• Proceedings of the Korean Information Science Society Conference
• /
• 2004.04b
• /
• pp.175-177
• /
• 2004

최근, 이미지 검색기법에서는 객체추출 방법이나 관심영역 추출방법에 관한 연구가 활발히 이루어지고 있다. 그러나, 컬러 이미지의 경우 색상을 고려한 관심영역 특징추출 방법이나 인덱스 기법은 많이 연구되지 못하고 있다. 따라서, 본 논문에서는 컬러 이미지의 색상을 기반으로 하는 사분트리 분할 인덱스 기법을 제안한다. 사분트리 분할 인덱스 구조는 컬러 이미지의 공간 영역을 계층적인 영역으로 분할하여 각 공간 영역의 평균 색상 갓을 데이터베이스에 저장한다 저장되어진 각 영역의 평균 색상은 검색의 효율성을 높이기 위해 사분트리 인스턴스(Quad-tree distance)를 퍼지 값으로 계산하여 인덱스를 생성한다. 생성된 사분트리 분할 인덱스는 컬러 이미지의 관심영역(Region of Interest)의 색상을 검색할 때 유용하게 사용되며. 검색속도의 향상에 도움을 준다.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.271-274
• /
• 2001

미국의 National Library of Medicine에서 제공하는 Visible human 컬러영상을 이용하여, 신체 장기의 3차원 모델링 및 가시화 하기 위한 영역 분할 방법 연구가 활발히 진행되고 있다. 특히 다른 신체 장기 분할에 비해 뼈분할은 주위의 영역들과 모호한 경계를 지니고 있어 컬러영상만을 가지고 구분해 내기가 쉽지 않다. 이러한 문제점을 해결하기 위해 본 논문에서는 Visible human CT영상을 가지고 뼈 영역을 분할하고 분할 된 뼈 영역의 경계를 추출하여 그 경계를 컬러영상의 최적화된 위치로 변환해 최종적인 뼈 영역 분할을 시도한다. 제안된 방법은 Visible human 단면영상의 머리부분에 적용하여 좋은 결과를 얻음을 실험을 통해 효율성을 검증하였다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.12C
• /
• pp.1147-1153
• /
• 2009

We propose a novel image segmentation and segment-based stereo matching technique using color, depth, and motion information. Proposed technique firstly splits reference images into foreground region or background region using depth information from depth camera. Then each region is segmented into small segments with color information. Moreover, extracted segments in current frame are tracked in the next frame in order to maintain depth consistency between frames. The initial depth from the depth camera is also used to set the depth search range for stereo matching. Proposed segment-based stereo matching technique was compared with conventional one without foreground and background separation and other conventional one without motion tracking of segments. Simulation results showed that the improvement of segment extraction and depth estimation consistencies by proposed technique compared to conventional ones especially at the static background region.

• The Journal of the Korea Contents Association
• /
• v.6 no.9
• /
• pp.19-27
• /
• 2006

Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the region merge constraints are used to decide whether regions are merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.48 no.5
• /
• pp.37-44
• /
• 2011

This paper proposes a confusion-line separating algorithm in a CIE Lab color space using color segmentation for protanopia and deuteranopia. Images are segmented into regions by grouping adjacent pixels with similar color information using the hue components of the images. To this end, the region growing method and the seed points used in this method are the pixels that correspond to peak points in hue histograms that went through a low pass filter. In order to establish a color vision deficiency (CVD) confusion line map, we established 512 virtual boxes in an RGB 3-D space so that boxes existing on the same confusion line can be easily identified. After that, we checked if segmented regions existed on the same confusion line and then performed color adjustment in an CIE Lab color space so that all adjacent regions exist on different confusion lines in order to provide the best color identification effect to people with CVDs.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.3 s.303
• /
• pp.7-14
• /
• 2005

In this paper we proposed the block-based color image segmentation method using the cylindrical metric to solve the problems such as long processing time and over segmentation due to noise and texture properties in the conventional methods. In the proposed method we define the new similarity function and the merge condition between regions to merge initial regions with the same size considering the color and texture properties of chromatic and achromatic regions which is defined according to the HSI color values, and we continue to merge boundary blocks into the adjacent region already segmented to maintain edges until the size of block is one. In the simulation results the proposed method is better than the conventional methods in the evaluation of the segmented regions of texture and edge region, and we found that the processing time is decreased by factor of two in the proposed method.

