Journal of Digital Contents Society (디지털콘텐츠학회 논문지)

Digital Contents Society (한국디지털콘텐츠학회)
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Noise-robust Hand Region Segmentation In RGB Color-based Real-time Image

RGB 색상 기반의 실시간 영상에서 잡음에 강인한 손영역 분할

  • Yang, Hyuk Jin (Dept. of Computer Science, Gyeongsang Nat'l University) ;
  • Kim, Dong Hyun (Dept. of Computer Science and CCBM, Graduate School, Gyeongsang Nat'l University) ;
  • Seo, Yeong Geon (Dept. of Computer Science and CCBM, Graduate School, Gyeongsang Nat'l University)
  • 양혁진 (경상대학교 컴퓨터과학과) ;
  • 김동현 (경상대학교 컴퓨터과학과, 대학원 컴퓨터과학과, 대학원 문화융복합학과) ;
  • 서영건 (경상대학교 컴퓨터과학과, 대학원 컴퓨터과학과, 대학원 문화융복합학과)
  • Received : 2017.12.05
  • Accepted : 2017.12.25
  • Published : 2017.12.31
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Abstract

This paper proposes a method for effectively segmenting the hand region using a widely popular RGB color-based webcam. This performs the empirical preprocessing method four times to remove the noise. First, we use Gaussian smoothing to remove the overall image noise. Next, the RGB image is converted into the HSV and the YCbCr color model, and global fixed binarization is performed based on the statistical value for each color model, and the noise is removed by the bitwise-OR operation. Then, RDP and flood fill algorithms are used to perform contour approximation and inner area fill operations to remove noise. Finally, ROI (hand region) is selected by eliminating noise through morphological operation and determining a threshold value proportional to the image size. This study focuses on the noise reduction and can be used as a base technology of gesture recognition application.

본 논문은 널리 알려진 RGB 색상 기반의 웹캠을 사용한 손 영역을 효율적으로 분할하는 방법을 제안한다. 이 방법은 잡음을 제거하기 위하여 네 번의 경험적 전처리 방법을 수행한다. 먼저, 전체 영상 잡음을 제거하기 위하여 가우시안 평활화를 수행한다. 다음으로, RGB 영상은 HSV와 YCbCr 색상 모델로 변환되어, 각 색상 모델에 대해 통계적인 값에 기반하여 전역 고정 이진화가 수행된 후, 잡음은 bitwise-OR 연산에 의해 제거된다. 다음으로, 윤곽 근사화와 내부 영역 구멍 연산을 위해 RDP와 flood fill 알고리즘이 사용된다. 끝으로, 모폴로지 연산을 통하여 잡음을 제거하고 영상의 크기에 비례한 임계값을 결정하여 손 영역이 결정된다. 본 연구는 잡음 제거에 초점을 맞추고 있고 손 동작 인식 응용 기술에 사용될 수 있다.

Keywords

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