邊割集 的英文怎麼說
中文拼音 [biāngējí]
邊割集
英文
edge cut set-
Further more, this algorithm also provides the criterion distinguishing edge inflexion and sleek curve section and the method computing inaccurately curvature radius and approximate perimeter. the paper also introduces the use method with cell edge hollow repairing and overlap or conglutination cell segmentation. for example, this algorithm has proved high - speed and has a good effect of cell segmentation on more than twenty groups of conglutinate and absent cells which are gathered from three kinds of cells
同時給出了利用這些參數判別邊界角點，邊界光滑段的判據，以及估算曲率半徑，等效周長的方法;最後，以細胞邊界凹陷的修補和重疊細胞粘連的分割為例驗證了演算法的可行性，該演算法在採集到的30餘組粘連和缺損細胞上進行了驗證，結果表明，該演算法處理速度快，分割效果良好。Following the characteristics of medical image segmentation, this paper proposed a new spline geometric deformable model ( sgdm ), which can be presented as a set of ordered vertices connected by edges
摘要根據醫學圖像分割的特點，建立了一種樣條幾何形變模型，它表示為一個有序的用邊線連接的頂點集合。This paper illustrates detailedly the thin groupware auto - adaptive recognition system ; it also illlustrates the procession of capture image and take indispensable foreclose to wipe off noise in order to get boundary easilyer. the recognition system uses " hough " transform method to make the recognition area orientation, and according to the unstable environment such as lights which leads to the change of the image ' s brightness, thresholds picture using an iterative selection method and then growing process for cell image segmentation based on local color similarity and global shape criteria, adaptively gets the best threshold to divide the washer off the background. the recognition system uses the classifier based on minimal - error - ratio bayes method to make decision after getting image characteristic
本文詳細介紹了薄形組合件自適應識別系統；闡明了圖像的分通道自動採集過程，以及對採集到的原始圖像所進行的預處理方法。通過採用哈夫變換去除偽邊緣點的方法，有效地解決了識別區域的定位問題。針對裝配零件（主要是墊片）薄、小導致圖像信息少、識別難度大，以及材質不一導致採集到的組合件圖像亮度波動等問題，提出了使用最佳閾值迭代法和使用種子填充的圖像串列分割技術，自適應地找出最佳閡值，使墊片和背景分離，從而提取墊片數目信息。By the theoretical analysis and experimental test, the image processing procedure of the system has been designed. firstly, the system needs carry out pre - process : the median filtering and average filtering of acquired image, next carrying out the threshold of filtered image, then performing morphology, such as open, close and so on. next, the boundary of binary image is extracted
通過理論分析與實驗驗證，得到了本系統圖像處理過程:首先對採集的圖像進行預處理，包括均值中值濾波，通過閾值分割進行二值化，然後對二值圖像進行開啟、閉合以及進行邊界提取操作來獲得清晰的圖像邊緣，最後通過邊緣檢測和擬合測量得到沖擊試樣各尺寸值，圖像坐標變換和模式匹配可以完成檢測區域定位。The welding position can be detected accurately through processing the image of arc area collected by the vision sensor ccd ( charge coupled device ), by the system of image collection and computer - ware, we can recognize the position of the welding line exactly, count out the warp between moving track of robot and the welding line. so we can control the robot ' s act real - timely, the seam tracking accuracy is enhanced efficiently
重點論述焊縫圖像分割和邊緣提取的理論方法，焊縫圖像由面陣ccd攝像系統攝取，通過圖像採集系統和計算機軟體，對檢測到的弧焊區圖像進行處理來準確地識別焊縫位置，計算機器人的運動軌跡和實際焊縫之間的偏差，據此控制機器人運動進行實時跟蹤，從而有效地提高焊縫跟蹤精度。Using vc + + 6. 0 as the development platform, the system combines the common processing and analyzing image by means of image geometry change, process enhancement, edge detection, region segmentation, feature extraction and so on. based on the image processing and recognition, the system realizes the functions of color recognition, shape recognition and inspection under the laboratorial environment
課題主要使用的開發平臺為vc + + 6 . 0 。系統集成了圖像處理和分析的常用演算法，包括圖像的幾何操作，圖像的增強操作，圖像的邊緣檢測演算法、圖像區域分割、圖像的形狀參數提取等;並在此基礎上實現了實驗環境下零件顏色識別，形狀識別和缺陷檢測等功能。This paper clarifies image collect automatically process of multi - channels, and pre - processing process of original image in order to noise reduction. in image processing, method as follows will be introduced in this paper : a method combining image threshold iterative segmentation with threshold interpolation, edge detection operator sobel and log, edge linking method using delation operator based on mathematical morphology, using boundary tracking and projection method in edge distill process. through this method, measurement of wheelset will be met precision demand
本文闡明了圖像的分通道自動採集過程，以及對採集到的原始圖像進行預處理過程，達到圖像去噪聲的目標，本課題採用了閾值分割中迭代閾值和閾值插值相結合的方法， sobel運算元、 log運算元邊緣檢測演算法，基於數學形態學的膨脹運運算元進行邊緣斷點連接以及目標提取中的投影法和邊緣跟蹤方法，使得提取輪對圖像邊緣達到測量精度的要求。分享友人