• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2737-2753
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• 2013

In this study, we propose a novel salient object detection strategy based on regional contrast and relative spatial compactness. Our algorithm consists of four basic steps. First, we learn color names offline using the probabilistic latent semantic analysis (PLSA) model to find the mapping between basic color names and pixel values. The color names can be used for image segmentation and region description. Second, image pixels are assigned to special color names according to their values, forming different color clusters. The saliency measure for every cluster is evaluated by its spatial compactness relative to other clusters rather than by the intra variance of the cluster alone. Third, every cluster is divided into local regions that are described with color name descriptors. The regional contrast is evaluated by computing the color distance between different regions in the entire image. Last, the final saliency map is constructed by incorporating the color cluster's spatial compactness measure and the corresponding regional contrast. Experiments show that our algorithm outperforms several existing salient object detection methods with higher precision and better recall rates when evaluated using public datasets.

• IEIE Transactions on Smart Processing and Computing
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• 제6권4호
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• pp.229-236
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• 2017

This paper presents an efficient object-based color image-retrieval algorithm that is suitable for the classification and retrieval of images from small to mid-scale datasets, such as images in PCs, tablets, phones, and cameras. The proposed method first finds salient regions by using regional feature vectors, and also finds several dominant colors in each region. Then, each salient region is partitioned into small sub-blocks, which are assigned 1 or 0 with respect to the number of pixels corresponding to a dominant color in the sub-block. This gives a binary map for the dominant color, and this process is repeated for the predefined number of dominant colors. Finally, we have several binary maps, each of which corresponds to a dominant color in a salient region. Hence, the binary maps represent the spatial distribution of the dominant colors in the salient region, and the union (OR operation) of the maps can describe the approximate shapes of salient objects. Also proposed in this paper is a matching method that uses these binary maps and which needs very few computations, because most operations are binary. Experiments on widely used color image databases show that the proposed method performs better than state-of-the-art and previous color-based methods.

• 정보처리학회논문지B
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• 제13B권5호
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• pp.515-524
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• 2006

배경추출은 비디오 감시 시스템에서 움직이는 물체를 찾는데 중요한 기술이다. 본 논문에서는 벡터 정렬을 이용한 새로운 온라인 컬러 배경 추출 방법을 제안한다. 제안된 방법에서 배경은 물체보다 발생빈도가 높다는 사실을 이용하여, 연속된 프레임의 컬러화소 값들의 벡터 미디언을 그 화소에서의 배경이라 간주한다. 본 알고리즘에서 현재 프레임의 물체는 얻어진 배경과의 거리가 문턱치보다 큰 화소들의 집합으로 구성된다. 알고리즘의 성능을 평가하기 위하여 온라인 가우시안 혼합 모델(Gaussian Mixture Model)을 이용한 다중 배경추출 방법과 비교하였으며, 비교결과 유사 또는 우월한 실험 결과를 확인하였다.

• 한국정밀공학회지
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• 제27권6호
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• pp.24-31
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• 2010

Laser carbonization of a polymer layer can be employed in various applications in the microelectronics industry, e.g repairing brightness pixels of an LCD panel. In this work, the process of thermal degradation of LCD color filter polymer by various laser sources with pulsewidths from CW to fs is studied. LCD pixels are irradiated by the lasers and the threshold irradiance of LCD color filter polymer carbonization is experimentally measured. In the numerical analysis, the transient temperature distribution is calculated and the number density of carbonization in the polymer layer is also estimated. It is shown that all the lasers can carbonize the polymer layers if the output power is adjusted to meet the thermal conditions for polymerization and that pulsed lasers can result in more uniform distribution of temperature and carbonization than the CW laser.

