Feature matching method for binocular image splicing of mobile inspection robot

Abstract

The invention provides a feature matching method for binocular image splicing of a mobile inspection robot, and the method comprises the steps: constructing a scale pyramid in a feature point detection stage, extracting feature points through a FAST algorithm with an extremely high speed, and enhancing the robustness of scale invariance; adopting the improved CS -LBP description method to describe the feature points, enhancing robustness of rotation invariance, reducing the dimension of the feature vector, and improving the matching efficiency; and finally, measuring the similarity of the feature vectors by using a DDRN algorithm to complete matching, and eliminating mismatching by using an improved RANSAC algorithm. Compared with a traditional algorithm, the algorithm has the advantages that the real-time performance is greatly improved, meanwhile, feature extraction and matching of the image are accurately achieved, the improved description method is high in anti-interference performance on the rotating image, and high adaptability is still achieved in complex transformation scenes such as affine, zooming and illumination.

Description

technical field [0001] The invention relates to the field of mobile inspection robots, in particular to a feature matching method for mosaic binocular images of a mobile inspection robot. Background technique [0002] At present, mobile inspection robots are an important means of liberating artificial labor in high-risk industrial production. For example, in my country, coal mine resources are very rich, and it is also the main energy consumption in my country. Coal mining is still one of the high-risk industries. Real-time detection and mining of coal mine sites Real-time detection of equipment is an important prerequisite for normal mining operations. Even after a coal mine accident, the detection of underground coal mines is an important guarantee for rapid rescue. In harsh environments, the health, life and property of staff cannot be guaranteed. In order to avoid this situation, mobile inspection robot technology has become an important means of real-time inspection in th...

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Problems solved by technology

[0009] In order to solve the above problems, the object of the present invention is to provide a feature matching method for binocular image mosaic of mobile inspection robot, aiming at the problem of complex operation of traditional algorithm in image mosaic, large amount of calculation and slow matching speed, in the stage of feature point detection, Build a scale pyramid and use the extremely fast FAST algorithm to extract feature points to enhance the robustness of scale invariance; then use the improved CS-LBP description method to describe feature points to enhance the robustness of rotation invariance while reducing the feature vector The dimension improves the matching efficiency; finally, the DDRN algorithm is used to measure the similarity of the feature vectors to complete the matching, and the improved RANSAC algorithm is used to eliminate false matches

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