中文摘要：

AIMTo 选择最佳的边察觉方法识别角膜的表面，并且把三个恰当的曲线方程与 Matlab software.METHODSFifteen 题目作比较被招募。从光连贯断层摄影术(10 月) 的角膜的图象被进口进 Matlab 软件。五个边察觉方法(精明，木头， Prewitt， Roberts， Sobel ) 被用来识别角膜的表面。然后，二个用手的识别方法(ginput 和 getpts ) 被使用分别地识别边坐标。在这些方法之中的差别被比较。二项式的曲线(y=Ax ²+Bx+C), 多项式曲线[p (x)=p1x ⁿ +p2x ⁿ¹ +....+pnx+pn+1 ] 并且圆锥形的节(斧子 ²+Bxy+Cy²+Dx+Ey+F=0) 被用于分别地适合角膜的表面的曲线。在三条恰当的曲线之中的相对优点被分析。最后，角膜的地形学获得的怪癖(e) 和圆锥形的节与配对的 t-test.RESULTSFive 边察觉算法相比显示了角膜的表面的边的所有有的连续坐标。用手的识别的纵标接近了实际的边的里面。二项式的曲线极大地受影响倾斜角度。多项式曲线是几何性质的缺乏并且不稳定。圆锥形的节能计算倾斜的对称轴，怪癖，圆中心，等等。由角膜的地形学和圆锥形的节的 e 价值之间没有重要差别(t=0.9143， P=0.3760 > 0.05 ).CONCLUSIONIt 是可行的与 Matlab 与数学曲线模仿角膜的表面软件。边察觉有更好的重覆性和更高的效率。用手的识别途径是为察觉的不可缺少的补充。多项式和圆锥形的节两个都是为角膜的曲线适合的其他的方法。圆锥形的曲线基于特定的几何性质是最佳的选择。

英文摘要：

AIM：To select the optimal edge detection methods to identify the corneal surface,and compare three fitting curve equations with Matlab software. METHODS：Fifteen subjects were recruited. The corneal images from optical coherence tomography（OCT）were imported into Matlab software. Five edge detection methods（Canny,Log,Prewitt,Roberts,Sobel）were used to identify the corneal surface. Then two manual identifying methods（ginput and getpts）were applied to identify the edge coordinates respectively. The differences among these methods were compared. Binomial curve（y=Ax2＋Bx＋C）,Polynomial curve [p（x）=p1xn＋p2x（n-1）＋....＋pnx＋pn＋1] and Conic section（Ax2＋Bxy＋Cy2＋Dx＋Ey＋F=0）were used for curve fitting the corneal surface respectively. The relative merits among three fitting curves were analyzed. Finally,the eccentricity（e）obtained by corneal topography and conic section were compared with paired t-test. RESULTS：Five edge detection algorithms all had continuous coordinates which indicated the edge of the corneal surface. The ordinates of manual identifying were close to the inside of the actual edges. Binomial curve was greatly affected by tilt angle. Polynomial curve was lack of geometrical properties and unstable. Conic section could calculate the tilted symmetry axis,eccentricity,circle center,etc. There were no significant differences between ＇e＇ values by corneal topography and conic section（t=0.9143,P=0.3760 〉0.05）.CONCLUSION：It is feasible to simulate the corneal surface with mathematical curve with Matlab software. Edge detection has better repeatability and higher efficiency. The manual identifying approach is an indispensable complement for detection. Polynomial and conic section are both the alternative methods for corneal curve fitting. Conic curve was the optimal choice based on the specific geometrical properties.