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- W4327501306 abstract "Circuit boards of electrical appliances are carefully checked before leaving the factory to ensure integrity and well functions. For the circuits of high-value electrical equipment, high-precision detection devices will be developed to check if there are any missing components on the circuit. However, for non-scale production of electrical equipment, manual inspection methods are still used to check the circuit boards of electrical equipment. To solve this problem, an unsupervised detection method for missing circuit components is proposed based on difference images and cluster analysis. By the proposed method, the quality inspector only needs to determine a circuit board with complete components and good function as a standard circuit board before testing. Then, a difference image is calculated between the standard image and the target image (i.e., the image to be tested). The difference image is divided into blocks and the eigenvector of each image block is obtained. By employing cluster analysis of the eigenvectors, missing components on the circuit are detected and located. Experimental results show that the proposed achieves a better performance on missing component detection compared with other unsupervised and supervised methods." @default.
- W4327501306 created "2023-03-17" @default.
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- W4327501306 date "2022-09-01" @default.
- W4327501306 modified "2023-09-27" @default.
- W4327501306 title "Unsupervised Detection for Missing Circuit Components based on Difference Images" @default.
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- W4327501306 doi "https://doi.org/10.1109/iccgiv57403.2022.00036" @default.
- W4327501306 hasPublicationYear "2022" @default.
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