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3D edge detection by separable recursive filtering and edge closing. Author: Monga , O.; Deriche , R.; Malandain , G.; Cocquerez , J.P. Source: Pattern Recognition, 1990. Proceedings., 10th International Conference , Page(s): 652 - 654 Student: Jia – Hong Chen Advisor: Ku – Yaw Chang.

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3d edge detection by separable recursive filtering and edge closing

3D edge detection by separable recursive filtering and edge closing

Author: Monga, O.; Deriche, R.; Malandain, G.; Cocquerez, J.P.

Source: Pattern Recognition, 1990. Proceedings., 10th International Conference , Page(s): 652 - 654

Student: Jia – Hong Chen

Advisor: Ku – Yaw Chang

outline
Outline
  • Introduction
  • A 3D edge detection scheme
  • Closing 3D edges
  • Conclusion
introduction
Introduction
  • 3D edge detectors are issued
    • a generalization in 3D of 2D edge detectors
  • we propose an unified formalism for 3D edge detection
    • recursive filters
    • tracking/closing algorithm
outline1
Outline
  • Introduction
  • A 3D edge detection scheme
  • Closing 3D edges
  • Conclusion
a 3d edge detection scheme
A 3D edge detection scheme
  • Canny演算法
    • Step1: smoothing,降低雜訊
    • Step2:找邊緣,求梯度的強度
    • Step3: hysteresis
a 3d edge detection scheme1
A 3D edge detection scheme
  • Step1: smoothing
    • 使用Gaussian filter,在Gaussian filter函式中使用到variance來調整Gaussian filter的值
a 3d edge detection scheme5
A 3D edge detection scheme
  • Step2:找邊緣,求梯度的強度
    • 使用Sobel method找出邊緣,他會先計算出每一個像素的值再利用求出梯度
    • 另外利用求出梯度方向
a 3d edge detection scheme6
A 3D edge detection scheme
  • 1st Derivative (Gradient)
a 3d edge detection scheme11
A 3D edge detection scheme
  • Step3: hysteresis
    • 設定2個門檻值T1和T2,由G得到的結果,任何像素如果大於T1則被認定為邊緣像素,而在這個邊緣像素鄰近的點如果有大於T2也會被認定為邊緣像素.
outline2
Outline
  • Introduction
  • A 3D edge detection scheme
  • Closing 3D edges
  • Conclusion
closing 3d edges
Closing 3D edges
  • It is often very difficult
    • select adequate thresholds for the thresholding stage
    • High thresholds allows to remove noisy edge points but also true edge points
    • low thresholds allow to obtain all true edge points but also noisy edge points
closing 3d edges1
Closing 3D edges
  • Generally it is easier
    • extend uncompleted contours thanvalidate true contours in a noisy edge image
  • choose high thresholds
    • remove false edge points
    • use atracking/closing algorithm
closing 3d edges2
Closing 3D edges
  • Deriche and Cocquerez
    • 2D edge closing method proposed
    • supposes that it is possible to recognize endpoints of contours
      • Examination of a neighbourhood 3 x 3 of an edge point
  • The implementation of this algorithm is easy
    • if an edge point is identified as an extremity the algorithm is applied recursively to the involved extremity until a stop condition is verified
closing 3d edges3
Closing 3D edges
  • The 3D extension of this algorithm
    • applying it on each plane XY, YZ, ZX
    • adding the three edge images obtained
  • This can be justified by the assumption
    • the intersection of a 3D surface by at least one plane among XY,YZ and ZX
closing 3d edges4
Closing 3D edges
  • it remains some localized information lacks
    • cause holes of width 1 along X,Y or Z
  • To solve this problem
    • select the codes corresponding to holes of width 1
    • 2D implementation consists in scanning the image
    • fill up each identified hole
outline3
Outline
  • Introduction
  • A 3D edge detection scheme
  • Closing 3D edges
  • Conclusion
conclusion
Conclusion
  • We have proposed a 3D edge detection scheme
  • saving in computational effort is of great interest
  • Currently we investigate true 3D closing edge methods