• Journal of Korea Multimedia Society
• /
• v.8 no.4
• /
• pp.473-481
• /
• 2005

In this paper, we propose an image segmentation method preserving object's boundaries by using the number of quantized colors and merging regions using adaptive threshold values. First of all, the proposed method quantizes an original image by a vector quantization and the number of quantized colors is determined differently using PSNR each image. We obtain initial regions from the quantized image, merge initial regions in CIE Lab color space and RGB color space step by step and segment the image into semantic regions. In each merging step, we use color distance between adjacent regions as similarity-measure. Threshold values for region-merging are determined adaptively according to the global mean of the color difference between the original image and its split-regions and the mean of those variations. Also, if the segmented image of RGB color space doesn't split into semantic objects, we merge the image again in the CIE Lab color space as post-processing. Whether the post-processing is done is determined by using the color distance between initial regions of the image and the segmented image of RGB color space. Experiment results show that the proposed method splits an original image into main objects and boundaries of the segmented image are preserved. Also, the proposed method provides better results for objective measure than the conventional method.

• Journal of the Korea Computer Graphics Society
• /
• v.18 no.2
• /
• pp.9-15
• /
• 2012

In this paper, we propose a method to segment a color image into several meaningful regions. We suppose that the meaningful region has a set of colors with high frequency in the color image. To find these colors, the color image is represented as several sets of color points in RGB space. And when we use the density of points defined in this method, color belonging to a dense region of color points in RGB space refers to the color that appeared frequently in the image. Eventually, we can find meaningful regions by looking for regions with high density of color points using our level set function in RGB space. However, if a meaningful region does not have a contiguous region of the sufficient size in the image, this is not a meaningful region but meaningless region. Thus, the pixels in the meaningless region are assigned to the biggest meaningful region belonging to its neighboring pixels in the color image. Our method divides the color image into meaningful regions by applying the density of color points to level set function in RGB space. This is different from the existing level set method that is defined only in 2D image.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.1970_1971
• /
• 2009

한의학에서 혀는 장부의 건강 상태를 표면적으로 보여주는 중요한 요소 중의 하나이다. 특히 장부가 혀의 영역에 연결이 되어 각 장부의 특성을 파악하는데 매우 요긴하게 사용되고 있다. 이 연구에서는 비침습적으로 카메라와 조명 장치를 이용한 설진기를 이용하여 객관적으로 혀 영역을 촬영하고 진단을 위한 혀 영역의 객관적인 지표를 자동으로 찾는 방법을 개발하는 것을 목표로 한다. 이를 위해서 가장 중요한 일은 혀의 컬러 요소를 파악하여 정확한 위치를 찾아내는 것이다. 컬러를 색상, 채도, 명암으로 분해하고 지역 영역의 히스토그램을 분석하여 분할 임계값을 선택, 전체 영역을 분할한다. 결론적으로 이 방법은 설태가 있는 영역을 찾아내고 설태의 종류를 구분하는 방법을 제안하였다.

• Journal of Korea Multimedia Society
• /
• v.7 no.3
• /
• pp.319-326
• /
• 2004

In this paper, we propose color image segmentation by region merging method preserving the boundary of an object. The proposed method selects initial region by using quantized image's index map after vector quantizing an original image. After then, we merge regions by applying boundary restricted factor in order to consider the boundary of an object in HSI color space. Also we merge the regions in RGB color space for non-processed regions in HSI color space. And we reduce processing time by decreasing iterative process in region merging algorithm. Experimental results have demonstrated the superiority in region's segmentation results and processing time for various images.