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edge tracing meaning in Chinese

边缘跟踪

Examples

  1. Experiments specify that we can get the accurate edge trace and the equations fitted from the collecting data through edge sharpening and detection of image processing technique
    实验结果表明,采用图像处理技术是可以将一个采集来的图像经过边缘锐化和边缘检测形成比较清晰的轨迹,能够拟合出比较精确的方程。
  2. ( 7 ) traditional region labeling was not considered because it wastes time and scan frequently the image . but fast edge tracing was improved to trace several edges each time . chain code of the edge was used to calculate perimeter and object area
    ( 7 )针对区域标记存在速度慢、重复扫描图像等不足,改进了轮廓跟踪算法,使区域标记与轮廓跟踪有机地结合在一起,提高了处理速度,同时改进了面积计算方法,避免了筛选和排序。
  3. First , the authors uses regional growing algorithm based on seeds point selected by manual work to ascertain the main area awaits to be segmented , then taking advantage of the precision of the edge tracing method to precisely define the boundary and thus to attain the precise segmentation
    先用人工选取种子点的区域增长算法确定待分割组织的主体区域,再利用边缘跟踪法对细节处理较好的特点精确定位边界,从而达到准确分割的目的。
  4. Contraposed those characteristics of leather , after studying all kinds of algorithms of image segmentation , this dissertation chooses the techniques of thresholding methods of parallel region segmentation and edge tracing methods of serial edge segmentation to detect the contour of the leather image . then by using polygonal approximation method , we can convert the contour ' s form from image into graphics . it will make following arrangement works more convenient
    本论文针对皮革图象的上述特点,在对各种图象分割算法进行研究后,选用了并行区域分割中的阈值化技术及串行边界分割中的轮廓跟踪技术,将皮革图象的边缘轮廓检测出来,并对该轮廓进行多边形拟合,使其由图象转换为图形,以便为后续排样工作提供方便。
  5. Segmentation of chromosome : the chromosome image is segmented by the method of boundary gray level threshold and entropy algorithm based on genetic algorithm , then , after boundary smoothing and edge tracing , the chromosome position information is acquired . 2 . diagnostic extraction of chromosome : on the basis of skeleton pixel after thinning , the medial axes are obtained by the orthogonal approximation
    主要研究内容如下: 1 、染色体图像分割:采用基于边界灰度的门限算法和基于遗传算法的熵算法来寻找染色体图像二值化需要的分割阈值,对分割后的图像存在的噪声分别采用内插来置换和边界跟踪来消除; 2 、染色体特征提取:采用细化技术将染色体细化一些离散的骨架点,用插值方法获得平滑的曲线染色体中线。
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