A Dynamic Target Recognition Method Based on Correlation Tracking Algorithm

Abstract

Target recognition is a very important part in the field of image processing. The effect of target recognition directly affects the success or failure of subsequent processing. This paper proposed a dynamic target recognition method based on correlation tracking algorithm. The correlation tracking algorithm only needs matching the original data of grey level of related images, no feature extraction or division is required for images. In this case, all information of this series of images can be kept, and the correlation tracking algorithm also has many advantages, no complex pre-processing of the original images is required, and the grey level of images can be used to directly matching key points, so the possibility of implementation is greatly increased. Moreover, under the condition of low noise, matching also can be carried out, and there is no high demand for the quality of sequential images. In such an approach, its local anti-interference ability is very strong. The correlation tracking algorithm can be used to predict the trajectory of a moving object in real life. The experimental results show that the proposed method can detect the objects in an image by providing the region of objects and the background with different colors. The conclusions can be drawn that the proposed method can successfully tackle the object recognition task in most cases.