• 제목/요약/키워드: image of science

검색결과 9,961건 처리시간 0.038초

Medical Image Watermarking Based on Visual Secret Sharing and Cellular Automata Transform for Copyright Protection

  • Fan, Tzuo-Yau;Chao, Her-Chang;Chieu, Bin-Chang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권12호
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    • pp.6177-6200
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    • 2018
  • In order to achieve the goal of protecting medical images, some existing watermark techniques for medical image protection mainly focus on improving the invisibility and robustness properties of the method, in order to prevent unnecessary medical disputes. This paper proposes a novel copyright method for medical image protection based on visual secret sharing (VSS) and cellular automata transform (CAT). This method uses the protected medical image feature as well as VSS and a watermark to produce the ownership share image (OSI). The OSI is used for medical image verification and must be registered to a certified authority. In the watermark extraction process, the suspected medical image is used to generate a master share image (MSI). The watermark can be extracted by combining the MSI and the OSI. Different from other traditional methods, the proposed method does not need to modify the medical image in order to protect the copyright of the image. Moreover, the registered OSI used to verify the ownership and its appearance display meaningful information, facilitating image management. Finally, the results of the final experiment can prove the effectiveness of our method.

Segmentation of Millimeter-wave Radiometer Image via Classuncertainty and Region-homogeneity

  • Singh, Manoj Kumar;Tiwary, U.S.;Kim, Yong-Hoon
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.862-864
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    • 2003
  • Thresholding is a popular image segmentation method that converts a gray-level image into a binary image. The selection of optimum threshold has remained a challenge over decades. Many image segmentation techniques are developed using information about image in other space rather than the image space itself. Most of the technique based on histogram analysis information-theoretic approaches. In this paper, the criterion function for finding optimal threshold is developed using an intensity-based classuncertainty (a histogram-based property of an image) and region-homogeneity (an image morphology-based property). The theory of the optimum thresholding method is based on postulates that objects manifest themselves with fuzzy boundaries in any digital image acquired by an imaging device. The performance of the proposed method is illustrated on experimental data obtained by W-band millimeter-wave radiometer image under different noise level.

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체계적 분석 기법을 이용한 의미기반 이미지검색 분야 고찰에 관한 연구 (A Systematic Review on Concept-based Image Retrieval Research)

  • 정은경
    • 한국비블리아학회지
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    • 제25권4호
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    • pp.313-332
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    • 2014
  • 디지털 기술과 인터넷의 발달로 인해 이미지 생산, 유통, 이용이 활발하게 이루어지고 있으며, 이미지 검색에 관한 연구도 증가하는 추세이다. 이미지검색 분야는 내용기반과 의미기반으로 나뉘어 연구가 수행되어왔으며, 문헌정보학 관점에서는 특히 의미기반의 색인과 검색에 주목해왔다. 본 연구는 체계적인 분석기법을 이용하여 의미기반 이미지검색 분야 연구 집적의 분석결과를 제시하고자 한다. 이를 위하여 데이터는 Web of Science 수록된 문헌정보학(Information Science/Library Science)분야의 이미지검색 논문 및 학술회의 논문 총 282건을 대상으로 하였으며, 국내 연구와 비교를 위해서는 DBpia에 수록된 문헌정보학 분야의 이미지검색 논문 35건을 수집하였다. 데이터 분석 과정은 우선 개괄적인 현황을 파악하기 위해서 서지사항을 분석하였고, 이와 함께 내용분석을 통한 체계적 분석 고찰을 수행하였다. 연구 결과 이미지 검색은 기존 연구에서 밝힌 바와 같이 의미기반 이미지 검색이 주된 흐름이며, 그 중에서도 이미지 색인과 기술 분야, 이미지 요구와 검색행태 분야의 연구가 주를 이루는 것으로 나타났다. 최근 연구 경향으로 주목할 만한 분야는 집합적 색인, 다언어/다문화 환경에서의 색인과 이미지 요구, 감정색인과 접근 등이다. 이용자 중심의 이미지 검색 연구 측면에서는 특정 이용자 그룹 중에서 대학생이나 대학원생이 주된 연구 대상 이용자 그룹이며 이 외에도 이미지를 업무에 사용하는 이용자 그룹에 대한 연구가 주된 경향이다. 최근에는 일반 이용자를 대상으로 일상생활 환경에서 이미지검색에 관한 연구가 등장하기 시작했다. 국내 연구와 비교하면, 논문의 수적인 차이를 제외하면 세부 연구 주제에 있어서 상당히 유사한 분포를 보이는 것으로 나타났다. 이러한 연구결과는 지금까지의 이미지 검색 분야의 연구 집적을 조명하며, 향후 발전적 방향을 제시하는데 있어서 도움이 될 것으로 기대한다.

Automatic Generalization of Image Transformation Processes Using a Genetic Algorithm

  • Masunaga, Shinya;Nagao, Tomoharu
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1997년도 Proceedings International Workshop on New Video Media Technology
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    • pp.101-106
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    • 1997
  • A method is proposed to generalize the image transformation from an image to another one according to a pair of example images. When an original image and its target image are given, the unknown image transformation from the original image to the target one in automatically approximated by a sequence of several known image transformation filters by the method. The target image is assumed to be generated manually by using a drawing software. In this method, the order of image transformation filers is regarded as the chromosome of a virtual living thing and is evolved according to Genetic Algorithm. This method can be applied to automatic construction of expert systems for image processing.

