Abstract
The detection of stable, distinctive and rich feature point sets has been an active area of research in the field of video and image analysis. Transparency imaging, such as X-ray, has also benefited from this research. However, an evaluation of the performance of various available detectors for this type of images is lacking. The differences with natural imaging stem not only from the transparency, but -in the case of medical X-ray- also from the non-planarity of the scenes, a factor that complicates the evaluation. In this paper, a method is proposed to perform this evaluation on non-planar, calibrated X-ray images. Repeatability and accuracy of nine interest point detectors is demonstrated on phantom and clinical images. The evaluation has shown that the Laplacian-of-Gaussian and Harris-Laplace detectors show overall the best performance for the datasets used.
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References
Schmid, C., Mohr, R., Bauckhage, C.: Evaluation of interest point detectors. International Journal of Computer Vision 37(2), 151–172 (2000)
Remondino, F.: Detectors and descriptors for photogrammetric applications. In: ISPRS III (2006)
Mokhtarian, F., Mohanna, F.: Performance evaluation of corner detectors using consistency and accuracy measures. Computer Vision and Image Understanding 102(1), 81–94 (2006)
Heyden, A., Rohr, K.: Evaluation of corner extraction schemes using invariance methods. In: International Conference on Pattern Recognition, vol. 1, p. 895 (1996)
Moreels, P., Perona, P.: Evaluation of features detectors and descriptors based on 3d objects. International Journal of Computer Vision 73(3), 263–284 (2007)
Chen, Q., Medioni, G.G.: Efficient iterative solution to m-view projective reconstruction problem. In: CVPR, pp. 2055–2061 (1999)
Farin, D.: Automatic video segmentation employing object/camera modeling techniques. PhD thesis (2005)
Shi, J., Tomasi, C.: Good features to track. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1994, pp. 593–600 (1994)
Harris, C., Stephens, M.: A combined corner and edge detection. In: Proc. of 4th Alvey Vision Conference, pp. 147–151 (1988)
Smith, S.M., Brady, J.M.: Susan-a new approach to low level image processing. International Journal of Computer Vision, 45–78 (1997)
Lindeberg, T.: Feature detection with automatic scale selection. International Journal of Computer Vision 30, 79–116 (1998)
Bay, H., Tuytelaars, T., Van Gool, L.: Surf: Speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)
Mikolajczyk, K., Schmid, C.: An affine invariant interest point detector. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2350, pp. 128–142. Springer, Heidelberg (2002)
Shilat, F., Werman, M., Gdalyahn, Y.: Ridge’s corner detection and correspondence. In: Computer Vision and Pattern Recognition, p. 976 (1997)
Maintz, J.B.A., van den Elsen, P.A., Viergever, M.A.: Evaluation of ridge seeking operators for multimodality medical image matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(4), 353–365 (1996)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60, 91–110 (2004)
Mikolajczyk, K., Schmid, C.: Scale & affine invariant interest point detectors. International Journal of Computer Vision 60(1), 63–86 (2004)
Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2004)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005)
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Papalazarou, C., Rongen, P.M.J., de With, P.H.N. (2009). Evaluation of Interest Point Detectors for Non-planar, Transparent Scenes. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2009. Lecture Notes in Computer Science, vol 5807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04697-1_1
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DOI: https://doi.org/10.1007/978-3-642-04697-1_1
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