• 한국통신학회논문지
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• 제23권9A호
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• pp.2325-2332
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• 1998

In this paper, the quality scalable coding of selected region is presented. If a region is semantically more important than the others, it is appropriate that the image compression shcem is capable of handling the regional semantic difference because the information loss of the region of interest is more severe. We propose the quality scalable coding with its model by interoducing the quality scale parameter. It is more extended and generalized image compression philosophy than te conventional coding. As an implementation of the proposed quality scalable coding, H.263 based scheme is presented. This scheme can control the temporal and spatial quality efficiently, and improve the reconstructed image quality of the region of interest.

• Asia Marketing Journal
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• 제18권4호
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• pp.99-124
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• 2017

Little research on sensory study has been conducted from a marketing perspective and most of sensory studies have been done from a science perspective. Thus, this study examined wine sensory perceptions in the consumers' minds, which is how wine consumers associate grape variety Shiraz/ Syrah by the three different region of origins with specific sensory images. Total 234 questionnaires were collected from online wine community members at restaurants in Korea. The main results show that the most two shared sensory images of Shiraz/ Syrah were 'Dry' and 'Fruity' across the three region of origins. For Barossa Shiraz, the unique images were mainly found in Aroma image category such as 'Chocolate', 'Prune', whereas for Rhone Syrah, the unique images were mainly revealed in Overall image category e.g. 'Deep', 'Fascinating'. Additionally, this study confirmed that Maipo Valley is not recognizable region of origin of Shiraz/ Syrah. This study employed a free choice, Pick Any and conducted correspondence analysis to find out the degree of associations of sensory images and each region of origin.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4386-4404
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• 2016

Most existing salient object detection algorithms commonly employed segmentation techniques to eliminate background noise and reduce computation by treating each segment as a processing unit. However, individual small segments provide little information about global contents. Such schemes have limited capability on modeling global perceptual phenomena. In this paper, a novel salient object detection algorithm is proposed based on region merging. An adaptive-based merging scheme is developed to reassemble regions based on their color dissimilarities. The merging strategy can be described as that a region R is merged with its adjacent region Q if Q has the lowest dissimilarity with Q among all Q's adjacent regions. To guide the merging process, superpixels that located at the boundary of the image are treated as the seeds. However, it is possible for a boundary in the input image to be occupied by the foreground object. To avoid this case, we optimize the boundary influences by locating and eliminating erroneous boundaries before the region merging. We show that even though three simple region saliency measurements are adopted for each region, encouraging performance can be obtained. Experiments on four benchmark datasets including MSRA-B, SOD, SED and iCoSeg show the proposed method results in uniform object enhancement and achieve state-of-the-art performance by comparing with nine existing methods.

• 대한의용생체공학회:의공학회지
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• 제11권2호
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• pp.217-226
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• 1990

This paper presents a new algorithm that extracted lung region in X-ray and enhanced the region. With a lung region that was extracted by histogram threshold value, it was diffi cult to detect perfect lung boundary. Therefore we presented perfect lung boundary detection method using apex detection and apex region restoration. Also, by applying modified equalization algorithm and presented function to inside of lung region, we want to give help to automatic diagnosis In X-ray chest image. Presented main line trace algorithm gave good result in detection of lung boundary And, as apex detection method using lung row and column gray level average value found more correct place of lung than the rpethod of prior algorithm, we succeeded perfect lung region detection, Also, presented function that had lung region's gray level distribution characteristic was very effective to image enhancement.

• 대한전자공학회논문지SP
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• 제46권5호
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• pp.111-119
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• 2009

본 논문에서는 영상의 영역별 특성을 고려한 영상의 보간 방법을 제안한다. 먼저 입력 영상은 에지 영역과 평탄한 저주파 영역으로 나뉜다. 그리고 에지 영역은 다시 방향성이 존재하는 에지 영역과 텍스처와 같이 에지의 방향성이 존재하지 않는 복잡한 고주파 영역으로 구분된다. 평탄한 저주파 영역에서는 쌍선형보간법 (Bilinear Interpolation), 방향성이 없는 복잡한 고주파 영역은 3차 컨벌루션 보간법 (Cubic Convolution Interpolation), 방향성이 있는 에지 영역은 NEDI (New Edge directed Interpolation)를 각각 적용한다. 다양한 영상에 대한 실험결과 제안한 방법이 기존이 방법보다 주관적 화질이 뛰어나고 우수한 성능을 발휘하는 것을 확인하였다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1995년도 추계학술대회
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• pp.171-172
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• 1995