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히스토그램 이동과 차분을 이용한 가역 비밀 이미지 공유 기법 (Reversible Secret Image Sharing Scheme Using Histogram Shifting and Difference Expansion)

  • 전병현;이길제;정기현;유기영
    • 한국멀티미디어학회논문지
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    • 제17권7호
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    • pp.849-857
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    • 2014
  • In this paper, we propose a (2,2)-reversible secret image sharing scheme using histogram shifting and difference expansion. Two techniques are widely used in information hiding. Advantages of them are the low distortion between cover and stego images, and high embedding capacity. In secret image sharing procedure, unlike Shamir's secret sharing, a histogram generate that the difference value between the original image and copy image is computed by difference expansion. And then, the secret image is embedded into original and copy images by using histogram shifting. Lastly, two generated shadow images are distributed to each participant by the dealer. In the experimental results, we measure a capacity of a secret image and a distortion ratio between original image and shadow image. The results show that the embedding capacity and image distortion ratio of the proposed scheme are superior to the previous schemes.

Review of Soil Structure Quantification from Soil Images

  • Chun, Hyen-Chung;Gimenez, Daniel;Yoon, Sung-Won;Park, Chan-Won;Moon, Yong-Hee;Sonn, Yeon-Kyu;Hyun, Byung-Keun
    • 한국토양비료학회지
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    • 제44권3호
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    • pp.517-526
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    • 2011
  • Soil structure plays an important role in ecological system, since it controls transport and storage of air, gas, nutrients and solutions. The study of soil structure requires an understanding of the interrelations and interactions between the diverse soil components at various levels of organization. Investigations of the spatial distribution of pore/particle arrangements and the geometry of soil pore space can provide important information regarding ecological or crop system. Because of conveniences in image analyses and accuracy, these investigations have been thrived for a long time. Image analyses from soil sections through impregnated blocks of undisturbed soil (2 dimensional image analyses) or from 3 dimensional scanned soils by computer tomography allow quantitative assessment of the pore space. Image analysis techniques can be used to classify pore types and quantify pore structure without inaccurate or hard labor in laboratory. In this paper, the last 50 years of the soil image analyses have been presented and measurements on various soil scales were introduced, as well. In addition to history of image analyses, a couple of examples for soil image analyses were displayed. The discussion was made on the applications of image analyses and techniques to quantify pore/soil structure.

확률적 방법을 통한 컬러 영상 분할 (Color Image Segmentation by statistical approach)

  • 강선도;유헌우;장동식
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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    • pp.1677-1683
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    • 2006
  • Color image segmentation is useful for fast retrieval in large image database. For that purpose, new image segmentation technique based on the probability of pixel distribution in the image is proposed. Color image is first divided into R, G, and B channel images. Then, pixel distribution from each of channel image is extracted to select to which it is similar among the well known probabilistic distribution function-Weibull, Exponential, Beta, Gamma, Normal, and Uniform. We use sum of least square error to measure of the quality how well an image is fitted to distribution. That P.d.f has minimum score in relation to sum of square error is chosen. Next, each image is quantized into 4 gray levels by applying thresholds to the c.d.f of the selected distribution of each channel. Finally, three quantized images are combined into one color image to obtain final segmentation result. To show the validity of the proposed method, experiments on some images are performed.

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Region Division for Large-scale Image Retrieval

  • Rao, Yunbo;Liu, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권10호
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    • pp.5197-5218
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    • 2019
  • Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

Unsupervised Segmentation of Images Based on Shuffled Frog-Leaping Algorithm

  • Tehami, Amel;Fizazi, Hadria
    • Journal of Information Processing Systems
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    • 제13권2호
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    • pp.370-384
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    • 2017
  • The image segmentation is the most important operation in an image processing system. It is located at the joint between the processing and analysis of the images. Unsupervised segmentation aims to automatically separate the image into natural clusters. However, because of its complexity several methods have been proposed, specifically methods of optimization. In our work we are interested to the technique SFLA (Shuffled Frog-Leaping Algorithm). It's a memetic meta-heuristic algorithm that is based on frog populations in nature searching for food. This paper proposes a new approach of unsupervised image segmentation based on SFLA method. It is implemented and applied to different types of images. To validate the performances of our approach, we performed experiments which were compared to the method of K-means.

Fast Iterative Solving Method of Fuzzy Relational Equation and its Application to Image Compression/Reconstruction

  • Nobuhara, Hajime;Takama, Yasufumi;Hirota, Kaoru
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제2권1호
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    • pp.38-42
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    • 2002
  • A fast iterative solving method of fuzzy relational equation is proposed. It is derived by eliminating a redundant comparison process in the conventional iterative solving method (Pedrycz, 1983). The proposed method is applied to image reconstruction, and confirmed that the computation time is decreased to 1 / 40 with the compression rate of 0.0625. Furthermore, in order to make any initial solution converge on a reconstructed image with a good quality, a new cost function is proposed. Under the condition that the compression rate is 0.0625, it is confirmed that the root mean square error of the proposed method decreases to 27.34% and 86.27% compared with those of the conventional iterative method and a non iterative image reconstruction method, respectively.