Working pavement anomaly detection and path optimization method based on computer vision
A computer vision and anomaly detection technology, applied in the field of computer vision, can solve the problems of AGV car bumping, economic loss, and the falling of goods from the car, so as to improve the calculation speed, avoid obstacles in time, and avoid economic losses.
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Embodiment 1
[0050] The embodiment of the present invention provides a method for abnormal detection and path optimization of working road surface based on computer vision, such as figure 1 shown, including:
[0051] The specific scenario for this embodiment is: an AGV trolley automated transportation factory.
[0052] 101. Collect real-time working pavement images, and perform image preprocessing to obtain preprocessed working pavement images.
[0053] The real-time working road image is collected by the camera that comes with the AGV car; image preprocessing is performed on the collected real-time working road image, including: performing Gamma correction and histogram equalization on the image to increase the color difference between the images. contrast and the overall image contrast effect.
[0054] Then, the image is denoised, and the black and white light and dark spot noises generated from the image sensor, channel transmission and decoding processing are processed by median filter...
Embodiment 2
[0083] The embodiment of the present invention provides a method for abnormal detection and path optimization of working road surface based on computer vision, such as figure 2 shown, including:
[0084] 201. Collect a real-time working pavement image, and perform image preprocessing to obtain a preprocessed working pavement image.
[0085] The real-time working road image is collected by the camera that comes with the AGV car; image preprocessing is performed on the collected real-time working road image, including: performing Gamma correction and histogram equalization on the image to increase the color difference between the images. contrast and the overall image contrast effect.
[0086] Then, the image is denoised, and the black and white light and dark spot noises generated from the image sensor, channel transmission and decoding processing are processed by median filtering to obtain the preprocessed image.
[0087] 202. Perform region segmentation on the preprocessed...
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