一种分级声纳图像识别系统的设计研究

设计了一种基于声纳纹理信息的由粗到精的分级图像识别系统。系统的粗识别部分是由灰度—空间直方图构成，该直方图将灰度和空间信息有机地融合起来，较好地解决了传统直方图缺少空间信息的不足；精识别部分通过计算图像频谱曲线的分形维数进行图像识别。该方法既考虑了图像的全局特性又包含了细节信息。从而在不增加计算复杂性的前提下。使识别效率明显提高。通过对声纳图像的识别实验，进一步证明了该方法的有效性和工程应用价值。

Design and Study of Hierarchy Sonar Image Recognition System

Based on coarse-to-fine-recognition, a hierarchy sonar image recognition system is designed. For coarse-recognition, gray-spatial histograms, integrating gray and spatial information, are exploited and overcome the limits of spatial information of traditional histograms. For fine-recognition, the Fourier spectrum in polar coordinates is measured by the fractal dimension. This system contains detail information as well as global information of images. The combination of coarse and fine-recognition improves recognizing accuracy without increasing the complexity of computation. The effectiveness and practical value are shown by sonar image recognizing experiments.