No abstract

A moving object recognition approach is presented in this paper. The motion of an object includes the linear or nonlinear translation and rotation. For a 3 -D object, the images taken by a camera are in planar form. They are varied by different distances between camera and the object, variant angles and timing for taking pictures. However, the change rate among these images taken at different instant are logically related. The brightness level between any two neighbour string cells of machine digital scanning raster varies according to the Markovian random walk process. Thus, the direction and position of a moving object can be found by the variations of the cell random walk.The angles between a machine digital scanning raster and the edges of an object in a planar image are called pseudo -refractional angles. The variations of angles can be used as features for object recognition. Together with the Kolmogorov complexity program, the probability function of the process can be changed into a finite length of string arrays to simplify the recognition procedure. The distance between camera and the object can be measured by a radar or supersonic signal for military or industrial applications.

How to use one-chip processor and small size memory to recognize the shape of object is the most important topic in modern industrial application. Usually, it is impossible to get the front view of fast flying object ,the image taken at the view direction are called plane projection images The plane projection image is composed of "object" and "background", that is what we say pixel recursion image. The image processing by the using of pixel recursion is the most simple and fast approach. The pixel recursion image can be achieved by the scanning, and the image after size and orientation normalization can be recognieed by the €had String Array (W) approach.The size nornalization can be achieved by the scann-~ ing device and the orientation normalization can be handled by the Circular Layer String method. In the orientation normalization, the principle axis of unknow image is achieved by rotation and compared with the standard patterns which are pre-estimation. The unknown irnage can be divided into serval subimage and each subimage is coded by the Vertical String Array. By the using of Vertical String Array, the shape of unknown object can k described precisely. In this paper, the experiment results of Vertical String Array. Random Walk and Gauss-Markov-R-process are also discussed.