Edge detection in petrographic images

The automatic detection of mineral grain boundaries in images obtained from a polarized‐light microscope requires special techniques. Observations in both plane‐ and cross‐polarized light may be necessary and the section must be rotated relative to the plane of polarization of the microscope to see all the grain boundaries. In computer‐based microscopy this can be accomplished by the sequential accumulation of individual images captured from one microscope field of view with different polarizer orientations.

[1]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[2]  Peter de Souza,et al.  Edge detection using sliding statistical tests , 1983, Comput. Vis. Graph. Image Process..

[3]  Ellen C. Hildreth,et al.  The detection of intensity changes by computer and biological vision systems , 1983, Comput. Vis. Graph. Image Process..

[4]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Jun S. Huang,et al.  Statistical theory of edge detection , 1988, Comput. Vis. Graph. Image Process..

[6]  Margaret M. Fleck Multiple widths yield reliable finite differences , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[7]  Amlan Kundu Robust edge detection , 1990, Pattern Recognit..

[8]  K.J. Cios,et al.  An edge extraction technique for noisy images , 1990, IEEE Transactions on Biomedical Engineering.

[9]  Margaret M. Fleck Some Defects in Finite-Difference Edge Finders , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Margaret M. Fleck Multiple Widths Yield Reliable Finite Differences (Computer Vision) , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Svetha Venkatesh,et al.  Edge evaluation using necessary components , 1992, CVGIP Graph. Model. Image Process..