In this paper, an anatomical labeling system for assisting localization of region of interest on human brain imaging is represented. Model image for labeling anatomical name on the other image is Atlas. Object image to be labeled, such as CT, MR, and PET, is registered onto Atlas. And then, anatomical name for region of interest is appeared on a window by clicking mouse button on object image. The same part named anatomically on that region is labeled and drawn on object image.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.827-828
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• 2008

Blur identification is the first and the most important step of restoring images. Edge region of the image usually conveys important information of blur parameters. In this paper we propose a region-based edge extraction method for estimating point-spread-function (PSF). As a result, the proposed method can detect the starting and the ending points of a step response, and provides the PSF parameters to the restoration process.

• 디지털콘텐츠학회 논문지
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• 제17권6호
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• pp.593-601
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• 2016

본 논문은 휘도 성분 영상으로부터 컬러 성분 영상들을 추정 부호화함으로써 높은 압축률을 달성할 수 있는 영역 기반 스펙트럴 상관 추정 부호화 방법에 관한 것이다. 제안된 방법은 3단계로 구성되어 있다. 우선, 정규 색차합 영상과 휘도 영상을 이용해 산출한 Y/C 비트 평면합 영상을 대상으로 영상 분할을 수행하여 영역들의 형상 정보를 추출한다. 이후, 각 영역 단위로 휘도 영상과 R, B 영상 간의 근사화 자승 오차가 최소가 되도록 하는 비례 인자와 가감 인자를 산출한다. 최종적으로, 각 영역의 비례 인자와 가감 인자를 비트스트림으로 부호화한다. 컴퓨터 시뮬레이션 결과에 따르면, 제안된 방법은 동일한 PSNR에서 두 칼라 성분 영상을 부호화하기 위해 소요되는 bpp를 비교할 때, JPEG/베이스라인 혹은 JEPG2000/EBCOT 알고리즘에 비해 2배 혹은 3배 이상의 압축률을 제공한다.

• 디지털콘텐츠학회 논문지
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• 제18권1호
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• pp.71-77
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• 2017

가상광고는 컴퓨터 그래픽을 이용하여 스포츠영상과 같은 미디어제작영상에 제품의 이미지, 로고, 선전문구 등을 삽입하는 광고기법이다. 최근 영상처리 기술과 컴퓨터 성능의 상승으로 인해 스포츠영상에 가상광고를 삽입하기 위한 기술적인 요소가 충족되어 영상 내에 가상광고의 삽입이 활발하게 진행되고 있다. 또한 자동적인 가상광고 삽입을 위한 영상 처리 기술이 가상광고 영역에서 중요한 연구 분야로 자리 잡고 있다. 이에 본 논문에서는 스포츠 영상 내에서 자동적으로 가상광고를 삽입하기 위해 영상처리 기법과 기계학습을 활용하여 저정보 영역을 추출하는 방법을 제안한다. 제안 방법은 영상의 밝기 정도를 히스토그램을 통해 분석하고 기계학습 방법을 활용하여 저정보 영역을 추출한다.

• 전자공학회논문지A
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• 제33A권5호
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• pp.203-211
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• 1996

This paper describes CAD tools for the construction of image database in IC chip analysis CAD system. For IC chip analysis by high-resolution microscopy, the image database is essential to manage more than several thousand images. But manual database construction is error-prone and time-consuming. In order to solve this problem, we develop a set of CAD toos that include image grabber to capture chip images, image editor to make the whole chip image database from the grabbed images, and image divider to reconstruct the database that consists of evenly overlapped images for efficient region search. we also develop an interactive pattern matching method for user-friendly image editing, and a heuristic region search method for fast image division. The tools are developed with a high-performance graphic hardware with JPEG image comparession chip to process the huge color image data. The tools are under the field test and experimental resutls show that the database construction time can be redcued in 1/3 compared to manual database construction.