• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.339-346
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• 2003

In this paper, we propose a new method in which interpolation images are created by using a small number of axiai T2-weighted images instead of using many sectional images for 3D visualization of brain MR images. For image Interpolation, an important part of this process, we first segment a region of interest (ROI) that we wish to apply 3D reconstruction and extract the boundaries of segmented ROIs and MBR information. After the image size of interpolation layer is determined according to the changing rate of MBR size between top slice and bottom slice of segmented ROI, we find the corresponding pixels in segmented ROI images. Then we calculate a pixel's intensity of interpolation image by assigning to each pixel intensity weights detected by cube interpolation method. Finally, 3D reconstruction is accomplished by exploiting feature points and 3D voxels in the created interpolation images.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.737-747
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• 2012

Recently, in order to support automatic meter reading for conventional metering devices, an image processing-based approach of recognizing the number meter data in the captured meter images has attracted many researchers' interests. Numerical character segmentation is a very critical process for successful recognition. In this paper, we propose an efficient numeric character segmentation method which can segment numeric characters well for any metering device types under diverse illumination environments. The proposed method consists of two consecutive stages; detection of number area containing all numbers as a tight ROI(Region of Interest) and segmentation of numerical characters in the ROI. Detection of tight ROI is achieved in two steps: extraction of rough ROI by utilizing horizontal line segments after illumination enhancement preprocessing, and making the rough ROI more tight through clipping utilizing vertical and horizontal projection about binarized ROI. Numerical character segmentation in the detected ROI is stably achieved in two processes of 'vertical segmentation of each number region' and 'number segmentation in the each vertical segmented number region'. Through the experiments about a homegrown meter image database containing various meter type images of low contrast, low intensity, shadow, and saturation, it is shown that the proposed numeric character segmentation method performs effectively well for any metering device types under diverse illumination environments.

• Journal of the Korean Society of Radiology
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• v.16 no.5
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• pp.575-583
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• 2022

Magnetic resonance diffusion tensor imaging (DTI) has revealed the disruption of brain white matter microstructure in normal aging and alcoholism undetectable with conventional structural MR imaging. we plan to analyze the FA measurements of the ROI of dangerous drinkers selected from Alcohol Use Disorders Identification Test (AUDIT) and Tract-Based Spatial Statics (TBSS) tool was used to extract FA values in the ROI from the image acquired through the pre-processing process. TBSS has a higher sensitivity of the FA value and MD value in the white matter than the brain gray matter, and has the advantage of quantitatively deriving the unlimited degree of brain nerve fibers, and more specialized in the brain white matter. We plan to analyze the fractional anisotropy (FA) measurement value for damage by selecting the center of the anatomical structure of the white matter region of the brain with high anisotropy among the brain neural networks that are particularly vulnerable to alcohol as the region of interest (ROI). In this study, we expected that alcohol causes damage to the brain white matter microstructure from FA value in various areas including both Choroid plexus. Especially, In the case of the moderate drunker, the mean value of FA in Lt, Rt. Choroid plexus was 0.2831 and 0.2872, whereas, in the case of the severe drunker, the mean value of FA was 0.1972 and 0.1936. We found that the higher the score on the AUDIT scale, the lower the FA value in ROI region of the brain white matter. Using the AUDIT scale, the guideline for the FA value of DTI can be presented, and it is possible to select a significant number of potentially severe drinkers. In other words, AUDIT was proved as useful tool in screening and discrimination of severe drunker through DTI.

• 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 the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2121-2128
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• 2015

In this paper presents a method of extracting reliable and regions of interest (ROI) in barcode for the purpose of factory automation. backgrounds are separated based on directional components and the characteristics of detected patterns. post-processing is performed on candidate images with analysis of problems caused by blur, rotation and areas of high similarity. In addition, the resizing factor is used to achieve faster calculations through image resizing. The input images contained multiple product or barcode for application to diverse automation environments; a high extraction success rate is accomplished despite the maximum shooting distance of 80 cm. Simulations involving images with various shooting distances gave an ROI detection rate of 100% and a post-processing success rate of 99.3%.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.793-795
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• 2004

