• Title/Summary/Keyword: hidden image

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Bayesian Parameter Estimation of 2D infinite Hidden Markov Model for Image Segmentation (영상분할을 위한 2차원 무한 은닉 마코프 모형의 비모수적 베이스 추정)

  • Kim, Sun-Worl;Cho, Wan-Hyun
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06a
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    • pp.477-479
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    • 2011
  • 본 논문에서는 1차원 은닉 마코프 모델을 2차원으로 확장하기 위하여 노드들의 마코프 특성이 인과적인 관계를 갖는 마코프 메쉬 모델을 이용하여 완전한 2차원 HMM의 구조를 갖는 모델을 제안한다. 마코프메쉬 모델은 이웃시스템을 통하여 이전의 시점을 정의하고, 인과적인 관계를 통하여 전이확률의 계산을 가능하게 한다. 또한 영상의 최적의 분할을 위하여 계층적 디리슐레 과정을 사전분포로 두어 고정된 상태의 수가 아닌 무한의 상태 수를 갖는 2차원 HMM을 제안한다. HDP로 정의된 사전분포와 관측된 표본 자료의 정보를 갖는 우도함수를 결합한 사후분포의 베이스 추정은 깁스샘플링 알고리즘을 이용하여 계산된다.

Digital Watermark Verification with Zero Knowledge Proofs (디지털 워터마크에 대한 영지식 검증)

  • 이형우;김태윤
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.05d
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    • pp.877-881
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    • 2002
  • Digital contents such as image need both secure proving and publicly verification scheme on embedded digital watermark for contents distribution and copyright protection. Specially, we must provide publicly verification mechanism on digital watermark without revealing any of the secret information hidden on digital contents. In this paper, we review on the existing zero knowledge proofs and digital watermarking system, and propose advanced interactive zero knowledge proofs mechanism for enhancing the performance and security of watermark verification process. And it Provides a new watermark verification scheme without revealing any secret on the contents owner's copyright in formation.

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High accuracy online 3D-reconstruction by multiple cameras

  • Oota, Yoshikazu;Pan, Yaodong;Furuta, Katuhisa
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1749-1752
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    • 2005
  • For online high accurate reconstruction of an object from an visual information, a linear reconstruction method for multiple images is popular. Basically this method needs many cameras or many different screen shots from different view points. This method, however, has the benefit of less calculation and is adequate for a real time application by comparing other popular method. In this paper, online reconstruction system using more than three cameras is treated. An evaluation method of cameras' position, and of the number is derived for the linear reconstruction method. To decrease errors that are caused from skew of lens, positional error between corresponding points is taken into consideration on the evaluation. The proposed evaluation method enables estimation of the adequate number of cameras and then of feasible view locations. Additionally, repeating search of epipolar lines enables estimation of the hidden point. Comparing with result of an average error analysis, it was confirmed that the proposed methods works effectively.

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Twostep Clustering of Environmental Indicator Survey Data

  • Park, Hee-Chang
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.10a
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    • pp.59-69
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    • 2005
  • Data mining technique is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. It has been widely used in many applications, such that pattern analysis or recognition, data analysis, image processing, market research on off-line or on-line and so on. We analyze Gyeongnam social indicator survey data by 2001 using twostep clustering technique for environment information. The twostep clustering is classified as a partitional clustering method. We can apply these twostep clustering outputs to environmental preservation and improvement.

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Frame Based Classification of Underwater Transient Signal Using MFCC Feature Vector and Neural Network (MFCC 특징벡터와 신경회로망을 이용한 프레임 기반의 수중 천이신호 식별)

  • Lim, Tae-Gyun;Kim, Il-Hwan;Kim, Tae-Hwan;Bae, Keun-Sung
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.883-884
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    • 2008
  • This paper presents a method for classification of underwater transient signals using, which employs a binary image pattern of the mel-frequency cepstral coefficients(MFCC) as a feature vector and a neural network as a classifier. A feature vector is obtained by taking DCT and 1-bit quantization for the square matrix of the MFCC sequences. The classifier is a feed-forward neural network having one hidden layer and one output layer, and a back propagation algorithm is used to update the weighting vector of each layer. Experimental results with some underwater transient signals demonstrate that the proposed method is very promising for classification of underwater transient signals.

