TWO-LEVEL STRATEGY FOR IMAGE BOUNDARY DETECTION

Karin S. Komati, Evandro O. T. Salles, Mario Sarcinelli-Filho

Abstract

A new method for boundary detection in natural images is here proposed, consisting of two levels, or two-stage sequential processes: embedded integration and post-processing integration. In the embedded integration, two different methods to measure homogeneity in region-growing technique are integrated, based on a global statistical property: the shape of the power spectrum of the image being analyzed. One homogeneity measure is the J value (provided by the classical JSEG algorithm) and the second measure is a multifractal measurement. This first step provides a region extraction. In the second level, edge information is extracted by a classical method, and integrated with region information. This structure, called KSS, eliminates false boundaries in the region map, guided by the edge map, and the noise in edge map as well, now guided by the region map, thus taking the advantage of their complementary nature. Experiments on a large dataset of natural color images show that the result of such two-level strategy matches the human perception better than the individual methods, quantitatively and qualitatively speaking.

References

  1. Chaudhuri, B. B.; Sarkar, N., 1995. Texture segmentation using fractal dimension, IEEE Trans. Pattern Anal. Mach. Intell., 17 (1), 72-77.
  2. Côco, K. F., Salles, E. O. T., Sarcinelli-Filho, M., 2009. Topographic independent component analysis based on fractal and morphology applied to texture segmentation, Lecture Notes in Computer Science, 5441, 491-498.
  3. Deng, Y., Manjunath, B. S., 2001. Unsupervised segmentation of color-texture regions in images and video, IEEE Trans. Pattern Anal. Mach. Intell., 23 (8).
  4. Komati, K. S., Salles, E. O. T., Sarcinelli-Filho, M., 2010. Unsupervised color image segmentation based on local fractal dimension, In Proc. 17th International Conference on Systems, Signals and Image Processing (IWSSIP 2010), 1, 243-246.
  5. Komati, K. S., Salles, E. O. T., Sarcinelli-Filho, M., in press. A Strategy for Image Boundary Detection Combining Region and Edge Maps, Computing in Science and Engineering, IEEE computer Society Digital Library. doi: 10.1109/MCSE.2010.148.
  6. Martin, D., Fowlkes, C., Tal, D., Malik, J., 2001. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics, In Proc. 8th IEEE Intl Conf. Computer Vision, 2, 416-423.
  7. Martin, D. R., Fowlkes, C. C., Malik, J., 2004. Learning to detect natural image boundaries using local brightness, color, and texture cues, IEEE Trans. Pattern Anal. Mach. Intell., 26(5), 530-549, 2004.
  8. Muñoz, X., Freixenet, J., Cufí, X., Martí, J., 2003. Strategies for image segmentation combining region and boundary information, IEEE Pattern Recognition Letters, 24(1-3), 375-392.
  9. Pentland, A. P., 1984 Fractal-based description of natural scenes. IEEE Trans. on Pattern Analysis and Machine Intelligence, 6.
  10. Rotem, O., Greenspan, H., Goldberger, J., 2007. Combining Region and Edge Cues for Image Segmentation in a Probabilistic Gaussian Mixture Framework. In Proc 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8.
  11. Torralba, A., Oliva, A., 2003. Statistics of natural image categories, Institute of Physics Publishing: Computation in Neural Systems, 14, 391-412.
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Paper Citation


in Harvard Style

Komati K., Salles E. and Sarcinelli-Filho M. (2011). TWO-LEVEL STRATEGY FOR IMAGE BOUNDARY DETECTION . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011) ISBN 978-989-8425-47-8, pages 181-186. DOI: 10.5220/0003375801810186


in Bibtex Style

@conference{visapp11,
author={Karin S. Komati and Evandro O. T. Salles and Mario Sarcinelli-Filho},
title={TWO-LEVEL STRATEGY FOR IMAGE BOUNDARY DETECTION },
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)},
year={2011},
pages={181-186},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003375801810186},
isbn={978-989-8425-47-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)
TI - TWO-LEVEL STRATEGY FOR IMAGE BOUNDARY DETECTION
SN - 978-989-8425-47-8
AU - Komati K.
AU - Salles E.
AU - Sarcinelli-Filho M.
PY - 2011
SP - 181
EP - 186
DO - 10.5220/0003375801810186