우편물을 배달순서대로 정렬하는 과정을 순로구분이라고 하는데, 우편물의 처리과정에서 가장 많은 시간이 소요되는 부분이 바로 이 순로구분 과정이다. 우정선진국의 순로구분 자동화 시스템은 바코드를 이용하여 순로구분를 자동으로 처리하고 있지만, 국내의 시스템은 순로구분의 전 단계까지만 수행하고 나머지 과정은 배달원이 자신의 경험에 의해 수작업으로 처리하고 있다. 본 논문에서는 우편물을 자동 검증하는 방법으로 바코드 대신에 우편영상 특징기반의 Virtual ID 사용을 위한 유사한 우편영상 추출방법을 제안한다. 제안 방법은 질의영상과 후보영상간의 유사성을 판별할 때, 각 영상의 수취인 영역에서 추출된 문자열 Bounding Box들의 대응되는 쌍을 결정하고 그 쌍들의 영역이 겹치는 정도를 유사도로 측정하는 방법이다 291개의 우편영상에 대하여 실험한 결과, 289개의 영상이 정상적으로 유사한 우편영상으로 추출되었다. 또한, 유사한 우편영상으로 추출된 영상의 평균개수는 3.78개로 비교적 높게 나왔지만 이는 실험 데이터에 동일 DM 발송 우편물이 연속적으로 위치한 경우가 많았기 때문이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.127-130
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• 2006

본 논문에서는 MPEG-7 의 특징 기술자를 이용하고, 초기 중요도 가중치를 고려한 관심영역(ROI: Region-Of-Interest) 기반의 의료 영상 검색 시스템을 제안한다. 의료 영상에서 의미 없는 배경 부분을 제거하고, 영역 추출 처리 시간을 줄이는 관심 윈도우(AW: Attention Window)를 생성하여 관심 영역 세그먼테이션을 수행한다. 또한 인간 시각에 부합하는 검색 성능의 향상을 위해 특징 벡터 거리 계산에서 영역의 초기 가중치를 설정하였다. 실험에서 구현된 시스템은 의료 영상을 효과적으로 찾아내며, 조합된 특징과 가중치를 이용한 유사도 측정으로 검색 성능이 향상됨을 보여준다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.75-86
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• 2004

This paper proposes a method to speed up the document image binarization using a water flow model. The proposed method extracts the region of interest (ROI) around characters from a document image and restricts pouring water onto a 3-dimensional terrain surface of an image only within the ROI. The amount of water to be filed into a local valley is determined automatically depending on its depth and slope. The proposed method accumulates weighted water not only on the locally lowest position but also on its neighbors. Therefore, a valley is filed enough with only one try of pouring water onto the terrain surface of the ROI. Finally, the depth of each pond is adaptively thresholded for robust character segmentation, because the depth of a pond formed at a valley varies widely according to the gray-level difference between characters and backgrounds. In our experiments on real document images, the Proposed method has attained good binarization performance as well as remarkably reduced processing time compared with that of the existing method based on a water flow model.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.289-296
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• 2004

General watermarking techniques tend not to consider intrinsic characteristics of image, so that watermarks are embeded to entire images. In this paper, we present a watermarking algorithm based on wavelet domain, and the watermark is embedded into large coefficients in region of interest(ROI) being based on principle of multi-threshold watermark coding(MTWC) for robust watermark insertion. We try to accomplish both image duality and robustness using human visual system(HVS). The watermarks are embedded in middle frequency bands because the distortion degree of watermarked images appears to be less than lower frequency bands, and the embedded watermarks in the middle bands showed high extraction ratios after some distortion. The watermarks are consisted of pseudo random sequences and detected using Cox's similarity mesurement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2321-2326
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• 2011

Cervical vertebrae are a complex structure and an important part of human body connecting the head and the trunk. In this paper, we propose a method to extract sternocleidomastoid muscle from ultrasonography images of cervical vertabrae automatically. In our method, Region of Interests(ROI) is extracted first from an ultrasonography image after removing unnecessary auxiliary information such as metrics. Then we apply Ends-in search stretching algorithm in order to enhance the contrast of brightness. Average binarization is then applied to those pixels which its brightness is sufficiently large. The noise part is removed by image processing algorithms. After extracting fascia encloses sternocleidomastoid muscle, target muscle object is extracted using the location information of fascia according to the number of objects in the fascia. When only one object is to be extracted, we search downward first to extract the target muscle area and then search from right to left to extract the area and merge them. If there are two target objects, we extract first from the upper-bound of higher object to the lower-bound of lower object and then remove the fascia of the target object area. Smearing technique is used to restore possible loss of the fat area in the process. The thickness of sternocleidomastoid muscle is then calculated as the maximum thickness of those extracted objects. In this experiment with 30 real world ultrasonography images, the proposed method verified its efficacy and accuracy by health professionals.