• Title/Summary/Keyword: 은닉 영상

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Video-based fall detection algorithm combining simple threshold method and Hidden Markov Model (단순 임계치와 은닉마르코프 모델을 혼합한 영상 기반 낙상 알고리즘)

  • Park, Culho;Yu, Yun Seop
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.9
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    • pp.2101-2108
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    • 2014
  • Automatic fall-detection algorithms using video-data are proposed. Six types of fall-feature parameters are defined applying the optical flows extracted from differential images to principal component analysis(PCA). One fall-detection algorithm is the simple threshold method that a fall is detected when a fall-feature parameter is over a threshold, another is to use the HMM, and the other is to combine the simple threshold and HMM. Comparing the performances of three types of fall-detection algorithm, the algorithm combining the simple threshold and HMM requires less computational resources than HMM and exhibits a higher accuracy than the simple threshold method.

Reversible data hiding technique applying triple encryption method (삼중 암호화 기법을 적용한 가역 데이터 은닉기법)

  • Jung, Soo-Mok
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.1
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    • pp.36-44
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    • 2022
  • Reversible data hiding techniques have been developed to hide confidential data in the image by shifting the histogram of the image. These techniques have a weakness in which the security of hidden confidential data is weak. In this paper, to solve this drawback, we propose a technique of triple encrypting confidential data using pixel value information and hiding it in the cover image. When confidential data is triple encrypted using the proposed technique and hidden in the cover image to generate a stego-image, since encryption based on pixel information is performed three times, the security of confidential data hidden by triple encryption is greatly improved. In the experiment to measure the performance of the proposed technique, even if the triple-encrypted confidential data was extracted from the stego-image, the original confidential data could not be extracted without the encryption keys. And since the image quality of the stego-image is 48.39dB or higher, it was not possible to recognize whether confidential data was hidden in the stego-image, and more than 30,487 bits of confidential data were hidden in the stego-image. The proposed technique can extract the original confidential data from the triple-encrypted confidential data hidden in the stego-image without loss, and can restore the original cover image from the stego-image without distortion. Therefore, the proposed technique can be effectively used in applications such as military, medical, digital library, where security is important and it is necessary to completely restore the original cover image.

An Image Concealment Algorithm Using Fuzzy Inference (퍼지 추론을 이용한 영상은닉 알고리즘)

  • Kim, Ha-Sik;Kim, Yoon-Ho
    • Journal of Advanced Navigation Technology
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    • v.11 no.4
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    • pp.485-492
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    • 2007
  • In this paper, we propose the receiver block error detection of the video codec and the image concealment algorithm using fuzzy inference. The proposed error detection and concealment algorithm gets SSD(Summation of Squared Difference) and BMC(Boundary Matching Coefficient) using the temporal and spatial similarity between corresponded blocks in the two successive frames. Proportional constant, ${\alpha}$, for threshold value, TH1 and TH2, is decided after fuzzy data is generated by each parameter. To examine the propriety of the proposed algorithm, random errors are inserted into the QCIF Susie standard image, then the error detection and concealment performance is simulated. To evaluate the efficiency of the algorithm, image quality is evaluated by PSNR for the error detection and concealed image by the existing VLC table and by the proposed method. In the experimental results, the error detection algorithm could detect all of the inserted error, the image quality is improved over 15dB after the error concealment compare to existing error detection algorithm.

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Classified Image Compression and Coding using Multi-Layer Percetpron (다층구조 퍼셉트론을 이용한 분류 영상압축 및 코딩)

  • 조광보;박철훈;이수영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.11
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    • pp.2264-2275
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    • 1994
  • In this paper, image compression based on neural networks is presented with block classification and coding. Multilayer neural networks with error back-propagation learning algorithm are used to transform the normalized image date into the compressed hidden values by reducing spatial redundancies. Image compression can basically be achieved with smaller number of hidden neurons than the numbers of input and output neurons. Additionally, the image blocks can be grouped for adaptive compression rates depending on the characteristics of the complexity of the blocks in accordance with the sensitivity of the human visual system(HVS). The quantized output of the hidden neuron can also be entropy coded for an efficient transmission. In computer simulation, this approach lie in the good performances even with images outside the training set and about 25:1 compression rate was achieved using the entropy coding without much degradation of the reconstructed images.

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Design of Generalized Fluctuation Function for Reversible Data Hiding in Encrypted Image (암호화된 영상의 가역적 데이터 은닉을 위한 일반화된 섭동 함수 설계)

  • Kim, Young-Hun;Lim, Dae-Woon;Kim, Young-Sik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.11
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    • pp.1329-1340
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    • 2016
  • Recently, Zhang proposed a scheme to hide information in encrypted images using synchronous stream ciphers. After the receiver decrypts the encrypted image and extracts data by calculating the spatial correlation property value using the fluctuation function which is designed to calculate spacial correlation between adjacent pixels in a decrypted image. Then, Hong improved the Zhang's data hiding scheme by introducing the side match technique. In this paper, a novel fluctuation function is proposed to reduce the recovery errors which arise during extracting hidden data. Then, we also demonstrated that the proposed fluctuation function outperforms the previous functions through computer simulations for sample images.

