An Image Segmentation Assessment Tool ISAT 1.0

Anton Mazhurin, Nawwaf Kharma

Abstract

This paper presents algorithms and their software implementation, which assess the quality of segmentation of any image, given an ideal segmentation (or ground truth image) and a usually less-than-ideal segmentation result (or machine segmented image). The software first identifies every region in both the ground truth and machine segmented images, establishes as much correspondence as possible between the images, then computes two sets of measures of quality: one, region-based and the other, pixel-based. The paper describes the algorithms used to assess quality of segmentation and presents results of the application of the software to images from the Berkeley Segmentation Dataset. The software, which is freely available for download, facilitates R&D work in image segmentation, as it provides a tool for assessing the results of any image segmentation algorithm, allowing developers of such algorithms to focus their energies on solving the segmentation problem, and enabling them to tests large sets of images, swiftly and reliably.

References

  1. Berkley Segmentation Dataset and Benchmark, http://www.eecs.berkeley.edu/Research/Projects/CS/vi sion/bsds/ (last accessed: July 30, 2012).
  2. Bushberg, J. T., Seibert, J. A., Leidholdt, E. M., Boone, J.M., 2002. The essential Physics of Medical Imaging, published by Lippincott Williams & Wilkins, Philadelphia, pp. 288-290.
  3. Cardoso, J. S.; Corte-Real, L., 2005. Toward a generic evaluation of image segmentation. IEEE Transactions on Image Processing, vol.14, no.11, pp.1773-1782.
  4. Francisco, E. and Jepson, A., 2009. Benchmarking Image Segmentation Algorithms. International Journal of Computer Vision, vol. 85, issue 2, pp. 167-181.
  5. Hoover, A., Gillian, J.-B., Jiang, X., Flynn, P.J., Bunke, H., Goldgof, D., Bowyer, K., Eggert, D.W., Fitzgibbon, A., Fisher, R.B. 1996. An experimental comparison of range image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, no.7, pp.673-689.
  6. Hui Zhang, H., Fritts, J. E., Goldman, S.A., 2008. Image Segmentation Evaluation: A Survey of Unsupervised Methods. Computer Vision and Image Understanding, vol.110, no.2, pp. 260-280.
  7. Jiang, X., Marti, C., Irniger, C. and Bunke, H., 2006. Distance measures for image segmentation evaluation. EURASIP Journal on Applied Signal Processing, vol. 2006, pp. 1-10.
  8. McGuiness, K. and O'Connor, N. E., 2011. Toward Automated Evaluation of Interactive Segmentation. Computer Vision and Image Understanding, vol. 115 no. 6, pp. 868-884.
  9. Singh, T., Kharma, N., Daoud, M. and Ward, R., 2009. Genetic programming based image segmentation with applications to biomedical object detection. Proceedings of the 11th Annual conference on Genetic and evolutionary computation (GECCO 7809). ACM, New York, NY, USA, 1123-1130.
  10. Unnikrishnan, R., Pantofaru, C., Hebert, M., 2007. Toward Objective Evaluation of Image Segmentation Algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, no.6, pp.929-944.
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Paper Citation


in Harvard Style

Mazhurin A. and Kharma N. (2013). An Image Segmentation Assessment Tool ISAT 1.0 . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 436-443. DOI: 10.5220/0004216404360443


in Bibtex Style

@conference{visapp13,
author={Anton Mazhurin and Nawwaf Kharma},
title={An Image Segmentation Assessment Tool ISAT 1.0},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={436-443},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004216404360443},
isbn={978-989-8565-47-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - An Image Segmentation Assessment Tool ISAT 1.0
SN - 978-989-8565-47-1
AU - Mazhurin A.
AU - Kharma N.
PY - 2013
SP - 436
EP - 443
DO - 10.5220/0004216404360443