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The bared earth under or near power transmission lines is one of the main hidden trouble. It is one of the important tasks to recognize the bared earth region from aerial images of Unmanned Aerial Vehicle(UAV) power inspection. After failing to employ the Mask RCNN to recognize the bared earth, this paper proposed an approach of image feature fusion. The HOG and LBP features of aerial images were extracted and fused by different weights. The experiments show that, (1)the average precision of recognizing the bared earth reaches 80%; (2) the average recognizing precision is best when the weights of two features make the order of magnitude of the two features equal. The approach proposed in this paper is suitable for the first image filting by the UAV airborne platform because it has not only quite good recognizing precision but also quite good real-time performance, which provides a new idea for target recognition in UAV aerial images.