| 1. | Figure 5 shows the edge points found after the tool runs the calipers
图五就是图四的卡钳运行后找到的边缘点。 |
| 2. | To the non - edge point , it ’ s variance is estimated by it ’ s adjacent non - edge points in the same area
对非边缘点的小波系数,它的方差由其相邻的在同一块区域的系数点决定。 |
| 3. | In the post - processing for the edge points , the contour is found through the methods based on the mathematical morphology
在对边缘点的后处理中，我们采用了基于数学形态学的方法，得到了比较好的物体的外轮廓线。 |
| 4. | The found edge points are then applied to the line fitting tool which fits an infinite length line to the points . the fitted line is hown in figure 6
将找到的边缘点应用于拟合工具，进而形成一条无限长的直线。拟合后的直线如图六所示。 |
| 5. | An algorithm of searching edge points in cloud data is presented which can ensure the correctness of edge points and avoid the edge distortion
设计实现了三维海量空间数据中边界点的提取算法，确保边界点提取的正确性，从而避免数据划分过程中带来的数据边界失真现象。 |
| 6. | It analyses and studies the operating method in image processing area , including image division , image filter , picking up edge point , drawing up line and getting the distance of parallel lines
分析并研究了可用于指针图像处理的图像分割、图像滤波、边缘点提取、直线拟合、平行直线求距等运算方法。 |
| 7. | Upon that an efficient thinning algorithm based on borderline ( etab ) is proposed which treats with individual pixels point in each step and picks up unilateral edge points sequence as the framework of a character image
算法每一步都针对单个的像素点作处理,并提取笔划单侧边缘点序列作为字符图像骨架。 |
| 8. | Then a fast computing method is presented to estimate the curvature of edge points and the points at which curvature is less than some threshold are collected to fit lines
为提取直线边缘，使用改进的序列细化算法将边缘细化为单像素宽，而后用一种快速曲率估计方法估算边缘点的曲率，并保留估算值很小（约等于零）的点拟合直线。 |
| 9. | Firstly , we determined the position of energy edge in every trace by using edge detection algorithm , secondly , we divided all the edge points into wrong points and correct points , then calculated the value of wrong points by spline interpolation
为此，从初至波的特点出发，提出了单道数据边界检测和样条插值相结合进行初至波自动拾取的方法。 |
| 10. | 2 . a policy that that makes it more accurate step by step is adopted for corner detection , which effectively solve the problem that the illusive edge points caused by noise can ’ t be distinguished using the conventional edge extraction algorithm
2 .采用逐步求精的策略进行角点检测,有效地解决了传统边缘提取算法中,无法区分因为噪声产生的虚假边缘点问题。 |
