• Title/Summary/Keyword: ROI 영역

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Infrared Image Segmentation by Extracting and Merging Region of Interest (관심영역 추출과 통합에 의한 적외선 영상 분할)

  • Yeom, Seokwon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.6
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    • pp.493-497
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    • 2016
  • Infrared (IR) imaging is capable of detecting targets that are not visible at night, thus it has been widely used for the security and defense system. However, the quality of the IR image is often degraded by low resolution and noise corruption. This paper addresses target segmentation with the IR image. Multiple regions of interest (ROI) are extracted by the multi-level segmentation and targets are segmented from the individual ROI. Each level of the multi-level segmentation is composed of a k-means clustering algorithm an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering algorithm initializes the parameters of the Gaussian mixture model (GMM) and the EM algorithm iteratively estimates those parameters. Each pixel is assigned to one of clusters during the decision. This paper proposes the selection and the merging of the extracted ROIs. ROI regions are selectively merged in order to include the overlapped ROI windows. In the experiments, the proposed method is tested on an IR image capturing two pedestrians at night. The performance is compared with conventional methods showing that the proposed method outperforms others.

Ileus Detection by Using ART2 and Hough Transform (ART2와 Hough Transform을 이용한 장폐색 영역 검출)

  • Kim, Hyun Woo;Lee, Hae Ill;Park, Seung Ik;Kim, Kwang Beak
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.363-365
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    • 2018
  • 대장과 소장에서 모두 폐색 영역을 검출하기 위하여 본 논문에서는 기존에 연구된 장 폐색 영역 검출 방법과 ART2 알고리즘을 이용한 대장 폐색 영역과 소장 폐색 영역을 검출하는 방법을 제안한다. 제안된 방법은 기존에 연구된 방법을 이용하여 ROI 영역을 추출한 후, 추출된 ROI 영역을 ART2 알고리즘을 이용하여 영상을 군집화 한다. 군집화된 ROI 영역과 기존에 연구된 방법으로 X-ray 영상에서 검출한 장 폐색 영역의 형태학적 특징을 비교 및 분석하여 장 폐색의 형태학적 특징을 포함하는 클러스터를 분석한다. 따라서 장 폐색 영역에 해당되는 클러스터로 분류된 영역 내부를 클러스터의 중심에 해당되는 픽셀로 모두 대체한다. 그리고 $3^*3$ 필터를 이용한 침식과 팽창 연산을 적용하여 잡음을 제거한다. 잡음이 제거된 영상에서 각 객체들을 라벨링한 후에 크기를 비교하여 배경과 기타 지방 영역을 제거하고 남은 객체들을 장 폐색 영역으로 검출한다. 제안된 추출 방법을 장 폐색 X-ray 영상을 대상으로 실험한 결과, 기존에 연구된 방법으로 추출에 성공한 대장 장 폐색 영상과 추출에 실패한 소장 폐색 영상 모두에서 추출되는 것을 확인하였다.

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Selective Encryption Scheme Based on Region of Interest for Medical Images (의료 영상을 위한 관심영역 기반 선택적 암호 기법)

  • Lee, Won-Young;Ou, Yang;Rhee, Kyung-Hyune
    • Journal of Korea Multimedia Society
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    • v.11 no.5
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    • pp.588-596
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    • 2008
  • For the patients' privacy, secure access control of medical images is essentially necessary. In this paper, two types of Region of Interest (ROI)-based selective encryption schemes are proposed, which concentrate on the security of crucial parts in medical images. The first scheme randomly inverts the most significant bits of ROI coefficients in several high frequency subbands in the transform domain, which only incurs little loss on compression efficiency. The second scheme employs a symmetric key encryption to encrypt selectively the ROI data in the final code-stream, which provides sufficient confidentiality. Both of two schemes are backward compatible so as to ensure a standard bitstream compliant decoder so the encrypted images can be reconstructed without any crash.

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Extraction and analysis of rotator cuff tear area Using Clustering Based Quantization (클러스터링 기법 기반 양자화를 이용한 회전근개 건 파열 영역 추출 및 분석)

