Image registration is an important research content in image processing technology. Aiming at the problem that traditional registration methods are difficult to accurately register low-texture images, this paper proposes a high-precision image registration algorithm based online segment features. For the case of wrong match, using the RANSAC random consistent sampling algorithm when searching for the transformation model, and then iterate the nearest points through ICP to transform the parameters further accurately. From the experimental results, the image registration method proposed in this paper is robust to scale, rotation, and illumination and the registration accuracy is improved.
Aiming at the problems of small separation range and low separation rate in the intelligent separation of coal and gangue, a threshold separation method based on dual-energy X-ray technology is proposed. Low-energy original image, use ratio method to obtain R-value image, integrate R-value image and low-energy image information to fit the R-L curve of coal and gangue, count characteristic values and draw sample distribution maps, calculate the sorting threshold of coal and gangue, and realize coal and the sorting of gangue. The experimental results show that the threshold sorting algorithm is more effective in improving large-size materials than the traditional R-value recognition algorithm and R-L curve fitting algorithm, and the recognition rate of 150-300mm materials is as high as 96.99% and 92.32%.
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