Fan blade image segmentation and grid optimization splicing method

Abstract

The invention discloses a fan blade image segmentation and grid optimization splicing method. The fan blade image segmentation and grid optimization splicing method comprises the following steps: S1,continuously collecting images of a single-sided fan blade to form a group of to-be-spliced original images; S2, using the U-net algorithm to carry out image foreground segmentation on each original image, and extracting a fan blade main body part to form a group of images to be registered; S3, gridding each image to be registered, establishing an index from 1 to m for a grid vertex of each to-be-registered image, then expressing x and y coordinates of the grid vertexes as a vector V of a 2m dimension, defining a global energy function about V, and minimizing the energy function to obtain a grid vertex optimal solution, and S4, completing image splicing according to the grid vertex optimal solution. The method has the advantages that the problem that target splicing fails due to the fact that the depth of field of the target and the background is too large is solved, natural splicing of multiple fan blades is achieved, and spliced images are small in visual effect distortion, continuous and real.

Description

technical field [0001] The invention relates to the field of image splicing. More specifically, the present invention relates to a fan blade image segmentation and grid optimization mosaic method. Background technique [0002] Fan blades are key components of wind turbines. Due to long-term exposure to the external natural environment, common defects such as blisters, cracks, and peeling will appear on the surface of fan blades, which in turn affects the efficiency of wind power generation and the life of the fan. At present, the defect detection of fan blades mainly relies on manual work, which has the problems of low work efficiency, high risk and high cost. With the popularization and application of drone technology, drones are used to replace manual inspection operations, and high-definition resolution cameras are used to observe blades at close range, so that defective blades can be detected in advance and processed in time to ensure the safe operation of system equipm...

AI Technical Summary

Problems solved by technology

[0005] Another object of the present invention is to provide a fan blade image segmentation and grid optimization mosaic method, which uses the deep learning U-net algorithm and the wind blade mosaic method with straight line maintenance constraints, which solves the problem of target mosaic caused by excessive depth of field between the target and the background The problem of failure: the straight line feature of the edge of the wind turbine is effectively protected by using the grid splicing technology of the straight line maintenance technology, and the natural splicing of multiple fan blades is realized. The visual effect of the spliced ​​image is less distorted and continuous and real

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