• 대한전자공학회논문지SD
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• 제43권11호
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• pp.26-36
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• 2006

본 논문에서는 화소간의 상관관계를 이용한 CCD/CMOS 이미지 센서용 효율적인 색 보간 기법을 제안한다. 최근 각광받고 있는 CCD/CMOS 이미지 센서는 컬러 필터 배열(Color Filter Array)을 사용하기 때문에, 각 화소는 컬러 영상을 만들기 위한 3가지 색 채널 중 한 가지 채널만 갖고 있게 된다. 따라서 컬러 영상을 만들기 위해서는 색 보간 구조가 필요하다. 최근 제안되는 색 보간 기법은 보간된 영상의 품질 향상에만 주력하고 있는데 반해, 본 논문에서는 낮은 복잡도를 갖으면서 잘못된 색을 최소화하기 위한 방법을 제안한다. 제안된 색 보간 기법에서는 인접한 화소간의 상관관계를 이용하여, 현재 화소의 방향성을 결정할 때 이웃 화소의 방향성 정보를 이용하였다. 기존의 방향성을 고려한 색 보간 기법에 제안된 기법을 적용한 결과, 알고리즘의 종류에 따라 PSNR이 $0.09{\sim}0.47dB$ 향상되었고, 대부분의 잘못된 색(False color)을 최소화함으로써 색 보간된 컬러영상의 품질이 향상되었다. 제안된 색 보간 기법은 Verilog HDL 및 FPGA를 이용하여 실시간으로 구현 검증되었다. 0.25um CMOS 표준 셀 라이브러리를 이용하여 합성하였을 때, 총 게이트 수는 12K개였으며 5개의 라인 메모리가 사용되었다.

• 스마트미디어저널
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• 제2권2호
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• pp.8-13
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• 2013

Nowadays, the saliency region detection has become a popular research topic because of its uses for many applications like object recognition and object segmentation. Some of recent methods apply color distinctiveness based on an analysis of statistics of color image derivatives in order to boosting color saliency can produce the good saliency maps. However, if the salient regions comprise more than half the pixels of the image or the background is complex, it may cause bad results. In this paper, we introduce the method to handle these problems by using maximum symmetric surround. The results show that our method outperforms the previous algorithms. We also show the segmentation results by using Otsu's method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.670-673
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• 2002

This paper proposes a digital algorithm for gray-scale/color image segmentation of real-time video signals and a cell-network-based implementation architecture in state-of-the-art CMOS technology. Through extrapolation of design and simulation results we predict that about 300$\times$300 pixels can be integrated on a chip at 100nm CMOS technology, realizing very high-speed segmentation at about 1600sec per color image. Consequently real-time color-video segmentation will become possible in near future.

• 한국산업정보학회논문지
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• 제16권2호
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• pp.31-38
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• 2011

피부색은 자동화된 얼굴 인식을 위한 매우 중요한 정보 중의 하나이다. 본 논문에서는 다층 신경망(Multi-Layer Perceptron)을 이용한 피부 영역 검출 기법을 제안하였다. 제안된 방법은 적응적 조명 보정 기법을 통해 피부색 영역의 검출 성능을 개선하였고, 전처리 필터를 적용하여 피부색이 아닌 영역을 먼저 제거시킴으로써 처리 속도를 향상시켰다. 제안된 방법의 실험 결과 기존의 방법과 비교하여 보다 우수한 검출 결과를 나타냈으며, 처리 속도 또한 약 31~49% 향상시킬 수 있었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.418-420
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• 1993

In this paper, we proposed a new FMS Landmark recognition algorithm using color images. Firstly, a NTSC image fame is captured, and then it is converted to a field image in order to reduce the image blurring from the AGV motion. Secondly, the landmark is detected via the comparison of the color vectors of image pixels with the landmark color. Finally, the identification of FMS landmark is executed using a newly designed landmark pattern with a set of reference points. The landmark pattern is normalized against its translation, rotation, and scaling. And then, its vertical projection data are fisted for the pattern classification using the standard data set. Experimental results show that our scheme performs well.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.520-524
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• 2009

In compressed color images, colors are usually represented by luminance and chrominance (YCbCr) components. Considering characteristics of human vision system, chrominance (CbCr) components are generally represented more coarsely than luminance component. Aiming at possible recovery of chrominance components, we propose a model-based chrominance estimation algorithm where color images are modeled by a Markov random field (MRF). A simple MRF model is here used whose local conditional probability density function (pdf) for a color vector of a pixel is a Gaussian pdf depending on color vectors of its neighboring pixels. Chrominance components of a pixel are estimated by maximizing the conditional pdf given its luminance component and its neighboring color vectors. Experimental results show that the proposed chrominance estimation algorithm is effective for quality improvement of compressed color images such as JPEG and JPEG2000.