• Title/Summary/Keyword: interest region

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Automatic Segmentation of the Interest Organ Region in CT Images Using Region Growing (CT 영상에서 Region Growing 기법을 이용한 관심 장기 영역의 자동 추출)

  • Bae, Ho-Young;Lee, Wu-Ju;Lee, Bae-Ho
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.10b
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    • pp.526-530
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    • 2006
  • 논문은 CT영상에서 영역 확장 기법을 이용하여 인간의 장기 중 뇌와 간을 자동으로 추출할 수 있는 방법을 제안한다. 이는 뇌와 간이 CT영상에서 비교적 넓은 영역을 차지하고 있다는 사실에 기인하였으며, CT영상에서 특정 장기 영역을 추출하기 위해서 크게 초기 탐색 영역 결정 단계와 최종 장기 영역 단계로 나누어진다. 초기 탐색 영역은 CT영상 내에서 추출하고자 하는 장기 영역과 관계없는 부분을 제거하고 특정 장기 영역만을 남겨 관심 장기 영역의 검출률을 높이는 작업이다. 본 논문에서는 CT영상에서 비교적 높은 Gray Level을 가지고 있는 뼈영역인 두개골과 척추의 위치를 기반으로 하여 초기 탐색 영역을 결정하는 방법을 사용하였다. 특정 장기 영역의 추출은 ATID(Automatic Threshold Intensity Decision)를 이용한 이진화 단계, 모폴로지의 Opening 기법을 이용한 잡음제거 단계, Region Growing 기법을 이용한 특정 영역 추출 단계를 이용하는 과정을 거친다. 본 논문에서는 Region Growing 기법을 거친 다음 각각의 그룹 중에서 크기가 가장 큰 부분을 최종 특정 장기 영역으로 결정하였다. 본 논문에서 제안한 알고리즘은 국립전남대학교 부속병원에서 수집된 각각 뇌영상 100장과 간영상 100장을 사용하여 실험하였고, 제안된 알고리즘을 통해 관심 장기 영역을 추출했을 경우 약 91%이상의 높은 추출률을 보였다.

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Priority Analysis for Resource Development of Waterfront in Jeju Region - Using AHP method (AHP 기법을 적용한 제주지역 친수공간 자원화방안 요인의 중요도 분석)

  • Boo, Chang-San;Kim, Suk Jong;Kim, Mincheol
    • Journal of Fisheries and Marine Sciences Education
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    • v.25 no.1
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    • pp.139-151
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    • 2013
  • Recently, in the context of increased interest for marine tourism, Jeju region of South Korea has attractive waterfront space and also has potential requirements for development. The objective of this paper was to analyze the priority for resource development of waterfront in Jeju region. In order to calculate the importance of factors related to the development of waterfront in Jeju area, this study conducted exploratory factor analysis to extract the factors and established the AHP model based on the factors name focusing on a total of 198 tourists. In this study, in accordance with the procedures of AHP analysis, pairwise comparisons were conducted focusing on a total of 15 experts. Especially, difference test between groups (academics and bureaucratic) was conducted. In the 1st criterion for evaluation, 'exploring experience' factor is most important thing and 'facilities & infrastructure' factors were in the following order. In the secondary criterion, AHP analysis showed that experience facilities, environmental management, and absence of residents consciousness were the important factors. In the future time, the results of this research can be utilized as basic data in the aspects of tourism development in Jeju waterfront region.

Tracking of eyes based on the iterated spatial moment using weighted gray level (명암 가중치를 이용한 반복 수렴 공간 모멘트기반 눈동자의 시선 추적)

  • Choi, Woo-Sung;Lee, Kyu-Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.5
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    • pp.1240-1250
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    • 2010
  • In this paper, an eye tracking method is presented by using on iterated spatial moment adapting weighted gray level that can accurately detect and track user's eyes under the complicated background. The region of face is detected by using Haar-like feature before extracting region of eyes to minimize an region of interest from the input picture of CCD camera. And the region of eyes is detected by using eigeneye based on the eigenface of Principal component analysis. Also, feature points of eyes are detected from darkest part in the region of eyes. The tracking of eyes is achieved correctly by using iterated spatial moment adapting weighted gray level.

Tracking of eyes based on the spatial moment using weighted gray level (명암 가중치를 이용한 공간 모멘트기반 눈동자 추적)

  • Choi, Woo-Sung;Lee, Kyu-Won;Kim, Kwan-Seop
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.198-201
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    • 2009
  • In this paper, an eye tracking method is presented by using on iterated spatial moment adapting weighted gray level that can accurately detect and track user's eyes under the complicated background. The region of face is detected by using Haar-like feature before extracting region of eyes to minimize an region of interest from the input picture of CCD camera. And the region of eyes is detected by using eigeneye based on the eigenface of Principal component analysis. And then feature points of eyes are detected from darkest part in the region of eyes. The tracking of eyes is achieved correctly by using iterated spatial moment adapting weighted gray level.

