Evaluating a colour morphological scale-space

Scale-spaces are usually associated with the diffusion equation operating on greyscale images. This paper presents a scale-space that is based on graph morphology and works in colour. The system is shown to be a natural extension of the existing greyscale graph-morphology scale-spaces. The system is evaluated by comparing it to a specially collected database of ground-truth images created by human subjects.

[1]  Y. J. Zhang,et al.  A survey on evaluation methods for image segmentation , 1996, Pattern Recognit..

[2]  Henk L. Muller,et al.  Evaluating image segmentation algorithms using monotonic hulls in fitness/cost space , 2001, BMVC.

[3]  J A Bangham,et al.  Data-sieving hydrophobicity plots. , 1988, Analytical biochemistry.

[4]  Jan J. Koenderink,et al.  Color Differential Structure , 2001, Scale-Space.

[5]  Arnold W. M. Smeulders,et al.  The Morphological Structure of Images: The Differential Equations of Morphological Scale-Space , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  J. Andrew Bangham,et al.  Scale-Space Filters and Their Robustness , 1997, Scale-Space.

[7]  Jitendra Malik,et al.  A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[8]  Kimberly Moravec,et al.  Scale trees for stereo vision , 2000 .

[9]  J. Koenderink.  The structure of images , 2004, Biological Cybernetics.

[10]  J. Andrew Bangham,et al.  Morphological scale-space preserving transforms in many dimensions , 1996, J. Electronic Imaging.

[11]  Jiri Matas,et al.  Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..

[12]  Graham D. Finlayson,et al.  Convex Colour Sieves , 2003, Scale-Space.

[13]  Martin J. Turner,et al.  Efficient Lossless Image Contour Coding , 1996, Comput. Graph. Forum.

[14]  Philippe Salembier,et al.  Binary partition tree as an efficient representation for filtering, segmentation and information retrieval , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).

[15]  Andrew W. Fitzgibbon,et al.  An Experimental Comparison of Range Image Segmentation Algorithms , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Paul H. Lewis,et al.  Content-based image retrieval with scale-space object trees , 1999, Electronic Imaging.

[17]  Philippe Salembier,et al.  Binary partition tree as an efficient representation for image processing, segmentation, and information retrieval , 2000, IEEE Trans. Image Process..

[18]  Gavin C. Cawley,et al.  The Segmentation of Images via Scale-Space Trees , 1998, BMVC.

[19]  Philippe Salembier,et al.  Flat zones filtering, connected operators, and filters by reconstruction , 1995, IEEE Trans. Image Process..

[20]  Mohamed A. Deriche,et al.  Scale-Space Properties of the Multiscale Morphological Dilation-Erosion , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Andrew P. Witkin,et al.  Scale-Space Filtering , 1983, IJCAI.

[22]  Adam Krzyzak,et al.  Robust Estimation for Range Image Segmentation and Reconstruction , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  D. W. Scott.  On optimal and data based histograms , 1979 .

[24]  Edward J. Delp,et al.  Morphological operations for color image processing , 1999, J. Electronic Imaging.

[25]  Refractor.  Vision , 2000, The Lancet.

[26]  Tony Lindeberg,et al.  Scale-Space Theory in Computer Vision , 1993, Lecture Notes in Computer Science.

[27]  J. Astola,et al.  Vector median filters , 1990, Proc. IEEE.

[28]  Ron Kimmel,et al.  From High Energy Physics to Low Level Vision , 1997, Scale-Space.

[29]  Bart M. ter Haar Romeny,et al.  Geometry-Driven Diffusion in Computer Vision , 1994, Computational Imaging and Vision.

[30]  Scott T. Acton,et al.  Scale space classification using area morphology , 2000, IEEE Trans. Image Process..