• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1189-1196
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• 2015

In this paper, we proposed automatic extraction of brain tumor using morphological operation and statistical tumors size in MR images. Neurosurgery have used gamma-knife therapy by MR images. However, the gamma-knife plan systems needs the brain tumor regions, because gamma-ray should intensively radiate to the brain tumor except for normal cells. Therefore, gamma-knife plan systems spend too much time on designating the tumor regions. In order to reduce the time of designation of tumors, we progress the automatical extraction of tumors using proposed method. The proposed method consist of two steps. First, the information of skull at MRI slices remove using statistical tumors size. Second, the ROI is extracted by tumor feature and average of tumors size. The detection of tumor is progressed using proposed and threshold method. Moreover, in order to compare the effeminacy of proposed method, we compared snap-shot and results of proposed method.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.447-448
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• 2006

In this paper, we propose tracking algorithm using multi resolution in wavelet transform domain. This algorithm consists of two steps. The first step is feature extraction that is select feature-points using 1-level wavelet transform in ROI (Region of Interest). The other step is feature tracking. Based on multi resolution of wavelet transform, we estimate a displacement between current frame and next frame on the basis of selected feature-points. Experimental results show that the proposed algorithm confirmed a better performance than a centroid tracking and correlation tracking.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.615-618
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• 2003

본 논문에서는 컨베이어 벨트상에서 이송되는 대용량 소포영상의 획득과정을 통해 ROI(Region of Interest) 고속추출하기 위한 방법 중에서 소포의 면적을 산출하기 위한 외형 좌표값을 산출하는 방법을 제시한 것이다. 이송하는 과정에서 높이센서의 값과 투입되는 각도에 따라 최장길이가 다르지만 이 값도 산출이 용이하다 이와 같은 정보와 결합하여 소포의 부피를 산출을 위해 사용될 수 있는 소포의 외형 좌표값들의 산출 방법과 활용방법을 제시한 것이다. 초기과정에는 불필요한 영역을 검사하기 위한 조건과 유사한 패턴을 단계적으로 제거하는 방법을 적용하였다. $4,096{\times}4,096$ 이상의 대용량 영상에서 불필요한 영역 제거 시간을 포함하여 평균 30.85msec 이내에 추출이 가능한 방법을 제시한 것이다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.850-852
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• 2005

차량을 포함하는 임의의 영상에서 번호판 추출은 다양한 조명조건 및 배경, 촬영 각도, 번호판 종류 등의 요인으로 인해 고도의 영상처리 과정을 필요로 한다. 본 논문에서는 실제 환경에서 발생할 수 있는 이러한 요인들에 대해 강건한 번호판 추출 방법을 제안한다. 제안하는 방법은 입력영상의 RGB 성분들을 색상성분과 영암성분으로 분리할 수 있는 칼라모델 HSI로 변환하고 H(hue)와 S(saturation)성분을 이용하여 번호판의 배경색상을 고려한 칼라 퍼지지도를 구성한다. 또한, I(intensity)성분을 이용하여 에지밀도를 추출하고 에지밀도 지도에 기반한 영역분리 퍼지지도를 생성한다. 마지막으로, 후보영역 탐색을 위해 칼라 퍼지지도와 영역분리 퍼지지도를 결합하고, 연결성분 해석(Connected Component Analysis)을 통해 ROI(Region Of Interest)를 추출한다. 제안하는 방법의 유효성 검증을 위해 조명 및 촬영 각도에 제한을 거의 두지 않고 촬영된 차량 영상 410장을 실험 영상으로 사용하였다. 실험 결과에서는 $97.1\%$의 효과적인 추출 성공률을 볼 수 있었다.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.17-24
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• 2015

In this paper, a novel scheme for correcting rotated region in medical images using SIFT(Scale Invariant Feature Transform) algorithm is presented. Using the feature extraction function of SIFT, the rotation angle of rotated object in medical images is calculated as follows. First, keypoints of both reference and rotated medical images are extracted by SIFT. Second, the matching process is performed to the keypoints located at the predetermined ROI(Region Of Interest) at which objects are not cropped or added by rotating the image. Finally, degrees of matched keypoints are calculated and the rotation angle of the rotated object is determined by averaging the difference of the degrees. The simulation results show that the proposed scheme has excellent performance for correcting the rotated region in medical images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.73-75
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• 2014

