Infrared image segmentation and fusion method based on inspection robot

Abstract

The invention relates to an infrared image segmentation and fusion method based on an inspection robot, which comprises the steps of enhancing and marking equipment edges in an infrared image by usingan MSR algorithm to obtain an enhanced infrared image; performing segmentation on the enhanced infrared image by adopting MUL-PCNN to obtain a segmented infrared image; detecting and extracting equipment edges in the segmented infrared image and a visible image by using Wavelet-Canny; performing feature point purification on the equipment edges by adopting an improved ASURF algorithm, and constructing an affine transformation matrix; and fusing grayscale information in the infrared image into the visible image by adopting bicubic interpolation based on the reliability so as to realize accurate fusion of the infrared image and the visible image. Compared with the prior art, the infrared image segmentation and fusion method has the characteristics of accurate positioning, complete segmentation, high matching accuracy and the like on the aspects such as fault point temperature reading and positioning, equipment segmentation and fault point matching and fusion, and has certain applicationvalues.

Description

technical field [0001] The invention relates to an infrared image segmentation and fusion method of an inspection robot, in particular to an infrared image segmentation and fusion method for an inspection robot based on MUL-PCNN and ASURF. Background technique [0002] Substations are the core hubs of power grids at all levels, and routine inspection of equipment in the substations is a key technical means to ensure the safe operation of the power grid. With the rapid development of the economy, the scale of the power system continues to expand, and the requirements for system stability continue to increase. The existing manual inspection mode is labor-intensive, the inspection quality is scattered, and it is greatly disturbed by harsh environments, so it is difficult to meet the above requirements. With the emergence of robots, they can replace manual tasks with difficult operations and high precision requirements, and more and more attention has been paid to the industria...

AI Technical Summary

Problems solved by technology

[0005] In the infrared image of the actual substation robot operation, the temperature reading and location of the fault point, the identification of the faulty equipment, and the matching and fusion of infrared and visible light images are the key technologies of the remote infrared warning system of the substation inspection robot, but there are often fault points in practical applications. Inaccurate temperature positioning, wrong equipment identification, and large fault point matching errors seriously affect the stable operation of the infrared early warning system

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