Three Dimensional Shape Recovery from Blurred Images

  • Kyeongwan Roh (Dept. of Computer Engineering ,Chosun University) ;
  • Kim, Choongwon (Dept. of Computer Engineering ,Chosun University) ;
  • Lee, Gueesang (Dept. of Computer Science, Chonnam National University) ;
  • Kim, Soohyung (Dept. of Computer Science, Chonnam National University)
  • Published : 2000.07.01

Abstract

There are many methods that extract the depth information based on the blurring ratio for object point in DFD(Depth from Defocus). However, it is often difficult to measure the depth of the object in two-dimensional images that was affected by various elements such as edges, textures, and etc. To solve the problem, new DFD method employing the texture classification with a neural network is proposed. This method extracts the feature of texture from an evaluation window in an image and classifies the texture class. Finally, It allocates the correspondent value for the blurring ratio. The experimental result shows that the method gives more accurate than the previous methods.

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