Round Target Recognition Method And System Realization

The recognition of circlular object is always an emphasis in image pattern identification. The particle object means a complex and anomalous quasi-circle shape, it commonly exists in realistic life, such as fruit in agriculture , sticks in industry product and round log in forestry and so on. Many articles have presented various methods to solve the recogniton of the circle object, such as template matching,Hough transform. There are many disadvantages about the existing method of identifying the round type images , such as low speed, low veracity and lack of wide appliance and so on.Aim at the existing method of recognizing the quasi-circle, a new policy was proposed after researching on its features. It makes full use of the direction information which goes along with the process of the optimum edge detection, and two algorithms: region statistics and center collection are designed to realize the enhancement of the central information by converging the outline of gobbet object to the center of it,and at the same time it effectively resolves the problem of cutting up the outline of the object and attribution of it; the algorithm of barycenter convergence and gobbet feature decision are used to realize the accurate location of the central position.The above methods are successfully applied in the recognition of stick bundle images in steel factory. The way of constructing the stick bundles offline counting system would be introduced below in detail.. The interface used by the system is designed by Visual Basic and the fast kernel arithmetics are turned into dll designed by Visual C++, thus the system can automatically first select the expectant processing area ; then recognize the radius of stick; and locate the center of stick in a quick way and in the end count the sticks in bundles.The validity of algorithms mentioned above are testified by the result of the experiment, and the goal of automatic identification and detection of quasi-circle object images with computer, are achieved by it too. In addition ,the result of the recognition of other quasi-circle object shows the better universality of the new method.