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Underwater Dam Crack Image Enhancement Algorithm Based on Rough Set

  

  1. College of Internet of Things Engineering, Hohai University, Changzhou 213022, China
  • Received:2015-04-16 Online:2015-09-21 Published:2015-09-24

Abstract:

 In view of the complex environmental conditions of underwater image acquisition for the dam cracks, such as the light scattering and attenuation caused by water
led to the low signal to noise ratio of image, the extremely uneven of light distribution as well as fracture texture weakening,this paper proposes an adaptive enhancement
algorithm, which adopts the discovery and classification rules of rough sets. This algorithm takes the congenital advantage of rough set when mining data for useful information.
On the base of rough set theory,we divide the defect images according to the equivalence relation, which can be used to calculate brightness layer by using upper approximation
and lower approximation, then enhance the texture of the crack image layer by layer. Further more, in order to feedback the best number of layers we introduce approximate
classification accuracy and system parameters importance. Finally,by calculating their value and analyzing their convergence we can get the best adaptive dam crack enhancement
image.The simulation results verify the effectiveness of the algorithm.

Key words: image enhancement； rough set； approximate classification accuracy, adaptive