基于小波变换及分形特征的目标检测与识别

提出在对图像进行小波变换的基础上提取图像的分形特征，即通过小波变换对图像进行频域上的分割，使得对图像的描述更丰富，对各频段上的细节图像分别求分形维数组成联合特征矢量，有利于迅速准确地将目标从复杂的自然背景中分离出来，实验结果表明，这种方法能够有效地区分人造物体和自然背景，但计算量较大。

Target Detection and Recognition Based on Wavelet Transform and Fractal Features

There exist cases when fractal features are used to the target detection and recognition that the fractal dimensions of targets are often close to that of their backgrounds. In these cases, it is very hard to distinguish targets from their backgrounds. The solution put forward in this paper is to calculate the fractal features based on the wavelet transform of the image. The image segmentation in the frequency field through wavelet transform enriches the illustration of the image, and the fractal dimensions calculated from the detail images of different frequency segments can be made to a united characteristic vector which is helpful to distinguish man-made targets from complicated background rapidly and accurately. The experimental results indicated that man-made targets and natural background could be effectively distinguished by this method. But it should be mentioned that the mass calculation needed might limit the application of this method.