针对视觉检测中高精度、自动化类椭圆图像特征提取的需要,提出一种类椭圆特征自动识别和中心亚像

素定位的完整实现方法。方法中采用基于类椭圆边缘属性对特征区域进行自动识别,采用最小二乘椭圆拟合

精确求取类椭圆亚像素定位中心。实验表明,基于该解决方案,可以实现类椭圆特征的自动识别及椭圆中心的

亚像素定位,定位算法精度较高,鲁棒性强,同时简便易行,不需要人机交互,可以很好地满足视觉检测仪器化

需求。-Vision testing for high-precision, automated image feature extraction Elliptic needs, the characteristics of a Class of Elliptic Automatic Identification and central sub-pixel positioning methods full implementation. Methods based on the type of property on the edge of the characteristics of an oval region of automatic identification, using least squares ellipse fitting precision to strike a class of elliptic center sub-pixel positioning. The experimental results show that based on the solution, you can realize the characteristics of Class of Elliptic Automatic Identification and oval center sub-pixel positioning, high precision positioning algorithm robustness, and user-friendly and does not require human-computer interaction can be well Vision testing instruments to meet the needs.