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A Feature-Based Robust Watermarking Scheme Using Circular Invariant Regions

  • Doyoddorj, Munkhbaatar;Rhee, Kyung-Hyung
    • Journal of Korea Multimedia Society
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    • v.16 no.5
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    • pp.591-600
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    • 2013
  • This paper addresses a feature-based robust watermarking scheme for digital images using a local invariant features of SURF (Speeded-Up Robust Feature) descriptor. In general, the feature invariance is exploited to achieve robustness in watermarking schemes, but the leakage of information about hidden watermarks from publicly known locations and sizes of features are not considered carefully in security perspective. We propose embedding and detection methods where the watermark is bound with circular areas and inserted into extracted circular feature regions. These methods enhance the robustness since the circular watermark is inserted into the selected non-overlapping feature regions instead of entire image contents. The evaluation results for repeatability measures of SURF descriptor and robustness measures present the proposed scheme can tolerate various attacks, including signal processing and geometric distortions.

Steganography based Multi-modal Biometrics System

  • Go, Hyoun-Joo;Moon, Dae-Sung;Moon, Ki-Young;Chun, Myung-Geun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.1
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    • pp.71-76
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    • 2007
  • This paper deals with implementing a steganography based multi-modal biometric system. For this purpose, we construct a multi-biometrics system based on the face and iris recognition. Here, the feature vector of iris pattern is hidden in the face image. The recognition system is designed by the fuzzy-based Linear Discriminant Analysis(LDA), which is an expanded approach of the LDA method combined by the theory of fuzzy sets. Furthermore, we present a watermarking method that can embed iris information into face images. Finally, we show the advantages of the proposed watermarking scheme by computing the ROC curves and make some comparisons recognition rates of watermarked face images with those of original ones. From various experiments, we found that our proposed scheme could be used for establishing efficient and secure multi-modal biometric systems.

A Review of the Applications of Spectroscopy for the Detection of Microbial Contaminations and Defects in Agro Foods

  • Kandpal, Lalit Mohan;Cho, Byoung-Kwan
    • Journal of Biosystems Engineering
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    • v.39 no.3
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    • pp.215-226
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    • 2014
  • Recently, spectroscopy has emerged as a potential tool for quality evaluation of numerous food and agricultural products because it provides information regarding both spectral distribution and image features of the sample (i.e., hyperspectral imaging). Spectroscopic techniques reveal hidden information regarding the sample and do so in a non-destructive manner. This review describes the various approaches of spectroscopic modalities, especially hyperspectroscopy and vibrational spectroscopies (i.e., Raman spectroscopy and Fourier transform near infrared spectroscopy) combined with chemometrics for the non-destructive assessment of contaminations and defects in agro-food products.

Moving Data Pictures (움직이는 데이터 그림)

  • Huh, Myung-Hoe
    • The Korean Journal of Applied Statistics
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    • v.26 no.6
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    • pp.999-1007
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    • 2013
  • This research shows several types of moving pictures from the data: 1) the word cloud of Korean texts, 2) the heat map of n ${\times}$ p matrices, 3) the moving image of p ${\times}$ p scatterplot matrix, 4) the local projective display of k clusters (Huh and Lee, 2012). Moving pictures may reveal the hidden information and beauty of the datasets and ignite the curiosity of information consumers. Video files are attached.

Twostep Clustering of Environmental Indicator Survey Data

  • Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.1-11
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    • 2006
  • Data mining technique is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. It has been widely used in many applications, such that pattern analysis or recognition, data analysis, image processing, market research on off-line or on-line and so on. We analyze Gyeongnam social indicator survey data by 2001 using twostep clustering technique for environment information. The twostep clustering is classified as a partitional clustering method. We can apply these twostep clustering outputs to environmental preservation and improvement.

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