Gabor conversion and extreme learning machine neural network-based seal performance detection method for aluminum foil seal
An extreme learning machine and sealing detection technology, which is applied in the direction of neural learning methods, biological neural network models, neural architectures, etc., can solve the problems of slow detection efficiency, low detection accuracy, and low degree of automation, and achieve fast response speed, The calculation process is simple and the effect of strong generalization
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[0012] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.
[0013] figure 1 The flow chart of the aluminum foil sealing airtightness detection method based on Gabor (Gabor) transform and extreme learning machine (ELM) neural network that the embodiment of the present invention provides, the method comprises:
[0014] The step of collecting the thermal image of the aluminum foil seal includes:
[0015] Image acquisition is performed for each target passing through the thermal imager, and different types of thermal images are collected as training samples and test samples for the neural network.
[0016] The steps of image preprocessing include:
[0017] Image enhancement is used as preprocessing, and the image enhancement adopts the processing method of pseudo-color image enhance...
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