介绍了一种利用多特征联合概率的红外图像中近圆形对象检测方法,通过计算图像中诸多小段曲线的弯拱方向来获得图像中各处存在圆的概率,并用梯度强度对这些概率进行加权,再结合对象内部为空洞的概率,共同形成对图像中近圆形对象所在位置的一个判决。经与经典的Hough变换法相比较,表现出一定的优越性。对一组不同特征的红外图像进行测试实验,均能检测出近圆形对象,表现出一定的适应性,对某些应用场景中的目标检测与识别有辅助价值。

A method is introduced for detecting approximately-circular object in infrared image by using the multi-feature joint probability. Bending direction of short-length curves in the image is calculated to get the directing probability of circles existing at each pixel. Edge intensity in gradient image is used to weight the probability, which is then combined with the probability of hole existing at each position and get a final judge whether or where the approximate-circular objects occur. The method shows some advantages when compared with the resolution from Hough transformation. Experiments with some quite different infrared images show that the method can successfully detect approximately-circular objects and shows good stability, so it is useful for target detection and recognition in some application.