Fractal dimension computation with the Parzon window and its application in target detection

Abstract

The automatic target detection under natural backgrounds is an important topic in the field of automatic target recognition. Fractal dimension is generally related to the roughness of the surface. The fractal dimension of the man-made object is usually lower than the background's because mostly it is smoother than natural background. This feature can be used to detect the target automatically. In the computing of the fractal dimension, the irregular values often appear at the boundary of the different textures in the image. This phenomenon can be called 'edge effect'. It may result in the difficulty in the followed image processing such as thresholding and cluster segmentation. The main reason of the edge effect is the same contribution of the every pixel in the neighborhood of the pixel where the fractal dimension being calculated. In this paper, in order to weaken the 'edge effect' in the fractal dimension computation, a 2-D Parzon window is designed. The accuracy of fractal dimension calculated after multiplied by the Parzon window is discussed, and a new algorithm is proposed to apply in the automatic target detection. The proposed automatic target detection algorithm is adopted in the experiments in images under complex land or sea backgrounds. The correctly detection rate is above 95%. The robust of this algorithm is represented in the cases of the variety of the light, rotation, size changing and occlusion of the target.