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A novel trignometric energy functional for image segmentation in the presence of intensity in-homogeneity

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

  • Sajid Hussain, Xi'an Jiaotong University
  • ,
  • Qi Chun, Xi'an Jiaotong University
  • ,
  • Muhammad Rizwan Asif
  • Muhammad Sohrab Khan
  • ,
  • Zhang Zhaoqiang, Xi'an Jiaotong University
  • ,
  • Muhammad Sadiq Fareed, Xi'an Jiaotong University
  • ,
  • Zhang Zhe, Xi'an Jiaotong University

A novel region based Active Contour Model (ACM) for image segmentation is presented using image local information for intensity inhomogeneity images. A transcendental (trigonometric) energy functional based on Local Fitted Image (LFI) energy is suggested to extract the image local information. The difference between the original and fitting image is introduced as an angular constraint of the trigonometric function. This new approach has the ability to handle images with severe intensity inhomogeneity, multiple intensity classes and regions with non-homogeneous pixel intensities. To regularize and maintain the level set function, Gaussian filtering procedure is adopted that not only maintains the level set consistency but also eliminates re-initialization procedure to avoid computational complexity. Furthermore, the proposed model holds boundary regularization property and achieves sub-pixel accuracy. Experimental results on several real and synthetic images demonstrate that the proposed model has higher performance and better accuracy in comparison to the state-of-the-art models.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Multimedia and Expo, ICME 2016
PublisherIEEE Computer Society
Publication year25 Aug 2016
Article number7552994
ISBN (Electronic)9781467372589
Publication statusPublished - 25 Aug 2016
Event2016 IEEE International Conference on Multimedia and Expo, ICME 2016 - Seattle, United States
Duration: 11 Jul 201615 Jul 2016


Conference2016 IEEE International Conference on Multimedia and Expo, ICME 2016
LandUnited States
SeriesProceedings - IEEE International Conference on Multimedia and Expo

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

    Research areas

  • Active Contour, Chan-Vese Model, Image segmentation, LBF Model, level set

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