본 논문에서는 원본 초음파 영상에서 스케일을 측정한 후, 영상의 확대 비율을 분석하여 충수염 객체의 크기에 대한 범위를 설정한다. 제안된 방법은 초음파 영상에서 ROI 영역을 추출한 후, 사다리꼴 타입의 소속 함수를 이용한 Fuzzy 이진화와 8방향 윤곽선 추적 기법을 적용하여 잡음을 제거한 후에 근막을 추출한다. 추출된 복부 근육의 근막 하단 경계선을 Cubic Spline 보간법을 이용하여 근막의 하단 영역을 추출한다. 초음파 영상의 근막을 기준으로 근막 영역을 제거한 후, SOM(Self-Organizing Map) 알고리즘을 이용하여 충수염의 후보 영역을 추출한다. 추출된 충수염의 후보 영역에 8방향 윤곽선 추적기법을 적용하여 충수염을 추출한다. 제안된 방법을 초음파 영상에 적용하여 실험한 결과, 기존의 충수염 추출 방법보다 충수염 영역이 비교적 정확히 추출되고 충수염의 크기를 측정할 수 있는 것을 실험을 통하여 확인하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.65-71
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• 2014

This paper present the multi-modal user distance estimation system using mono camera and mono microphone basically equipped with a mobile device. In case of a distance estimation method using an image, we is estimated a distance of the user through the skin color region extraction step, a noise removal step, the face and eyes region detection step. On the other hand, in case of a distance estimation method using speech, we calculates the absolute difference between the value of the sample of speech input. The largest peak value of the calculated difference value is selected and samples before and after the peak are specified as the ROI(Region of Interest). The samples specified perform FFT(Fast Fourier Transform) and calculate the magnitude of the frequency domain. Magnitude obtained is compared with the distance model to calculate the likelihood. We is estimated user distance by adding with weights in the sorted value. The result of an experiment using the multi-modal method shows more improved measurement value than that of single modality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1978-1984
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• 2016

This paper proposes a robust vehicle detecting method by using Adaboost and CLAHE(Contrast-Limit Adaptive Histogram Equalization). We propose two method to detect vehicle effectively. First, we are able to judge rainy and night by converting RGB value to brightness. Second, we can detect a taillight, designate a ROI(Region Of Interest) by using CLAHE. And then, we choose an Adaboost algorithm by comparing traditional vehicle detecting method such as GMM(Gaussian Mixture Model), Optical flow and Adaboost. In this paper, we use proposed method and get better performance of detecting vehicle. The precision and recall score of proposed method are 0.85 and 0.87. That scores are better than GMM and optical flow.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.237-244
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• 2002

In this paper, we propose a stereo image recognition-based method for measuring the volume of the rectangular parallelepiped. The method measures the volume from two images captured with two CCD (charge coupled device) cameras by sequential processes such as ROI (region of interest) extraction, feature extraction, and stereo matching-based vortex recognition. The proposed method makes it possible to measure the volume of the 3D object at high speed because only a few features are used in the process of stereo matching. From experimental results, it is demonstrated that this method is very effective for measuring the volume of the rectangular parallelepiped at high speed.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.9-14
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• 2018

The vision system is a device for acquiring images and analyzing and discriminating inspection areas. Demand for use in the automation process has increased, and the introduction of a vision-based inspection system has emerged as a very important issue. These vision systems are used for everyday life and used as inspection equipment in production processes. Image processing technology is actively being studied. However, there is little research on the area definition for extracting objects such as character recognition or semiconductor packages. In this paper, define a region of interest and perform edge extraction to prevent the user from judging noise as an edge. We propose a noise-robust alignment correction model that can extract the edge of a region to be inspected using the distribution of edges in a specific region even if noise exists in the image. Through the proposed model, it is expected that the product production efficiency will be improved if it is applied to production field such as character recognition of tire or inspection of semiconductor packages.