USING TEMPLATE MATCHING FOR OBJECT RECOGNITION IN INFRARED VIDEO SEQUENCES

This paper deals with problems of surface object recognition in urban environmental conditions in infrared sequences using the template matching technique. Target recognition is always necessary in the selection and tracking the defined objects. The objects feature is changed in dependence on time and space condition such as weather condition, urban environment, etc. In this article, we proposed a method for targets recognition using template matching technique in infrared (IR) video sequences. A user simply chooses the given object at some point during detection. On the basis of feature of selected object, the algorithm employed the template matching techniques to find the object. The designed algorithm was tested in program MATLAB and MATLAB - SIMULINK. The paper will deal with a new algorithm using template matching. The idea of the paper will approach to reduce processing time and increase precision for object detection and selection in using template matching technique. There are many similarities criteria for template matching that are sum of absolute differences (SAD), locally scaled sum of absolute difference (LSAD), zero -mean sum of absolute differences (ZSAD), sum of squared differences (SSD), etc. In this paper we have employed the similarity criteria normalized cross correlation. The cross correlation is not invariant to changes in image intensity such as lighting conditions, and the range of correlation coefficient is dependent on the size of the feature, while we can normalize for the effect of changing intensity and template size by using normalized cross correlation. The basic principle of the algorithm is based on the assumption the object is selected at time t with the center of mass T and we also know the greatest relative velocity between the camera and the target v(ct). Thus, the greatest distance which the target can move after the interval Delta t will be limited in the circle with the center T at time t and radius R. That means the size of compared image will be smaller than the size of original frame in infrared video sequence. Therefore, the computational time will be faster. In order to reduce the unnecessary computational time of the template matching technique in whole frame, we need to keep the requirement of the selected maximum size of the target is smaller than a half of the size of the frame. It means that the maximum size of the image f(x, y) is equal to the size of the frame in video sequence.