Image Segmentation Based on Active Contours without Edges

Information

• Publication Type: Conference Paper
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: August 2012
• Location: Cluj-Napoca, Romania
• Lecturer: Anca Morar
• Event: 8th IEEE International Conference on Intelligent Computer Communication and Processing 2012
• Booktitle: IEEE ICCP 2012 - Proceedings
• Conference date: 30. August 2012 – 1. September 2012
• Pages: 213 – 220
• Keywords: Active contours without edges, image segmentation, nonlinear anisotropic diffusion, parallel image processing

Abstract

There are a lot of image segmentation techniques that try to differentiate between background and object pixels, but many of them fail to discriminate between different objects that are close to each other. Some image characteristics like low contrast between background and foreground or inhomogeneity within the objects increase the difficulty of correctly segmenting images. We designed a new segmentation algorithm based on active contours without edges. We also used other image processing techniques such as nonlinear anisotropic diffusion and adaptive thresholding in order to overcome the images’ problems stated above. Our algorithm was tested on very noisy images, and the results were compared to those obtained with known methods, like segmentation using active contours without edges and graph cuts. The new technique led to very good results, but the time complexity was a drawback. However, this drawback was significantly reduced with the use of graphical programming. Our segmentation method has been successfully integrated in a software application whose aim is to segment the bones from CT datasets, extract the femur and produce personalized prostheses in hip arthroplasty.

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BibTeX

@inproceedings{Morar_2012_ISB,
  title =      "Image Segmentation Based on Active Contours without Edges",
  author =     "Anca Morar and Florica Moldoveanu and Eduard Gr\"{o}ller",
  year =       "2012",
  abstract =   "There are a lot of image segmentation techniques that try to
               differentiate between background and object pixels, but many
               of them fail to discriminate between different objects that
               are close to each other. Some image characteristics like low
               contrast between background and foreground or inhomogeneity
               within the objects increase the difficulty of correctly
               segmenting images. We designed a new segmentation algorithm
               based on active contours without edges. We also used other
               image processing techniques such as nonlinear anisotropic
               diffusion and adaptive thresholding in order to overcome the
               images’ problems stated above. Our algorithm was tested on
               very noisy images, and the results were compared to those
               obtained with known methods, like segmentation using active
               contours without edges and graph cuts. The new technique led
               to very good results, but the time complexity was a
               drawback. However, this drawback was significantly reduced
               with the use of graphical programming. Our segmentation
               method has been successfully integrated in a software
               application whose aim is to segment the bones from CT
               datasets, extract the femur and produce personalized
               prostheses in hip arthroplasty.",
  month =      aug,
  location =   "Cluj-Napoca, Romania",
  event =      "8th IEEE International Conference on Intelligent Computer
               Communication and Processing 2012",
  booktitle =  "IEEE ICCP 2012 - Proceedings",
  pages =      "213--220",
  keywords =   "Active contours without edges, image segmentation, nonlinear
               anisotropic diffusion, parallel image processing",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2012/Morar_2012_ISB/",
}