• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1997년도 Proceedings International Workshop on New Video Media Technology
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• pp.19-24
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• 1997

This paper describes an image segmentation technique for the object-oriented coding at very low bit rates. By noting that, in the object-oriented coding technique, each objects are represented by 3 parameters, namely, shape, motion, and color informations, we propose a segmentation technique, in which the 3 parameters are fully exploited. To achieve this goal, starting with the color space conversion and the noise reduction, the input image is divided into many small regions by the K-menas algorithm on the O-K-S color space. Then, each regions are merged, according to the shape and motion information. In simultations, it is shown that the proposed technique segments the input image into relevant objects, according to the shape and motion as well as the colors. In addition, in order to evaluate the performance of the proposed technique, we introduce the notion of the interesting regions, and provide the results of encoding the image with emphasizing the interesting regions.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.145-148
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• 2002

A study on image searching and management techniques is actively developed by user requirements for multimedia information that are existing as images, audios, texts data from various information processing devices. We had been studied an automatical shape region segmentation method using color. distribution and edge characteristics of moving images for. contents-base description. The Proposed method uses a color information quantized on human visual system and extracts overlapped regions to be matched by using edge characteristics of the image frame. The performance of the proposed method is represented by similarity for comparison to a segmented image and original image.

• 대한전자공학회논문지SP
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• 제48권3호
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• pp.90-98
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• 2011

전 세계적으로 벼 병충해의 인식과 분류는 농업현장에서 기술적 경제적으로 중요한 요소이다. 컴퓨터 비젼 기술은 벼 병충해를 진단하고 곡물의 효율적인 관리에 유용하다. 영역 분할은 벼 병충해를 조기에 정확하게 탐지하는데 매우 중요한 기술이다. 가우시안 평균기법을 이용한 새로운 벼 병충해 분할 방식을 다양한 색체공간에서 제안하였다. 사용 색체공간에 따라 벼 병충해의 분할에 따른 성능은 달라질 것이다. 따라서, 이 수치연구는 어느 색체공간이 벼 병충해를 분할하는데 최적한지를 결정할 목적으로 수행되었다. 본 연구는 NTSC, CIE, YCbCr, HSV, 그리고 정규화 RGB의 5개의 색체공간을 다루었다. 연구 결과는 YCbCr 색체공간이 98%의 정확도로 벼 병충해 영역을 최적으로 분할하는 것을 보여주었다. 또한 제안하는 방법은 벼 병충해의 영역을 자동화에 의하여 강건하게 분할할 수 있다는 것을 증명하였다.

• 전자공학회논문지CI
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• 제46권2호
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• pp.92-99
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• 2009

본 논문에서는 교통 신호등 영역 검출을 포함한 교통 신호등 외곽 부분과 신호등 색을 자동으로 판별하여 사용자에게 알려주는 교통 신호등 자동 판별 시스템 구현을 제안하였다. 본 논문은 교통 신호등색을 정확하게 검출하기 위하여 교통 신호등색에 해당하는 파장 범위를 설정하고, 색상 성분을 분할하였다. 색상 성분을 통해 교통 신호등색(빨강 주황 녹색)을 검출하며 배경부분은 그레이 영상으로 변환한다. 다음으로 웨이브렛 변환 알고리즘을 사용하여 다양한 환경에서 신호등 영역을 검출할 수 있는 알고리즘을 제안하였다. 또한, 교통 신호등 인식 부분은 CBIR(Content-Based Image Retrieval)기반에서 캐니 에지 연산자와 허도로프 매칭 알고리즘의 특성을 적용한 인식 알고리즘을 제안하였다. 제안된 알고리즘은 교통 신호등이 첨가되어 있는 조명, 배경 등이 다양한 영상을 대상으로 실험하며, 기존 알고리즘과 비교하여 제안 알고리즘의 성능이 향상되었음을 확인하였다.

