Method and system for quickly matching image features applied to mine machine vision

A system for matching image features applied to mine machine vision, comprising:

• a processor including a de-noising module, which is configured to de-noise an image to be analyzed using CBDNet network, wherein the image to be analyzed is an intercepted mine video frame image;
• a processor including an image segmenting module, which is configured to perform super-pixel segmentation on the image to be analyzed obtained by de-noising to obtain a plurality of image blocks;
• a processor including an image block screening module, which is configured to calculate the information entropy of each image block to obtain an image block with information entropy greater than a first preset threshold;
• a processor including a feature point set acquiring module, which is configured to use SURF algorithm to extract feature points of the image block with information entropy greater than a first preset threshold, so as to obtain the feature point set of the image to be analyzed;
• a processor including a feature point describing module, which is configured to use the Harr wavelet method to describe each feature point in the feature point set, so as to obtain a feature point descriptor set of the image to be analyzed;
• and
• a processor including a determining module, which is configured to match the feature points in the feature point set of the image to be analyzed with the feature points of the target image based on the feature point descriptor set of the image to be analyzed to confirm whether an aspect of the mine is abnormal, wherein the target image is an image containing information related to potential abnormalities of the mine.