• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.499-501
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• 2000

본 논문에서는 영역기반 검색환경을 제공하는 FRIP(Finding Region in the Pictures) 시스템을 소개한다. FRIP 시스템은 영역 기반 검색환경을 제공하기 위해서, 우선적으로 영상을 분할하고, 각 분할된 영역으로부터 색상, 질감, 크기, 모양, 위치 정보와 같은 최적의 특징 벡터들을 추출하여 색인화시킨다. 그런 뒤에, 사용자가 검색하고자 하는 영역과 검색 영상 수 k를 입력하면, 유사성 측정 식에 의해 가장 유사한 k만큼의 영상을 우선 순위 형태로 사용자에 보여주게 된다. 본 시스템에서는 영상을 분할하기 위해서 기본적인 RGB 색상계를 확장(Scaling 및 이동(Shifting) 알고리즘을 통해 영상의 대비 정도가 향상된 새로운 색상계로 변환시키고, 원형 필터를 설계하여, 영역 안에 포함된 의미 없는 작은 영역을 제거하도록 하였다. 그리고 이렇게 분할된 각 영역들로부터, 본 시스템에서 제안하는 모양 기술자인 MRS(Modified Radius-based Signature)를 포함하여 5가지의 최적의 특징 벡터들을 전처리 단계에서 데이터베이스에 색인으로 저장하고 유사성 측정을 위한 수치로 사용하였다.

• Proceedings of the KAIS Fall Conference
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• 2008.11a
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• pp.368-370
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• 2008

대한민국 대표 축제로 자리 잡은 보령머드축제의 핵심 프로그램인 머드 셀프마사지 행사의 재미와 다양성을 부여하기 위하여, 색상이 함유된 머드에 관한 연구를 수행하였다. 머드 고유의 낮은 명도를 조절하고자 이산화티탄을 첨가하여 머드의 질감을 유지하면서 색상이 발현되는 이산화티탄의 함량을 실험하고, 결정된 혼합비율에 황색산화철을 첨가하여 색상의 발현도를 색차계, 육안검사, 사용감 등으로 판단하였다. 결정된 색상은 물에 젖음 시 발색정도와 세척상태를 검토하여 보령머드 축제 프로그램인 머드 셀프마사지 행사에 사용하여 축제의 다양성을 높이고 또한 한국의 고유색인 오방색을 나타낼 수 있는 유색머드를 개발하고자 하였다.

• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.41-45
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• 2011

This paper presents a fire detection criterion based on flame color, spatial and temporal characteristic analysis of color fire images. To propose the criterion, Firstly the fire candidate regions were selected by using analyzed Cr and Y threshold value, and then texture analysis of candidate regions was performed by using DCT. Finally variation of Y values of these regions was calculated for temporal analysis. The proposed fire detection criterion was simulated by using fifteen test images and practicality was verified.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.10
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• pp.11-18
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• 2019

This study explores the relationship between the expression of material Sensibility properties and the meaning of tectonic in the architectural space of Kengo kuma. First of all, It can be derived that The sensibility of the material is based on phenomenological meaning of the tectonic after modern architecture that also Kengo kuma has been aware of. So it derived characteristics of sensibility by material expression and meaning from the Kengo kuma's works including critical books and collection of architecture works. All derived characteristics consist of sub-sections of the case analysis to figure out correlation with expression of Material Sensibility and tectonic meaning at the Kengo kuma's works. At the ends, it was analyzed through the relationship chart.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.57-63
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• 2009

The rapid growth of computer-based image database, necessity of a system that can manage an image information is increasing. This paper presents a region-based image retrieval method using the combination of color(autocorrelogram), texture(CWT moments) and shape(Hu invariant moments) features. As a color feature, a color autocorrelogram is chosen by extracting from the hue and saturation components of a color image(HSV). As a texture, shape and position feature are extracted from the value component. For efficient similarity confutation, the extracted features(color autocorrelogram, Hu invariant moments, and CWT moments) are combined and then precision and recall are measured. Experiment results for Corel and VisTex DBs show that the proposed image retrieval algorithm has 94.8% Precision, 90.7% recall and can successfully apply to image retrieval system.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.132-142
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• 2014

