Abstract
To solve the problem of simultaneous localization and mapping of mobile robot vision navigation using infrared thermal imaging, A point-line feature extraction and matching algorithm after infrared image enhancement is proposed for visual odometry. We first used a guided filter to smooth the input image and separate it into the base layer and the detail layer. Then constraining the gradient of the detail will be used gain mask to enhance it. Finally, the two parts of the image combined with weighted coefficients will be exported into the second guided filter. The output image will use LSD to extract line feature, then using ORB algorithm will get point feature extraction and matching from line feature image. The results show the it can effectively improve the defect of infrared image blurred with similar background temperature and difficult to extract image features for mobile robot visual SLAM.
Highlights
Monocular visual odometry for its rich visual information and the computation is relatively small, and become an important branch of Visual-Simultaneous localization and mapping( V-SLAM)[1]
Point feature is the most widely used feature in visual SLAM, and it is mature in feature extraction, matching and representation
It improves the problem that the FAST detector does not have directionality, and uses the fast binary descriptor BRIEF to accelerate the feature extraction of the whole image At present, there are many visual odometry and visual SLAM based on line segment features too
Summary
Monocular visual odometry for its rich visual information and the computation is relatively small, and become an important branch of Visual-Simultaneous localization and mapping( V-SLAM)[1]. It improves the problem that the FAST detector does not have directionality, and uses the fast binary descriptor BRIEF to accelerate the feature extraction of the whole image At present, there are many visual odometry and visual SLAM based on line segment features too. According to using infrared image for VSLAM and comprehensive efficiency and cost, this paper proposed an algorithm which firstly doing image enhancement and denoising and deal with point and line feature extraction. This pretreatment process can effectively improve the infrared visual navigation robot localization accuracy and robustness
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