Pavement obstacle detection method based on reverse feature matching

Abstract

The invention discloses a pavement obstacle detection method based on reverse feature matching. Remote sensing change detection field, the method is based on space-air high-resolution remote sensing images. Change information in an image is extracted by using an SIFT feature point reverse matching method, the area and position information of a pavement obstacle in the image is obtained by processing the change information, the method has the characteristics of large-scale and macroscopic detection, and reference information can be provided for emergency rescue and disaster relief route planning and road rush-repair engineering quantity estimation. The method is characterized in that the method comprises the steps that SIFT feature point sets are calculated for remote sensing images beforeand after road loss respectively, feature matching is carried out, and negation is carried out on a matching result to obtain a change information feature point set; screening by using a road buffer area to obtain a change information feature point set in the road area, and screening out false change points and tiny change points by using a sliding window method; and finally, grouping and combining the feature points to obtain position information of the obstacle, obtaining an approximate range of the obstacle in combination with a region growing method, and performing area estimation. The keytechnology of the invention belongs to the field of remote sensing change detection, but the position and area information of the road obstacle can be obtained without image registration, and the degree of automation is high.

Description

technical field [0001] The invention relates to the detection of road obstacles, in particular to the detection of road obstacles caused by disasters such as mudslides, landslides, and subsidences using remote sensing technology, and belongs to the field of remote sensing technology. Background technique [0002] As of the end of 2018, the total mileage of my country's highways reached 4.8465 million kilometers, and the road density reached 50.48 kilometers per hundred square kilometers. my country's mountainous area accounts for more than two-thirds of the country's total area, and mountainous roads are extremely vulnerable to disasters such as mudslides, landslides, subsidence, and rolling stones. In 2018 alone, there were 501 geological disasters that caused road damage, causing huge economic losses. It is of great practical significance for both military and civilian transportation organizations to promptly ascertain information about obstacles in the direction of road ...

AI Technical Summary

Problems solved by technology

[0004] Therefore, the existing road damage remote sensing detection technology has shortcomings such as low degree of automation, difficult registration, and the need for personnel with professional knowledge to operate.

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