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A Digital Image Watermarking Using A Bottom-up Attention Module (상향식 주의 모듈을 사용한 디지털 워터마킹 기법)

  • Cheoi, Kyung-Joo
    • The KIPS Transactions:PartB
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    • v.15B no.4
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    • pp.293-300
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    • 2008
  • This paper takes a bottom-up attention module into consideration for digital image watermarking. A bottom-up attention module is employed to obtain the region of interest, and watermark information is embedded into the obtained region. Previous studies in digital image watermarking have been focused on the signal processing techniques, especially in waveform coding spreading watermarks over the entire target image. However, we notice that the third party's visual attention is usually concentrated on a few regions in an image but not on all of them. These regions are easy to be the target of attacks. If watermark information is inserted into these regions from the beginning, it can be detected with high correlation. Various kinds of images are tested, and the results showed good quality.

Contrast Enhancement Method for Images from Visual Sensors (비주얼 센서 영상에 대한 대비 개선 방법)

  • Park, Sang-Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.3
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    • pp.525-532
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    • 2018
  • Recently, due to the advancements of sensor network technologies and camera technologies, there are increasing needs to effectively monitor the environment in a region that is difficult to access by using the visual sensor network that combines these two technologies. Since the image captured by the visual sensor reflects the natural phenomenon as it is, the quality of the image may deteriorate depending on the weather or time. In this paper, we propose an algorithm to improve the contrast of images using the characteristics of images obtained from visual sensors. In the proposed method, we first set the region of interest and then analyzes the change of the color value of the region of interest according to the brightness value of the image. The contrast of an image is improved by using the high contrast image of the same object and the analysis information. It is shown by experimental results that the proposed method improves the contrast of an image by restoring the color components of the low contrast image simply and accurately.

A High Speed Road Lane Detection based on Optimal Extraction of ROI-LB (관심영역(ROI-LB)의 최적 추출에 의한 차선검출의 고속화)

  • Cheong, Cha-Keon
    • Journal of Broadcast Engineering
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    • v.14 no.2
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    • pp.253-264
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    • 2009
  • This paper presents an algorithm, aims at practical applications, for the high speed processing and performance enhancement of lane detection base on vision processing system. As a preprocessing for high speed lane detection, the vanishing line estimation and the optimal extraction of region of interest for lane boundary (ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled. Image feature information is extracted only in the ROI-LB. Road lane is extracted using a non-parametric model fitting and Hough transform within the ROI-LB. With simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since outliers of edge at each block can be removed with clustering of edge orientation for each block within the ROI-LB, the performance of lane detection can be greatly improved. The various real road experimental results are presented to evaluate the effectiveness of the proposed method.

Effective Frame Rate Up-Conversion Method Using Adaptive Motion Refinement Based on ROI Separation (관심영역 분리에 따른 적응적인 움직임 보정에 기초한 효과적인 프레임 율 증가 기법)

  • Lee, Beom-yong;Kim, Jin-soo
    • The Journal of the Korea Contents Association
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    • v.16 no.2
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    • pp.310-319
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    • 2016
  • This paper proposes an effective FRUC (Frame Rate Up-Conversion) technique, which is based on ROI (Region Of Interest) separations and adaptive motion vector refinement. In this paper, in order to overcome the weakness of the EBME (Extended Bi-lateral Motion Estimation) algorithm, which is widely known in FRUC techniques, first, the proposed algorithm performs a bi-directional motion estimation for the complementary asymmetric region. Then, the proposed algorithm classifies each block into ROI or non-ROI block and refine motion vectors in accordance with their block characteristics to have a higher accuracy than the conventional EBME algorithm, specially, for the occlusion regions. The experimental results show that the proposed algorithm can improves 0.59dB on average PSNR as compared to the conventional method.

ROI Detection by Genetic Algorithm Based on Probability Map (확률맵 기반 유전자 알고리즘에 의한 ROI 검출)

  • Park, Hee-Jung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.8
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    • pp.3028-3035
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    • 2010
  • This paper propose a genetic method based on probability map to detect region of the lips on a natural image with the faces. The method has many solutions in order to detect regions such as the lips instead of one optimal solution of existing methods. To do this, it represents a pair of spatial coordinates as a chromosome, and introduces genetic operations like conservation interval, the number of generations and non-overlapping selection. By using the probability map of the HS in HSV color space, it increases adaptability to similar color that is a property of genetic algorithm. In our experiments, the optimal value of the important parameter $\beta$ was analyzed, which was used as the condition of an ending function and affected performance of the proposed algorithm. Also the algorithm was analyzed on what performance it has when its mating methods are different. The results of the experiment showed that our algorithm could be flexibly adapted for detecting other ROIs.

Detection of Road Lane with Color Classification and Directional Edge Clustering (칼라분류와 방향성 에지의 클러스터링에 의한 차선 검출)

  • Cheong, Cha-Keon
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.4
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    • pp.86-97
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    • 2011
  • This paper presents a novel algorithm to detect more accurate road lane with image sensor-based color classification and directional edge clustering. With treatment of road region and lane as a recognizable color object, the classification of color cues is processed by an iterative optimization of statistical parameters to each color object. These clustered color objects are taken into considerations as initial kernel information for color object detection and recognition. In order to improve the limitation of object classification using the color cues, the directional edge cures within the estimated region of interest in the lane boundary (ROI-LB) are clustered and combined. The results of color classification and directional edge clustering are optimally integrated to obtain the best detection of road lane. The characteristic of the proposed system is to obtain robust result to all real road environments because of using non-parametric approach based only on information of color and edge clustering without a particular mathematical road and lane model. The experimental results to the various real road environments and imaging conditions are presented to evaluate the effectiveness of the proposed method.