• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.337-339
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• 2006

이동 카메라 환경에서의 객체 추적은 배경과 객체의 동시 이동으로 인친 배경 모델링과 같은 고정 카메라 환경에서의 접근방법으로는 해결이 어려운 문제이다. 또한 다중 객체의 추적에서는 객체간 가려짐이 발생하는 상황에 대한 안정적 기법이 필수적으로 요구된다. 본 연구에서는 커널에 기반한 객체의 표현과 Mean shift 알고리즘을 통해 여러 명의 사람을 실시간으로 추적하고, 객체간의 공간 정보와 확률적 유사도에 기반한 객체간의 가려짐의 발생과 가려짐 후의 복원에 대한 방법을 제안하였다.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.205-210
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• 2008

A new approach is proposed for restoration of corrupted regions and segmentation in natural text images. The challenge is to fill in the corrupted regions on the basis of color feature analysis by second order symmetric stick tensor. It is show how feature analysis can benefit from analyzing features using tensor voting with chromatic and achromatic components. The proposed method is applied to text images corrupted by manifold types of various noises. Firstly, we decompose an image into chromatic and achromatic components to analyze images. Secondly, selected feature vectors are analyzed by second-order symmetric stick tensor. And tensors are redefined by voting information with neighbor voters, while restore the corrupted regions. Lastly, mode estimation and segmentation are performed by adaptive mean shift and separated clustering method respectively. This approach is automatically done, thereby allowing to easily fill-in corrupted regions containing completely different structures and surrounding backgrounds. Applications of proposed method include the restoration of damaged text images; removal of superimposed noises or streaks. We so can see that proposed approach is efficient and robust in terms of restoring and segmenting text images corrupted.