Active contour

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Snakes , also known as active contours , are a concept that is used in digital image processing to determine an object contour. In practice, Snake algorithms are mainly used in medical image processing, for example in diagnostics for ultrasound recordings . They are used for computer-aided object tracking and are invariant with regard to scaling and rotation.

The concept is based on the description of the object contour using a parametric curve . Their shape is corrected after an often manual initialization depending on so-called internal and external energies . The external energies are calculated from the image content in relation to the position of the contour . A form of the gradient is often used here ( gradient vector flow ). The internal energies are only calculated from the shape of the contour. A minimization algorithm is used to calculate the shape of the contour in which the sum of all energies reaches a minimum. Instead of actually performing the minimization, the shape of the snake can also be changed very often and then that shape can be viewed as the result in which the sum of the energies is minimal.

The first publication on snakes is the work of M. Kass, A. Witkin and Demetri Terzopoulos . Since then, numerous other articles have followed. a. Propose new types of energy functional or new approaches to minimize the total energy.

software

The algorithm is implemented in the free image processing libraries Scikit-image and OpenCV .

See also

literature

  • Kerstin Wolsiffer: Design and implementation of an interactive VR-based tool for segmentation and visualization of medical volume data . In: mbi Technical Report . No. 90 , 1996, pp. 5-18 .

Web links

Individual evidence

  1. ^ M. Kass, A. Witkin, D. Terzopoulos: Snakes: active contour models . In: International Journal for Computer Vision , 1988
  2. Active Contour Model - skimage docs. Retrieved September 13, 2018 .
  3. ^ OpenCV: Contours: Getting Started. Retrieved September 16, 2018 .