluster analysis