Stereo camera is drawing attention as an essential sensor for future intelligence robot system since it has the advantage of acquiring not only distance but also other additive information for an object. However, it cannot match correlated point on target image for low textured region or periodic patterned region such as wall of building or room. In this paper, we propose a stereo matching technique that increase the matching performance by fusing belief propagation stereo matching algorithm and local distance measurements of 2D-laser range finder in order to overcome this kind of limitation. The proposed technique adds laser measurements by referring quad-tree based segment information on to the local-evidence of belief propagation stereo matching algorithm, and calculates compatibility function by reflecting over-segmented information. Experimental results of the proposed method using simulation and real test images show that the distance information for some low textured region can be acquired and the discontinuity of depth information is preserved by using segmentation information.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.75-85
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• 2013

To acquire depth information using stereo vision, it is required to find correspondence points between stereo image pair. Conventional stereo vision systems usually use two cameras to get disparity data. Therefore, conventional stereo matching methods cannot resolve the tradeoff problem between accuracy and precision with respect to the length of baseline. Besides, belief propagation method, which is being used recently, has a problem that matching performance is dependent on the fixed weight parameter ${\lambda}$. In this paper, we propose a modified belief propagation stereo matching technique based on multi-baseline stereo vision to solve the tradeoff problem. The proposed method calculates EMAD(extended mean of absolute differences) as local evidence. And proposed method decides weight parameter ${\lambda}$ adaptively to local texture information. The proposed method shows higher initial matching performance than conventional methods and reached optimum solution in less iteration. The matching performance is increased about 4.85 dB in PSNR.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.5
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• pp.1-11
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• 2007

As the availability of an image information has been significantly increasing, necessity of system that can manage an image information is increasing. Accordingly, we proposed the region-based content retrieval(CBIR) algorithm based on an efficient combination of an image segmentation, an image texture, a color feature and an image's shape and position information. As a color feature, a HSI color histogram is chosen which is known to measure spatial of colors well. We used active contour and CWT(complex wavelet transform) to perform an image segmentation and extracting an image texture. And shape and position information are obtained using Hu invariant moments in the luminance of HSI model. For efficient similarity computation, the extracted features(color histogram, Hu invariant moments, and complex wavelet transform) are combined and then precision and recall are measured. As a experimental result using DB that was supported by www.freefoto.com. the proposed image retrieval engine have 94.8% precision, 82.7% recall and can apply successfully image retrieval system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4C
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• pp.226-231
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• 2011

To improve the conventional illustrated fish book, this paper introduces the concept of an electronic illustrated fish book which applies IT techniques to the conventional one, and proposes the image retrieval for it. The image retrieval is a core technology of the electronic illustrated fish book and make it overwhelm the conventional one. Since fishes, even if the same kind, have different features in shape, color, and texture and the same fish can even have different features by its pose or environment at that time for taking a picture, the conventional image retrieval, that uses simple features in shape, color, and texture, is not suitable for the electronic illustrated fish book. The proposed image retrieval adopts detail shape features extracted from head, body, and tail of a fish and different weights are given to the features depending on their invariability. The simulation results show that the proposed algorithm is far superior to the conventional algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.249-255
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• 2022

Potholes are an important clue to the structural defects of asphalt pavement and cause many casualties and property damage. Therefore, accurate pothole detection is an important task in road surface maintenance. Many machine learning technologies are being introduced for pothole detection, and data preprocessing is required to increase the efficiency of deep learning models. In this paper, we propose a preprocessing method that emphasizes important textures and shapes in pothole datasets. The proposed preprocessing method uses intensity transformation to reduce unnecessary elements of the road and emphasize the texture and shape of the pothole. In addition, the feature of the porthole is detected using Superpixel and Sobel edge detection. Through performance comparison between the proposed preprocessing method and the existing preprocessing method, it is shown that the proposed preprocessing method is a more effective method than the existing method in detecting potholes.