• Title/Summary/Keyword: 은닉영상

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Recognition of characters on car number plate and best recognition ratio among their layers using Multi-layer Perceptron (다중퍼셉트론을 이용한 자동차 번호판의 최적 입출력 노드의 비율 결정에 관한 연구)

  • Lee, Eui-Chul;Lee, Wang-Heon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.1
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    • pp.73-80
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    • 2016
  • The Car License Plate Recognition(: CLPR) is required in searching the hit-and-run car, measuring the traffic density, investigating the traffic accidents as well as in pursuing vehicle crimes according to the increasing in number of vehicles. The captured images on the real environment of the CLPR is contaminated not only by snow and rain, illumination changes, but also by the geometrical distortion due to the pose changes between camera and car at the moment of image capturing. We propose homographic transformation and intensity histogram of vertical image projection so as to transform the distorted input to the original image and cluster the character and number, respectively. Especially, in this paper, the Multilayer Perceptron Algorithm(: MLP) in the CLPR is used to not only recognize the charcters and car license plate, but also determine the optimized ratio among the number of input, hidden and output layers by the real experimental result.

An Adaptive Steganography of Color Image Using Bit-Planes and Multichannel Characteristics (비트플레인 및 다중채널 특성을 이용한 칼라 영상의 적응 스테가노그라피)

  • Jung Sung-Hwan;Lee Sin-Joo
    • Journal of Korea Multimedia Society
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    • v.8 no.7
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    • pp.961-973
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    • 2005
  • In this paper, we proposed an adaptive steganography of color image using bit-planes and multichannel characteristics. Applying fixing threshold, if we insert information into all bit-planes of RGB channel, each channels showed different image quality. Therefore, we first defined the channel weight and the bit-plane weight to solve the fixing threshold problem of BPCS (bit-plane complexity steganography) method. We then proposed a new adaptive threshold method using the bit-plane weight of channels and the bit-plane complexity of cover image to increase insertion capacity adaptively In the experiment, we inserted information into the color images with the same image quality and same insertion capacity, and we analyzed the Insertion capacity and image quality. As a result, the proposed method increased the insertion capacity and improved the image quality than BPCS method.

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Proxy Server Providing Multi-level Privileges for Network Cameras on the Video Surveillance System (CCTV 대체용 네트워크 카메라의 보안 강화를 위한 다중 접근권한 프락시 서버 구현)

  • Bae, Kwang-Jin;Lee, Kyung-Roul;Yim, Kang-Bin
    • Journal of Internet Computing and Services
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    • v.12 no.2
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    • pp.123-133
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    • 2011
  • This paper introduces security problems on the video surveillance systems where the network cameras are equipped at remote places and isolated from the updated and secure environment and proposes a framework for a proxy server that is delegated to connect to network cameras by providing a secure connections from the clients. The server in the framework is deployed within a secure network, secretes the information for connection to cameras and authenticates the clients. Additionally, it provides a secure video service incorporating multi-level privileges for both images and clients through a encryption key distribution and management facility. Through an implementation of the server and a its deployment, it was proved that In this server implement to multi network camera and we confirm compare direct access to network camera equal video quality of service and it can be protection network camera. We expect that can be secure and integral management about traditional network camera through experimental result.

Location Information Hiding Way Of HD Black Box Recording process (HD 블랙박스 녹화과정에서의 위치정보 은익방법)

  • Seok, Jin-Hwan;Yoon, Jong-Chul;Hong, Jong-Sung;Han, Chan-Ho
    • Journal of the Institute of Convergence Signal Processing
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    • v.17 no.1
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    • pp.10-17
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    • 2016
  • GPS location information storage included in the HD black box is using a unique manner for each manufacturer does not have a specific standard. In this paper, in order to overcome the limitations of the storage space and thereby the image quality according to store GPS position information deteriorate to solve the problems that cause, we propose the location information concealment method included in the HDTV video content using a essential hidden region. HDTV video content is a Border Extender of 8 lines in the frame to the bottom of the compression will be required. This was inserted into the image of a gray scale used in block form in order to space the current position information is concealed to prevent image degradation. The proposed method was confirmed using real HD black box, there are more difficult to interpret the format of the ASCII code re-edit the location information when the compression effect disappears with the existing security zones added. Therefore, the proposed method is suitable for location-based services, such as Facebook or Youtube videos.

