基于Freeman链码的几何图形识别算法

Recognition Algorithm for Geometry Figure Based on Freeman Chain Code

目前关于几何图形识别的算法存在的问题主要有准确率低,计算复杂度较高,运行时间较长等。利用简洁高效的Freeman链码算法结合几何图形特有的几何属性设计出新的算法,使其能够快速识别几何图形的顶点分布,并反映在一张边界震荡(boundary vibration,BV)曲线图上。该曲线图能够刻画几何图形的属性,如顶点的个数、距离分布,角度的大小,线段的曲直和图形的周长等。因此通过对曲线图的特征分析可以准确识别对应的几何图形。该算法不受图形的平移、旋转、放缩、噪声影响。为了测试算法的稳定性,仿真试验针对九种不同的随机生成且带噪声的几何图形,结果识别率较高,运行速度较快,达到了预期的效果。

Currently there exist some problems about recognition algorithm for geometry figure,such as low rate of accuracy, high order of complexity,long time of running and so forth.This article designs a new algorithm by using the laconic efficient Free- man chain code algorithm with geometry properties of geometry figures, so that it can recognize the distribution of vertexes of geometry figures quickly,and it is displayed in a figure of boundary vibration （BV） curve.By analyzing,we see this figure of curve can describe the properties of geometry figures, such as the number and distance distribution of vertexes,the size of angles,the eurvity of line segments, the perimeter of figures and so on.Hence we can recognize the relevant geometry figure accurately by analyzing the characteristic of the figure of curve.This algorithm isn＇t influenced by translation, rotation, extension and noise of figures.In order to test the stability of the algorithm, the simulation is in connection with nine different kinds of geometry figures which are generat- ed arbitrarily and catty- noise, the result shows the rate of accuracy is high and the speed of running is fast, we acquire the prospec- tive effect.