  • Park, Ji-Hun;Choi, Cheol-Ho;Song, Yu-Seon;Kim, Kwang Beak
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.494-496
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    • 2017
  • 본 논문에서는 기존의 회전근개 건 파열 추출 방법을 개선하기 위하여 초음파 영상에서 환자 정보를 제거하여 ROI 영역을 추출한다. 추출된 ROI 영역에서 명암 대비를 강조하기 위해 기존의 사다리꼴 형태의 퍼지 스트레칭 기법에서 소속 함수를 개선한 퍼지 스트레칭 기법을 적용하여 힘줄과 연골 영역을 효과적으로 강조한다. 강조된 ROI 영역에서 Max-Min 이진화와 8방향 윤곽선 추적 기법 및 Monoton Cubic Spline 기법을 적용한 후에 라벨링 기법을 적용하여 힘줄 및 연골 영역을 추출한다. 추출된 힘줄과 연골 영역을 이용하여 회전근개 영역을 추출한다. 추출한 회전근개 영역에 SOM 기반 양자화 기법을 적용하여 회전근개 건 파열 영역을 추출한다. 제안된 회전근개 건 파열 영역 추출 방법을 다양한 초음파 회전근개 건 파열 영상을 대상으로 실험한 결과, 제안된 회전근개 건 파열 영역이 기존의 추출 방법보다 TPR 값이 증가되어 회전근개 건 파열 분석에 효과적인 것을 확인할 수 있었다.

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An Adaptive ROI Detection System for Spatiotemporal Features (시.공간특징에 대해 적응할 수 있는 ROI 탐지 시스템)

  • Park Min-Chul;Cheoi Kyung-Joo
    • The Journal of the Korea Contents Association
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    • v.6 no.1
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    • pp.41-53
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    • 2006
  • In this paper, an adaptive ROI(region of interest) detection system for spatialtemporal features is proposed. It utilizes spatiotemporal features for the purpose of detecting ROI. It is assumed that motion representing temporal visual conspicuity between adjacent frames takes higher priority over spatial visual conspicuity. Because objects or regions in motion usually draw stronger attention than others in motion pictures. In case of still images visual features that constitute topographic feature maps are used as spatial features. Comparative experiments with a human subjective evaluation show that correct detection rate of visual attention region is improved by exploiting both spatial and temporal features compared to the case of exploiting either feature.

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The Consideration of the Region of Interest on $^{99m}Tc$-DMSA Renal Scan in Pediatric Hydronephrosis Patients (수신증을 진단 받은 소아 환자의 DMSA 신장 검사에서 정확한 관심영역 설정에 대한 고찰)

  • NamKoong, Hyuk;Lee, Dong-Hyuk;Oh, Shin-Hyun;Cho, Seok-Won;Park, Hoon-Hee;Kim, Jung-Yul;Kim, Jae-Sam;Lee, Chang-Ho
    • The Korean Journal of Nuclear Medicine Technology
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    • v.16 no.1
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    • pp.27-33
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    • 2012
  • Purpose: Most of diagnosis in the pediatric hydronephrosis patients have been performed $^{99m}Tc$-DMSA renal scan. Then the region of interest (ROI) is set for comparative analysis of uptake ratio in left-right kidney after acquiring the image. But if the equipment set an automatic ROI, the ROI could include expanded renal pelvis due to hydronephrosis and the uptake ratio of left-right kidney will be incorrect result. Therefore this study compared both ROIs including expanded renal pelvis and excluding renal pelvis through experiment using normal kidney phantom and expanded renal pelvis phantom and suggested setting method of improved ROI. In addition, this study have been helped by readout doctor for investigate distinction radiopharmaceutical uptake between renal cortex and remained urine by expanded renal pelvis. Materials and Methods: The both of renal phantoms were filled with water and shacked with $^{99m}TcO_4$ 111 MBq. In order to describe the expanded renal pelvis, the five latex balloon were all filled with 10 mL water and each of balloon was mixed with $^{99m}TcO_4$ 18.5, 37, 55.5, 74, 92.5 MBq. And we made phantom with fixed $^{99m}TcO_4$activity of 37 MBq and mixed water 5, 10, 15, 20, 25 mL in each balloon. The left kidney was fixed its shape and the right kidney was modified like as hydronephrosis kidney by attached the latex balloons. And the acquiring counts were 2 million. After acquisition, we compared the image of ROI with Expanded renal pelvis and the image of ROI without renal pelvis for analyzing difference in the uptake ratio of left-right kidney and for reproducibility, set the ROI 5 times in the same images. Patients were injected $^{99m}Tc$-DMSA 1.5~1.9 MBq/kg and scanned 3 to 4 hours after injection. The each of 3 skillful radio technologists performed the comparing estimation by setting ROI. To determine statistical significance between two data, SPSS (ver. 17) Wilcoxon Signed Ranks Test was used. Results: As a result of renal phantom's experiment, we compared with average of counts Background (BKG) ratios in the setting of ROI including expanded renal pelvis and setting of excluding expanded renal pelvis. Therefore, they can obtain changed counts and changed ratios. Patient also can obtain same results. In addition, the radiopharmaceutical uptake in expanded renal pelvis was come out the remained urine that couldn't descend to ureter by the help of readout doctor. Conclusion: As above results, the case of setting ROI including expanded renal pelvis was more abnormally increasing uptake ratio than the case of setting ROI excluding expanded renal pelvis in analysis the uptake ratio in left-right kidney of hydronephrosis. Because of the work convenience and prompted analysis, the automatic ROI is generally used. But in case of the hydronephrosis study, we should set the manual ROI without expanded renal pelvis for an accurate observation of the uptake ratio of left-right kidney since the radiopharmaceutical uptake in expanded renal pelvis is the remained urine.

