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치아 영상의 반사 제거 및 치아 영역 자동 분할

Individual Tooth Image Segmentation with Correcting of Specular Reflections

  • 이성택 (건국대 의학공학부) ;
  • 김경섭 (건국대 의료생명대 의학공학부, 건국대 의공학실용기술연구소) ;
  • 윤태호 (건국대 의학공학부) ;
  • 이정환 (건국대 의료생명대 의학공학부) ;
  • 김기덕 (연세대 치과대학병원 통합진료과) ;
  • 박원서 (연세대 치과대학병원 통합진료과)
  • 투고 : 2010.04.26
  • 심사 : 2010.05.11
  • 발행 : 2010.06.01

초록

In this study, an efficient removal algorithm for specular reflections in a tooth color image is proposed to minimize the artefact interrupting color image segmentation. The pixel values of RGB color channels are initially reversed to emphasize the features in reflective regions, and then those regions are automatically detected by utilizing perceptron artificial neural network model and those prominent intensities are corrected by applying a smoothing spatial filter. After correcting specular reflection regions, multiple seeds in the tooth candidates are selected to find the regional minima and MCWA(Marker-Controlled Watershed Algorithm) is applied to delineate the individual tooth region in a CCD tooth color image. Therefore, the accuracy in segmentation for separating tooth regions can be drastically improved with removing specular reflections due to the illumination effect.

키워드

참고문헌

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