An Watermarking Method Based on Singular Vector Decomposition and Vector Quantization Using Fuzzy C-Mean Clustering (특이치 분해와 Fuzzy C-Mean(FCM) 군집화를 이용한 벡터양자화에 기반한 워터마킹 방법)

  • Lee, Byung-Hee;Jang, Woo-Seok;Kang, Hwan-Il
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.7
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    • pp.964-969
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    • 2007
  • In this paper, we propose the image watermarking method for good compression ratio and satisfactory image quality of the cover image and the embedding image. This method is based on the singular value decomposition and the vector quantization using fuzzy c-mean clustering. Experimental results show that the embedding image has invisibility and robustness to various serious attacks. The advantage of this watermarking method is that we can achieve both the compression and the watermarking method for the copyright protection simultaneously.

Real-time Video Watermarking using LSB coding (LSB 부호화를 이용한 실시간 비디오 워터마킹)

  • 이상준;김강욱;최동환;황찬식
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.719-722
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    • 2001
  • 최근 정지영상, 동영상, 음성 등의 멀티미디어 컨텐트가 디지털화 되고 네트워크가 발달함에 따라 영상을 포함한 멀티미디어 데이터의 접근이 용이해 졌다. 이러한 데이터의 불법적 사용과 인위적인 조작으로부터 소유권과 저작권을 효율적으로 보호하기 위한 워터마킹 기술이 많이 연구되고 있다. 일반적으로 정지 영상 및 음성에 대한 워터마킹 기술은 많이 연구가 되었지만 이러한 방법을 동영상에 그대로 적용하기에는 실시간 처리에 적용하기가 힘들다는 큰 문제점이 있다. 따라서 본 논문에서는 비디오 신호에서의 빠른 처리과정과 실시간으로 워터마크를 삽입하고, 원 영상 없이 워터마크를 추출 할 수 있는 새로운 방법(Blind Watermarking)을 제안하고자 한다. 제안한 방법은 대역확산을 근거로 하여 워터마크 은닉 과정에서 치환(Permutation) 과정과 LSB 부호화 방법을 이용하여 비디오 시퀀스의 모든 I-프레임에 은닉한다. 복원과정은 모든 I-프레임에서 LSB 복호화와 역 치환 과정을 거쳐 본래의 저작권 정보를 추출한다. 제안한 방법을 여러 가지 동영상 비디오에 적용해 본 결과 기존의 워터마킹 방법보다 효율적이고 시각적 손상이 없었으며 빠른 실시간 처리가 가능함을 볼 수 있었다.

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A Study on Steganographic Method for Binary Images (이진영상을 위한 심층암호 기법에 관한 연구)

  • Ha Soon-Hye;Kang Hyun-Ho;Lee Hye-Joo;Shin Sang-Uk;Park Young-Ran
    • Journal of Korea Multimedia Society
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    • v.9 no.2
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    • pp.215-225
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    • 2006
  • Binary images, such as cartoon character images, text images and signature images, which consist of two values with black and white have more difficulties inserting imperceptible secret data than color images. Steganography using binary cover images is not easy to satisfy requirements for both the imperceptibility of stego images and a high embedding rate of secret data at the same time. In this paper, we propose a scheme that can get both the high quality of stego images and a high embedding rate by supplementing the advantages of previous research. In addition, the insertion of the proposed method changes only existing pixels of the imperceptible position and can embed the secret data of [$log_2(mn+1)-2$] bits in a block with size of $m{\times}n$.

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Lossless Data Hiding Using Modification of Histogram in Wavelet Domain (웨이블릿 영역에서 히스토그램 수정을 이용한 무손실 정보은닉)

  • Jeong Cheol-Ho;Eom Il-Kyu;Kim Yoo-Shin
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.4 s.310
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    • pp.27-36
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    • 2006
  • Lossless data embedding is a method to insert information into a host image that guarantees complete restoration when the extraction has been done. In this paper, we propose a noble reversible data embedding algorithm for images in wavelet domain. The proposed embedding technique, which modifies histogram of wavelet coefficient, is composed of two inserting steps. Data is embedded to wavelet coefficient using modification of histogram in first embedding process. Second embedding step compensates the distortion caused by the first embedding process as well as hides more information. Hence we achieve higher inserting capacity. In view of the relationship between the embedding capacity and the PSNR value, our proposed method shows considerably higher performance than the current reversible data embedding methods.

Shot Boundary Detection of Video Sequence Using Hierarchical Hidden Markov Models (계층적 은닉 마코프 모델을 이용한 비디오 시퀀스의 셧 경계 검출)

  • Park, Jong-Hyun;Cho, Wan-Hyun;Park, Soon-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.8A
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    • pp.786-795
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    • 2002
  • In this paper, we present a histogram and moment-based vidoe scencd change detection technique using hierarchical Hidden Markov Models(HMMs). The proposed method extracts histograms from a low-frequency subband and moments of edge components from high-frequency subbands of wavelet transformed images. Then each HMM is trained by using histogram difference and directional moment difference, respectively, extracted from manually labeled video. The video segmentation process consists of two steps. A histogram-based HMM is first used to segment the input video sequence into three categories: shot, cut, gradual scene changes. In the second stage, a moment-based HMM is used to further segment the gradual changes into a fade and a dissolve. The experimental results show that the proposed technique is more effective in partitioning video frames than the previous threshold-based methods.