Context-free multiple-object segmentation using attention operator based on modified generalized symmetry transform

일반화 대칭변환을 변형한 관심 연산자에 의한 사전 정보없는 다중 물체 분할

  • 구태모 (경동전문대학 전자계산과) ;
  • 전준형 (경북대학교 전자전기 공학부) ;
  • 최흥문 (경북대학교 전자전기 공학부)
  • Published : 1997.04.01

Abstract

An efficient context-free multiple-object segmentation using attention operator based on modified generalized symmetry transform is proposed and implemented by modifying a radial basis function network. By using the difference of intensity gradient, instead of te intensity gradient itself, in generalized symmetry tranform so as to make the attention operator to preserve the edges of the objects shape, an efficient context-free multiple-object segementation is proposed in which no a priori shape informtion on the objects is requried. The attention operator is implemented by using a modified radial basis function network which can reflect symmetry, and by using te edge pyramid of the input image, both of the local and the global symmetry of the objects are reflected simultaneously to make the multiple-object with different sizes be segmented with a singel fixed-size $n\timesm$ can be done with O(n) complexity. The simulaton results show that the proposed algorithm can efficiently be used in context-free multiple-object segmentation even for the low contrast IR images as well as for the images from the camera.

Keywords