Cleaning method of municipal environmental sanitation cleaning garbage truck based on road garbage classification

Abstract

The invention relates to the technical field of image data processing, in particular to a municipal environmental sanitation sweeping garbage truck sweeping method based on road garbage classification. According to the method, the occlusion area in the road garbage image is determined according to the category probability identified by the garbage category identification neural network. And carrying out super-pixel segmentation on the shielding region to obtain a plurality of super-pixel blocks. And expanding the boundary line of the superpixel block to obtain an edge analysis area. Obtaining a plurality of candidate boundary lines in the edge analysis region, obtaining confidence coefficients according to the segmentation capability and pixel value distribution uniformity of the candidate boundary lines, taking the candidate boundary line with the maximum confidence coefficient as a segmentation edge line, obtaining a single junk image, and carrying out analysis by reusing the neural network, thereby achieving the accurate classification of junk. And controlling the cleaning garbage truck to perform targeted cleaning according to the garbage category. The garbage is accurately classified, the sweeping garbage truck is controlled to conduct targeted sweeping according to the classification result, the sweeping efficiency is improved, and meanwhile power consumption is reduced.

Description

technical field [0001] The invention relates to the technical field of image data processing, in particular to a method for cleaning garbage trucks for municipal sanitation cleaning based on road garbage classification. Background technique [0002] At present, urban environmental protection mainly adopts manual lifting for inspection and cleaning or automatic cleaning with garbage trucks. Among them, the automatic cleaning of garbage trucks can save labor costs and meet the purpose of automatic and intelligent urban construction. [0003] In order to maximize the efficiency and minimize the cost of cleaning garbage trucks, a specific cleaning mode needs to be performed according to the difficulty of garbage cleaning for the garbage on the road. Therefore, it is necessary to accurately identify the garbage on the road. In the prior art, neural networks are used to process images on the road, so as to achieve the purpose of garbage classification. However, due to the comple...

AI Technical Summary

Problems solved by technology

In the existing technology, neural networks are used to process images on the road to achieve the purpose of garbage classification, but because of the complex distribution of road garbage, it is easy for garbage to occlude each other, which leads to the inability of the neural network to perform classification tasks. Accurate identification of occluded garbage, thus failing to achieve the purpose of maximizing efficiency and minimizing costs

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