Research on the Image Annotation Technology for Product Quality and Safety Inspection Data. (March 2020)

• Record Type: Journal Article
• Authors: Ning, Xiuli; Li, Ying; Xu, Yingcheng; Lu, Xiaowei
• Is Part Of: Journal of physics. Volume 1487(2020)
• Publication Date: 2020-03
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1487/1/012020
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In recent years, the vicious events about quality and safety in China have continued to bring serious impacts on people's lives and property. The effective analysis and processing of product quality and safety inspection data will provide intellectual support for the overall improvement in product quality, and the effective control of prominent quality and safety problems in China. Aiming at the phenomenon that there is a large amount of image information in the quality detection data, this paper proposed an image annotation technology based on big data fusion, conducted weight fusion to image similarity and image user similarity, calculated the total similarity of images, and made denoising treatment. The experimental results showed that the method proposed in this study could annotate the quality test data well.