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A Study on the Convergence Technique enhanced GrabCut Algorithm Using Color Histogram and modified Sharpening filter

칼라 히스토그램과 변형된 샤프닝 필터를 이용한 개선된 그랩컷 알고리즘에 관한 융합 기술 연구

  • Received : 2015.10.13
  • Accepted : 2015.12.20
  • Published : 2015.12.31

Abstract

In this paper, we proposed image enhancement method using sharpening filter for improving the accuracy of object detection using the existing Grabcut algorithm. GrabCut algorithm is the excellent performance extracting an object within a rectangular window range, but it has the drawback of the inferior performance in image with no clear distinction between background and objects. So, in this paper, reinforcing the brightness and clarity through histogram equalization, and tightening the border of the object using the sharpening filter look better than that extracted result of existing GrabCut algorithm in a similar image of the object and the background. Based on improved Grabcut algorithm, it is possible to obtain an improved result in the image processing convergence technique of character recognition, real-time object tracking and so on.

본 논문에서는 기존의 그랩컷 알고리즘을 이용한 객체 검출의 정확도를 향상시키기 위하여 샤프닝 필터를 이용한 영상의 화질을 개선하는 방법을 제안한다. 그랩컷 알고리즘은 사각 윈도우 범위 내에서 객체 추출에 뛰어난 성능을 보이지만, 객체와 배경의 구분이 뚜렷하지 않은 영상에서는 성능이 떨어지는 단점이 있다. 따라서 본 논문에서는 히스토그램 평활화를 통해 밝기 및 선명도를 보강하고, 샤프닝 필터를 이용하여 객체의 경계를 강화하여 기존의 그랩컷 알고리즘보다 객체와 배경의 색상이 비슷한 영상에서 향상된 객체 추출 결과를 보인다. 개선된 그랩컷 알고리즘을 토대로 문자인식, 실시간 객체추적 등 영상처리 융합 기술에서 향상된 결과를 얻을 수 있다.

Keywords

References

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