针对水下特殊环境的目标检测与识别,提出一种基于霍夫变换与几何特征相结合的特征匹配算法.通过对Canny边缘检测和迭代阈值分割的有机融合,实现了对图像的后处理式联合分割,有效地减小了光照不均等噪声干扰对目标提取的影响.通过霍夫变换直线匹配和几何特征匹配算法对规则的几何目标进行识别,具有较好的抗旋转和抗缩放性能.实验结果表明了该算法的准确性和稳定性.%Aiming at the detection and recognition of underwater target with special environment, a feature matching algorithm based on Hough transform and geometrical feature is proposed.Combined the advantages of Canny edge detection and iterative threshold segmentation, the post-processing combined segmentation algorithm greatly reduced the noise effects on target extraction such as non-uniform illumination.Hough straight line matching and geometrical feature matehing algorithm realized regular geometrical shape target's recognition, showed the performance of anti-rotation and anti-scaling.Experimental result shows the algorithm's accuracy and stability
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