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Normalized Cut Based Edge Detection

  • Mario Barrientos
  • Humberto Madrid
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6718)

Abstract

This work introduces a new technique for edge detection based on a graph theory tool known as normalized cut. The problem involves to find certain eigenvector of a matrix called normalized laplacian, which is constructed in such way that it represents the relation of color and distance between the image’s pixels. The matrix dimensions and the fact that it is dense represents a trouble for the common eigensolvers. The power method seemed a good option to tackle this problem. The first results were not very impressive, but a modification of the function that relates the image pixels lead us to a more convenient laplacian structure and to a segmentation result known as edge detection. A deeper analysis showed that this procedure does not even need of the power method, because the eigenvector that defines the segmentation can be obtained with a closed form.

Keywords

Edge detection normalized cut power method image segmentation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mario Barrientos
    • 1
  • Humberto Madrid
    • 1
  1. 1.Applied Mathematics Research CenterAutonomous University of CoahuilaSaltilloMexico

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