Automatic recognition method of multi commodity image in Internet of Things system under noise interference

Yuanxi Li

doi:10.1117/12.2631418

18 March 2022 Automatic recognition method of multi commodity image in Internet of Things system under noise interference

Yuanxi Li

Author Affiliations +

Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 121680L (2022) https://doi.org/10.1117/12.2631418
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China

Abstract

Because of the interference of noise, the accuracy of image recognition will decrease. Therefore, an automatic recognition method of multi-commodity image in Internet-of-Things system is proposed. The local pixel block matching algorithm is used to construct the PCA training sample set, and the principal component analysis is used to model. The model is used to filter the noise of commodity image, and the epipolar constraint is introduced into RANSAC algorithm to ensure the reliability of recognition results. Experimental results show that the proposed method can achieve more than 95% accuracy when the threshold of the noise interference strategy is 30%, which is obviously better than the two comparison methods.

Citation Download Citation

Yuanxi Li "Automatic recognition method of multi commodity image in Internet of Things system under noise interference", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 121680L (18 March 2022); https://doi.org/10.1117/12.2631418

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