LGPSDD:Light Guide Plate Surface Defect Detection

Citation Author(s):
Zhaopan
Li
Submitted by:
Zhaopan Li
Last updated:
Wed, 11/18/2020 - 05:30
DOI:
10.21227/j177-fq57
License:
0
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Abstract 

The LGP dataset (LGPSSD) consists of LGP samples collected from the industrial site through the image acquisition device of LGP defect detection system. In our dataset, NG samples are regarded as positive samples, and OK samples are regarded as negative samples. Each sample is a grayscale image with a size of 224 * 224 , and has two types of labels: One is the Mask label which is used to supervise the training process of the segmentation subnet, and the other is the classification label (NG corresponds to 1, and OK corresponds to 0), which is employed to supervise the training process of the decision subnet. The dataset totally contains 422 positive samples and 400 negative samples. 

Characteristics: The difference in density between the light guide point distribution of LGP images, the different size, shape and brightness of LGP defects.

Instructions: 

The LGP dataset (LGPSSD) consists of LGP samples collected from the industrial site through the image acquisition device of LGP defect detection system. In our dataset, NG samples are regarded as positive samples, and OK samples are regarded as negative samples. Each sample is a grayscale image with a size of 224 * 224 , and has two types of labels: One is the Mask label which is used to supervise the training process of the segmentation subnet, and the other is the classification label (NG corresponds to 1, and OK corresponds to 0), which is employed to supervise the training process of the decision subnet. The dataset totally contains 422 positive samples and 400 negative samples. 

Characteristics: The difference in density between the light guide point distribution of LGP images, the different size, shape and brightness of LGP defects.