提出了一种能够从具有复杂背景的航空照片中识别出小目标的模式识别方法。此方法先对图象进行二值化，其中二值化所需的门限值是通过对图象的灰度直方图进行形态滤波并结合小波变换而得到的，然后从二值图象中提取出各非零区域，接下来对原始图象中与这些区域位置对应的灰度区域进行第二次门限化，最后对各小二值图象块进行平移、尺度和旋转不变性变换，求出每个变换图象块的ｎ阶几何矩做为其不变性特征输入ＢＰ网完成各目标的识别。

A system which can recognize compact targets from complex environments independently of objects’position, size and orientation is proposed. The system first selects threshold(s) automatically for the original image to get several binary images. In the simplest case, one threshold and ,therefore, two binary images are got, one of which is got by setting 1 the pixels whose gray value is larger than the threshold , setting others pixel 0, and the other is completely opposite to this one. The binary images are used to determine the patterns’position .The system then uses the position data to extract rectangle areas from the original gray image. For every extracted area, a threshold is selected to get two binary images which are respectively transformed independently of position, size and orientation. Finally the geometrical moments are calculated for the transformed binary image to input to a BP as the image’s features to recognize it.