Anti-snake shock absorber oil leakage detection method and system based on laws texture features
A technology of texture features and detection methods, which is applied in the field of rail vehicle image processing, can solve the problems of low algorithm robustness and low detection efficiency, achieve good separation effect, improve efficiency, and reduce costs
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specific Embodiment approach 1
[0054] Specific implementation mode one: the following combination figure 1 and figure 2 Describe this embodiment, the anti-snake shock absorber oil leakage detection method based on the Laws texture feature described in this embodiment, the method includes the following steps:
[0055] Step 1, collect the passing car image, and intercept the anti-snake shock absorber sub-image as the original image, and preprocess the original image;
[0056] Step 2. Preliminary positioning of the oil-stained area in the original image of the anti-snake shock absorber based on a threshold segmentation algorithm based on image entropy, and obtaining the original image of the initial positioning of the oil-stained area;
[0057] Step 3. Locate the position of the anti-snake damper in the original image based on the random Hough transform algorithm. According to the position of the anti-snake damper determined in this step, the shadow area outside the area of the anti-snake damper in the ima...
specific Embodiment approach 2
[0061] Specific implementation mode two: this implementation mode further explains implementation mode one, and the specific process of step one is:
[0062] Step 11. Set up high-definition imaging equipment on both sides of the track to obtain passing images of rail vehicles;
[0063] Step 12, take a screenshot of the anti-snake shock absorber sub-image from the passing car image as the original image;
[0064] Step 13: Perform image preprocessing on the original image by using a Gaussian filter or a histogram equalization algorithm.
[0065] Set up high-definition imaging equipment around the track of the railway high-speed train. After the train passes by, the image of the passing train is obtained, and the image of the anti-snake shock absorber is intercepted. The original image has image quality defects such as white noise, high brightness, and low contrast. The Gaussian filter, histogram equalization and other algorithms described in this embodiment are used to perform ...
specific Embodiment approach 3
[0066] Specific implementation mode three: the following combination image 3 Describe this embodiment, this embodiment will further explain Embodiment 1 or 2. Threshold segmentation is a commonly used image segmentation method. The basic idea is to determine a threshold, and then compare the gray value of each pixel with the threshold. According to the comparison result, the pixel is divided into two categories: foreground or background, and the threshold segmentation can be divided into the following three steps:
[0067] 1) Determine the threshold
[0068] 2) Compare threshold and pixel
[0069] 3) Pixel classification
[0070] Among them, the first step to determine the threshold is the most important. The choice of threshold will directly affect the accuracy of segmentation and the resulting image description and analysis. The gray value of the oil stain area is smaller than that of the background area, so it is suitable to use the threshold segmentation method for im...
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