Image classification and delineation of fragments

  • Authors:

  • Weixing Wang

  • Affiliations:

  • Department of Computer Science & Technology, Chongqing University of Posts & Telecommunications, China

  • Venue:
  • CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
  • Year:
  • 2005

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Abstract

This paper shows that an algorithm technique involving image classification and valley-edge based image segmentation is a highly efficient way of delineating densely packed rock fragments. No earlier work on segmentation of rock fragments has exploited these two building blocks for making robust segmentation. Our method has been tested experimentally for different kinds of closely packed fragment images which are difficult to detect by ordinary edge detections. The reason for the powerfulness of the technique is that image classification (knowledge of scale) and image segmentation are highly cooperative processes. Moreover, valley-edge detection is a nonlinear filter picking up evidence of valley-edge by only considering the strongest response for a number of directions. As tested, the algorithm can be applied into other applications too.