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Optimization Method of Loop Detection Based on Shadow Compensation

In visual simultaneous localization and mapping, loop detection is sometimes affected by illumination and other factors, which may lead to false negative or false positive errors. In order to improve the accuracy of loop detection and reduce the influence of shadow, this paper studies the image acquired under different illumination in the same place. Firstly, the color model of the acquired image is converted from RGB to HSI, and the shadow area in the image is marked by setting threshold value for H, S and I, and divides the non-connected shadow area. Then, according to the edge gradient direction of shadow area, it determines the effective feature pixel points for shadow compensation, and finally uses the feature pixel points to compensate the divided shadow area. The experimental results show that the shadow compensation method in this paper can improve the similarity between the images obtained under different illumination conditions at the same place, and the growth rate of similarity can reach 37.79%. Moreover, the number of loops after compensation in this paper is two more than before, and the calculated motion track is closer to the real motion track of the camera.