Scale-adaptive real-time detection for small targets

Small target detection is an interesting subject in computer vision. Traditional methods can not be used to detect specific target with interested size when there are many targets of different sizes in an image. Neither can they be used effectively to detect an approaching target whose image size become larger and larger. In order to solve these problems, a new method of small target detection is presented based on the positive and negative LOG (PNLOG) operator. With the new method, the true target is detected by the Top-Hat algorithm in several initial images based on the rough linear movement of the target in a short period of time. The parameters of PNLOG operator are defined based on the target features. The follow-up images is continuously detected by defined PNLOG operator to determine the position of the true target. The experimental results show that the new method has great capability in real-time detection, detection precision and anti-jamming.