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Relevance Feedback using Region-of-interest in Retrieval of Satellite Images (위성영상 검색에서 사용자 관심영역을 이용한 적합성 피드백)

  • Kim, Sung-Jin;Chung, Chin-Wan;Lee, Seok-Lyong;Kim, Deok-Hwan
    • Journal of KIISE:Databases
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    • v.36 no.6
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    • pp.434-445
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    • 2009
  • Content-based image retrieval(CBIR) is the retrieval technique which uses the contents of images. However, in contrast to text data, multimedia data are ambiguous and there is a big difference between system's low-level representation and human's high-level concept. So it doesn't always mean that near points in the vector space are similar to user. We call this the semantic-gap problem. Due to this problem, performance of image retrieval is not good. To solve this problem, the relevance feedback(RF) which uses user's feedback information is used. But existing RF doesn't consider user's region-of-interest(ROI), and therefore, irrelevant regions are used in computing new query points. Because the system doesn't know user's ROI, RF is proceeded in the image-level. We propose a new ROI RF method which guides a user to select ROI from relevant images for the retrieval of complex satellite image, and this improves the accuracy of the image retrieval by computing more accurate query points in this paper. Also we propose a pruning technique which improves the accuracy of the image retrieval by using images not selected by the user in this paper. Experiments show the efficiency of the proposed ROI RF and the pruning technique.

An Adaptive ROI Decision for Real-time Performance in an Autonomous Driving Perception Module (자율주행 인지 모듈의 실시간 성능을 위한 적응형 관심 영역 판단)

  • Lee, Ayoung;Lee, Hojoon;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.2
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    • pp.20-25
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    • 2022
  • This paper represents an adaptive Region of Interest (ROI) decision for real-time performance in an autonomous driving perception module. Since the whole automated driving system consists of numerous modules and subdivisions of module occur, it is necessary to consider the characteristics, complexity, and limitations of each module. Furthermore, Light Detection And Ranging (Lidar) sensors require a considerable amount of time. In view of these limitations, division of submodule is inevitable to represent high real-time performance for stable system. This paper proposes ROI to reduce the number of data respect to computation time. ROI is set by a road's design speed and the corresponding ROI is applied differently to each vehicle considering its speed. The simulation model is constructed by ROS, and overall data analysis is conducted by Matlab. The algorithm is validated using real-time driving data in urban environment, and the result shows that ROI provides low computational costs.

Transformer Network for Container's BIC-code Recognition (컨테이너 BIC-code 인식을 위한 Transformer Network)

  • Kwon, HeeJoo;Kang, HyunSoo
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.1
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    • pp.19-26
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    • 2022
  • This paper presents a pre-processing method to facilitate the container's BIC-code recognition. We propose a network that can find ROI(Region Of Interests) containing a BIC-code region and estimate a homography matrix for warping. Taking the structure of STN(Spatial Transformer Networks), the proposed network consists of next 3 steps, ROI detection, homography matrix estimation, and warping using the homography estimated in the previous step. It contributes to improving the accuracy of BIC-code recognition by estimating ROI and matrix using the proposed network and correcting perspective distortion of ROI using the estimated matrix. For performance evaluation, five evaluators evaluated the output image as a perfect score of 5 and received an average of 4.25 points, and when visually checked, 224 out of 312 photos are accurately and perfectly corrected, containing ROI.

Destination address block locating algorithm for automatic classification of packages (택배 자동 분류를 위한 주소영역 검출 알고리즘)

  • Kim, Bong-Seok;Kim, Seung-Jin;Jung, Yoon-Su;Im, Sung-Woon;Ro, Chul-Kyun;Won, Chul-Ho;Cho, Jin-Ho;Lee, Kuhn-Il
    • Journal of Sensor Science and Technology
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    • v.12 no.3
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    • pp.128-138
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    • 2003
  • In this paper, we proposed the algorithm for locating destination address block (DAB) from automatic system to classify packages. For locating DAB, because the size of obtained images is are very large, we select the region of interesting (ROI) to reduce time carrying into algorithm. After selecting the ROI, proposed algorithm is carried out within the ROI. We extract the outline of the handwriting part of the DAB and the rest components within the obtained ROI using thresholding. We carry out labeling to extract each connected component for extracted outline and the rest components. We extract the outline of the handwriting part of the DAB using the geometrical characteristic of the outline of the handwriting part of the DAB among many connected components. The last, we extract the locating DAB using the outline of the handwriting part of the DAB.