Abstract: An underwater detection device includes a surface drive boat and an unmanned underwater vehicle. The surface drive boat includes: a hull; transverse attitude-stabilizing thrusters and orbit vectored thrusters arranged at the bottom of the hull; a control box arranged on the hull and electrically connected with the transverse attitude-stabilizing thrusters and the orbit vectored thrusters; a cable and a cable winding assembly arranged on the hull, the control box being connected with the unmanned underwater vehicle by the cable, the cable winding assembly being electrically connected with the control box; and a positioning assembly arranged on the hull and electrically connected with the control box.

Abstract: A global and local binary pattern image crack segmentation method based on robot vision comprises the following steps: enhancing a contrast of an acquired original image to obtain an enhanced map; using an improved local binary pattern detection algorithm to process the enhanced map and construct a saliency map; using the enhanced map and the saliency map to segment cracks and obtaining a global and local binary pattern automatic crack segmentation method; and evaluating performance of the obtained global and local binary pattern automatic crack segmentation method. The present application uses logarithmic transformation to enhance the contrast of a crack image, so that information of dark parts of the cracks is richer. Texture features of a rotation invariant local binary pattern are improved. Global information of four directions is integrated, and the law of universal gravitation and gray and roundness features are introduced to correct crack segmentation results, thereby improving segmentation accuracy.