• 전자공학회논문지 IE
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• 제43권2호
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• pp.39-48
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• 2006

본 논문은 공간적 자동 객체 분할의 개념과 클러스터링 개념을 가진 웨이브렛 형태학 알고리즘을 제안하였다. 제안된 알고리즘을 이용하여 컬러 얼굴을 분할할 때 영상을 단순화하였으며, 또한 사용자의 조작 없이 실시간적으로 분할해 검출할 수 있도록 공간적 특성을 이용하였다. 이것은 HSV 컬러 모델을 이용하여 영상에서 잡음으로 간주되는 작은 부분을 제거하고, 얼굴영상 이외의 부분을 제거하기 위해 웨이브렛 형태학을 적용하였다. 본 논문은 웨이브렛 형태학 알고리즘과 형태학 알고리즘을 비교하였으며, 그리고 HSV 컬러 공간 모델을 적용한 영상에서 얼굴 객체 부분을 정확하게 검출함을 보였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.1093-1096
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• 1999

In this paper, video image segmentation algorithm based on color histogram and change detector is proposed. Color histograms are calculated from both changed region which is detected in the previous and current frame and unchanged region. With each histogram, modes and valleys are detected. Then, color vectors are calculated by averaging pixels in modes. Markers are extracted by labeling color vectors that represent modes, the watershed algorithm is applied to determine uncertain region. In growing region, the root mean square(RMS) of the distance between average pixel in marker region and adjacent pixel is used as a measure. The proposed algorithm based on color histogram and change detector segments video image fastly and effectively. And simulation results show that the proposed method determines the exact boundary between background and foreground.

• International Journal of Control, Automation, and Systems
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• 제4권2호
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• pp.236-246
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• 2006

Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks such as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. In this paper, the development of new snake model called 'adaptive color snake model (ACSM)' for segmentation and tracking is introduced. The simple operation makes the algorithm runs in real-time. For robust tracking, the condensation algorithm was adopted to control the parameters of ACSM. The effectiveness of the ACSM is verified by appropriate simulations and experiments.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2004년도 추계학술발표논문집(상)
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• pp.891-894
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• 2004

This paper proposes an improved image segmentation algorithm by the watershed algorithm based on the local adaptive threshold on local minima search and the fixing threshold on label allocation. The previous watershed algorithm generates the problem of over-segmentation. The over-segmentation makes the boundary in the inaccuracy region by occurring around the object. In order to solve those problems we quantize the input color image by the vector quantization, remove noise and find the gradient image. We sorted local minima applying the local adaptive threshold on local minima search of the input color image. The simulation results show that the proposed algorithm controls over-segmentation and makes the fine boundary around segmented region applying the fixing threshold based on sorted local minima on label allocation.

• Journal of Multimedia Information System
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• 제5권4호
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• pp.221-228
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• 2018

Skin-color information is not sufficient for palmprint segmentation in complex scenes, including mobile environments. Traditional active shape model (ASM) combines gray information and shape information, but its performance is not good in complex scenes. An improved ASM method is developed for palmprint segmentation, in which Perux method normalizes the shape of the palm. Then the shape model of the palm is calculated with principal component analysis. Finally, the color likelihood degree is used to replace the gray information for target fitting. The improved ASM method reduces the complexity, while improves the accuracy and robustness.

• 디지털산업정보학회논문지
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• 제14권4호
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• pp.169-176
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• 2018

In this study, we propose a new Fire Flame Region Extraction using Block Homogeneity Segmentation method of the Fire Image with irregular texture and various colors. It is generally assumed that fire flame extraction plays a very important role. The Color Image with fire flame is divided into blocks and edge strength for each block is computed by using modified color histogram intersection method that has been developed to differentiate object boundaries from irregular texture boundaries effectively. The block homogeneity is designed to have the higher value in the center of region with the homeogenous colors or texture while to have lower value near region boundaries. The image represented by the block homogeneity is gray scale image and watershed transformation technique is used to generate closed boundary for each region. As the watershed transform generally results in over-segmentation, region merging based on common boundary strength is followed. The proposed method can be applied quickly and effectively to the initial response of fire.