Obstacle recongnition method applied to automatic traveling device and automatic traveling device

An obstacle recognition method applied to an automatic traveling device, the method comprising the steps of:

• obtaining an image of an environment in a traveling direction of an automatic traveling device;
• separating out a chrominance channel image and a luminance channel image based on the image;
• performing pre-processing and edge processing on the luminance channel image to obtain an edge image;
• performing histogram statistics on the chrominance channel image to obtain a number of pixels with a maximum color proportion within a preset chrominance interval range of 15-180, denoted as max H;
• performing segmentation and contour processing on the chrominance channel image to obtain a chrominance segmentation threshold and a contour image;
• performing contour detection on the contour image to obtain a contour block;
• collecting statistics on feature values corresponding to the contour block in the edge image and the contour image by:
• obtaining position information of the contour block;
• comparing the position information of the contour block with a preset position threshold to obtain a target contour block;
• and
• collecting statistics on the feature values corresponding to the target contour block in the edge image and the contour image, wherein the feature values include one of:
• a contour size feature value, an average roughness value, and a proportion of black pixel points contained in the contour block;
• or a contour size feature value, an average roughness value, a proportion of pixels within a chrominance segmentation threshold range, and a proportion of black pixel points contained in the contour block;
• and
• comparing the max H and the feature values with preset obstacle recognition and determination conditions,
• wherein the preset obstacle recognition and determination conditions include a plurality of different preset obstacle recognition and determination conditions, and the step of comparing the max H and the feature values with preset obstacle recognition and determination conditions to obtain recognition results comprises:
• comparing the max H and the feature values with the preset obstacle recognition and determination conditions, and if the comparing results that the max H and the feature values satisfy one or more of the plurality of different preset obstacle recognition and the determination conditions are obtained, recognizing that the image has an obstacle region;
• and
• if the comparing results that the max H and the feature values do not satisfy any of the plurality of different preset obstacle recognition and the determination conditions are obtained, recognizing that the image is an image to be filtered.