A detection device and image recognition method for seat belt buckle size and surface defects
A technology of a seat belt buckle and a detection device, which is applied in the detection field, can solve the problems that the seat belt buckle cannot be automated, and achieves the effect of solving the automation
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Embodiment 1
[0042] see Figure 1 to Figure 6 , in one embodiment, a detection device for the size and surface defects of a seat belt buckle, including a front detection platform 26, a back detection platform 27, a feeding part, a front detection part, a turning part, a back detection part, an eddy current detection part, A first sorting unit, a second sorting unit, and a control unit.
[0043] in,
[0044] Both the feeding part and the front detection part are arranged on the front detection platform 26 . The feeding part is used for feeding and conveying the seat belt buckle to be tested to the front detection part, and the front detection part is used to detect the front of the seat belt buckle to be tested and convey it to the turning part.
[0045] The inversion part is arranged between the front detection platform 26 and the back detection platform 27, and is used for receiving and inverting the seat belt buckle conveyed by the front detection part, and conveying it to the rear det...
Embodiment 2
[0067] An image recognition method of the present invention is applied to the industrial camera 11 in the above-mentioned first embodiment, and the steps are as follows:
[0068] S1: Create a standard seat belt buckle shape template.
[0069] S2: The industrial camera 11 acquires an image, and preprocesses the image.
[0070]S3: Perform binary segmentation on the preprocessed image to obtain foreground and background, and then perform connected area detection to confirm the gray-scale mutation in the image.
[0071] S4: Match the image in S3 with the shape template, find the target area to be detected and divide it into blocks, analyze the gray value and pixel point features of each block, extract image blocks with large pixel differences, and identify them as defective pixels group.
[0072] The specific steps of the image recognition method are as follows: the industrial camera 11 collects the seat belt buckle image, first enhances the collected image, then uses median fil...
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