• Title/Summary/Keyword: HCbCr

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Design of RBFNNs Pattern Classifier Realized with the Aid of Face Features Detection (얼굴 특징 검출에 의한 RBFNNs 패턴분류기의 설계)

  • Park, Chan-Jun;Kim, Sun-Hwan;Oh, Sung-Kwun;Kim, Jin-Yul
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.2
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    • pp.120-126
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    • 2016
  • In this study, we propose a method for effectively detecting and recognizing the face in image using RBFNNs pattern classifier and HCbCr-based skin color feature. Skin color detection is computationally rapid and is robust to pattern variation for face detection, however, the objects with similar colors can be mistakenly detected as face. Thus, in order to enhance the accuracy of the skin detection, we take into consideration the combination of the H and CbCr components jointly obtained from both HSI and YCbCr color space. Then, the exact location of the face is found from the candidate region of skin color by detecting the eyes through the Haar-like feature. Finally, the face recognition is performed by using the proposed FCM-based RBFNNs pattern classifier. We show the results as well as computer simulation experiments carried out by using the image database of Cambridge ICPR.

Feature Point Extraction of Hand Region Using Vision (비젼을 이용한 손 영역 특징 점 추출)

  • Jeong, Hyun-Suk;Joo, Young-Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.10
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    • pp.2041-2046
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    • 2009
  • In this paper, we propose the feature points extraction method of hand region using vision. To do this, first, we find the HCbCr color model by using HSI and YCbCr color model. Second, we extract the hand region by using the HCbCr color model and the fuzzy color filter. Third, we extract the exact hand region by applying labeling algorithm to extracted hand region. Fourth, after finding the center of gravity of extracted hand region, we obtain the first feature points by using Canny edge, chain code, and DP method. And then, we obtain the feature points of hand region by applying the convex hull method to the extracted first feature points. Finally, we demonstrate the effectiveness and feasibility of the proposed method through some experiments.

Input Device of Non Touch Screen Using Hand Region Skeleton Model (손 영역 스켈레톤 모델을 이용한 비접촉 스크린 입력 장치)

  • Seo, Hyo-Dong;Kim, Hyo-Jin;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.1906-1907
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    • 2011
  • 본 논문에서는 손 영역 스켈레톤 모델을 이용한 비접촉식 스크린 입력 장치를 제안한다. 제안하는 방법은 HCbCr 컬러 모델을 생성한 후 손 후보 영역을 추출하고, 손 영역을 추출하기 위해 레이블링 기법을 사용한다. 손 이외의 피부를 제거하기 위해 손 크기 이하의 객체는 필터링을 거친 후 최종적인 손 영역을 추출한다. 손 영역의 특징점은 무게 중심법과 굴곡 기법을 이용하여 추출한다. 특징점을 연결하여 손의 스켈레톤 모델을 생성하고 각 손가락에 터치 이벤트를 부여한다. 손가락의 구부러진 각도를 이용하여 터치 동작을 인식 및 실행하게 된다.

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Classification and Tracking of Hand Region Using Deformable Template and Condensation (Deformable Template과 Condensation을 이용한 손 영역 분류와 추적)

  • Jeong, Hyeon-Seok;Joo, Young-Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.8
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    • pp.1477-1481
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    • 2010
  • In this paper, we propose the classification and tracking method of the hand region using deformable template and condensation. To do this, first, we extract the hand region by using the fuzzy color filter and HCbCr color model. Second, we extract the edge of hand by applying the Canny edge algorithm. Third, we find the first template by calculating the conditional probability between the extracted edge and the model edge. If the accurate template of the first object is decided, the condensation algorithm tries to track it. Finally, we demonstrate the effectiveness and feasibility of the proposed method through some experiments.

Input Device of Non-Touch Screen Using Vision (비전을 이용한 비접촉 스크린 입력장치)

  • Seo, Hyo-Dong;Joo, Young-Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.10
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    • pp.1946-1950
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    • 2011
  • This paper deals with an input device without the touch. The existing touch screens have some problems such as the week durability by frequent contact and the high cost by complex hardware configuration. In this paper, a non-touch input device is proposed to overcome these problems. The proposed method uses a skin color generated by the HCbCr color model and a hand region obtained by the labeling technique. In Addition, the skeleton model is employed to improve the recognition performance of the hand motion. Finally, the experiment results show the applicability of the proposed method.

Hand Region Feature Point Extraction Using Vision (비젼을 이용한 손 영역 특징점 추출)

  • Jeong, Hyun-Suk;Oh, Myung-Jea;Joon, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.1798_1799
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    • 2009
  • 본 논문에서는 강인한 손 영역 특징 점 추출 방법을 제안한다. 제안하는 방법은 HCbCr 칼라 모델을 생성한 후 퍼지 색상 필터에 적용하여 손 후보 영역을 추출한다. 최종적으로 손 영역을 추출하기 위해서 레이블링 기법을 사용한다. 그 후, 추출된 손 영역의 실루엣을 추출하고 히스토그램 기법을 적용하여 손 영역 내의 COG를 추출 한다. 손 영역 특징 점 추출을 위해 Canny edge 기법과 Chain Code기법, DP(Douglas-Peucker)기법들을 이용하여 전처리 과정을 거쳐 1차 특징점을 추출한다. 추출된 1차 특징 점을 Convex Hull기법에 적용하여 최종적인 손 영역 특징 점을 추출한다. 마지막으로, 복잡하고 다양한 실내 환경에서의 실험을 통해 그 응용 가능성을 증명한다.

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