改进主动形状模型的遥感图像飞机目标识别方法

Automatic method for aircraft target recognition in remote sensing images based on improved active shape model

提出一种基于梯度方向直方图(HOG)的飞机目标方向估计方法,通过改进主动形状模型(ASM)对不同类型目标之间的形变进行建模,利用核密度估计方法(KDE)得到目标的全局统计形状约束以实现目标识别,并设计了一种针对飞机目标的半自动图像特征点标定策略,提高了对训练样本特征点的标定效率。对遥感图像中飞机目标的识别实验表明,与现有方法相比,研究提出的方法对飞机目标具有更好的识别性能。

We propose an estimation method for aircraft target direction based on histograms of oriented gradients （HOG）, and then use the improved active shape model （ASM） to model the deformation between the different types of targets. Finally, we use kernel density estimation method （KDE） global statistical shape constraint to obtain the target to achieve the target recognition, and design a semi-automatic image feature point detection strategy for aircrafts, which improves the efficiency of training samples for calibration feature points. Recognition experiments on aircraft remote sensing images show the proposed method can better recognize aircraft targets than the existing methods.