基于Radon变换的水声图像矩特征提取与分类

成像声纳采集的水声图像分析是自动水下潜器研究中的一个重要课题，该文提出了一种基于图像边缘Radon变换的水声图像矩特征提取和分类方法。使用一种形态学边缘提取算子和细化算法提取二维图像中目标的轮廓，构造目标轮廓在 Radon变换空间的平移、比例和旋转矩不变量，应用于3类水下物体的分类中，实验仿真结果表明该方法在运算速度上优于Hu’s不变矩和图像目标面Radon投影空间不变矩，具有很好的性能和较高的实用价值。

Radon Transform-based Moment Feature Extraction and Classification of Underwater Acoustic Image

The analysis of underwater acoustic image object of sonar is a key issue in autonomous underwater vehicle(AUV).By applying Radon transform,a new method for underwater acoustic image's feature extraction and classification is proposed,which is non-sensitive to the ambiguous noise.After getting the close edge by morphological edge extraction and thinning operators,this paper constructs the edge moment invariants based on Radon projection and uses them in classification of three kinds of underwater objects.Simulation results show the proposed method is robust and its effectiveness is better than Hu's moment invariant and object's plane moment invariance in Radon projective space according to the computing speed.