자가 생성 지도 학습 알고리즘을 이용한 컨테이너 식별자 인식

  • Kim, Jae-Yong;Park, Chung-Sik;Kim, Gwang-Baek
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2005.11a
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    • pp.500-506
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    • 2005
  • 본 논문에서는 자가 생성 지도 학습 알고리즘을 이용한 운송 컨테이너 식별자 인식 시스템을 제안한다. 일반적으로 운송 컨테이너의 식별자들은 글자의 색이 검정색 또는 흰색으로 이루어져 있는 특정이 있다. 이러한 특성을 고려하여 원 컨테이너 영상에 대해 검은색과 흰색을 제외하고는 모든 부분을 잡음으로 처리하기 위해 퍼지 추론 방법을 이용하여 식별자 영역과 바탕영역을 구별한다. 식별자 영역으로 구분 된 영역은 그대로 두고, 바탕 영역으로 구분된 영역 은 전체 영상의 평균 픽셀 값으로 대체시킨다. 그리고 Sobel 마스크를 이용하여 에지를 검출하고, 추출된 에지를 이용하여 수직 블록과 수평 블록을 검출 하여 컨테이너의 식별자 영역을 추출하고 이진화한다. 이진화 된 식별자 영역에 대해 검정색의 빈도수를 이용하여 흰바탕과 민바탕을 구분하고 4 방향 윤곽선 추적 알고리즘을 적용하여 개별 식별자를 추출 한다. 개별 식별자 인식을 위해 자가 생성 지도 학습 알고리즘을 제안하여 개별 식별자 인식에 적용한다. 제안된 자가 생성 지도 학습 알고리즘은 입력층과 은닉층 사이의 구조를 ART-l을 개선하여 적용하고 은닉층과 출력층 사이에는 일반화된 델타 학습 방법과 Delta-bar-Delta 알고리즘을 적용하여 학습 및 인식 성능을 개선한다. 실제 80 개의 컨테이너 영상을 대상으로 실험한 결과, 제안된 식별자 추출 방법이 이전의 개별 추출 방법보다 추출률이 개선되었고 FCM 기반 자가 생성 지도 학습 알고리즘보다 제안된 자가 생성 지도 학습 알고리즘이 컨테이너 식별자의 학습 및 인식에 있어서 개선된 것을 확인하였다.색 문제를 해결하고자 하는 것이 연구의 목적이다. 정보추출은 사용자의 관심사에 적합한 문서들로부터 어떤 구체적인 사실이나 관계를 정확히 추출하는 작업을 가리킨다.앞으로 e-메일, 매신저, 전자결재, 지식관리시스템, 인터넷 방송 시스템의 기반 구조 역할을 할 수 있다. 현재 오픈웨어에 적용하기 위한 P2P 기반의 지능형 BPM(Business Process Management)에 관한 연구와 X인터넷 기술을 이용한 RIA (Rich Internet Application) 기반 웹인터페이스 연구를 진행하고 있다.태도와 유아의 창의성간에는 상관이 없는 것으로 나타났고, 일반 유아의 아버지 양육태도와 유아의 창의성간의 상관에서는 아버지 양육태도의 성취-비성취 요인에서와 창의성제목의 추상성요인에서 상관이 있는 것으로 나타났다. 따라서 창의성이 높은 아동의 아버지의 양육태도는 일반 유아의 아버지와 보다 더 애정적이며 자율성이 높지만 창의성이 높은 아동의 집단내에서 창의성에 특별한 영향을 더 미치는 아버지의 양육방식은 발견되지 않았다. 반면 일반 유아의 경우 아버지의 성취지향성이 낮을 때 자녀의 창의성을 향상시킬 수 있는 것으로 나타났다. 이상에서 자녀의 창의성을 향상시키는 중요한 양육차원은 애정성이나 비성취지향성으로 나타나고 있어 정서적인 측면의 지원인 것으로 밝혀졌다.징에서 나타나는 AD-SR맥락의 반성적 탐구가 자주 나타났다. 반성적 탐구 척도 두 그룹을 비교 했을 때 CON 상호작용의 특징이 낮게 나타나는 N그룹이 양적으로 그리고 내용적으로 더 의미 있는 반성적 탐구를 했다용을 지원하는 홈페이지를 만들어 자료

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Depth-Based Recognition System for Continuous Human Action Using Motion History Image and Histogram of Oriented Gradient with Spotter Model (모션 히스토리 영상 및 기울기 방향성 히스토그램과 적출 모델을 사용한 깊이 정보 기반의 연속적인 사람 행동 인식 시스템)

  • Eum, Hyukmin;Lee, Heejin;Yoon, Changyong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.6
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    • pp.471-476
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    • 2016
  • In this paper, recognition system for continuous human action is explained by using motion history image and histogram of oriented gradient with spotter model based on depth information, and the spotter model which performs action spotting is proposed to improve recognition performance in the recognition system. The steps of this system are composed of pre-processing, human action and spotter modeling and continuous human action recognition. In pre-processing process, Depth-MHI-HOG is used to extract space-time template-based features after image segmentation, and human action and spotter modeling generates sequence by using the extracted feature. Human action models which are appropriate for each of defined action and a proposed spotter model are created by using these generated sequences and the hidden markov model. Continuous human action recognition performs action spotting to segment meaningful action and meaningless action by the spotter model in continuous action sequence, and continuously recognizes human action comparing probability values of model for meaningful action sequence. Experimental results demonstrate that the proposed model efficiently improves recognition performance in continuous action recognition system.

Image Dehazing using Transmission Map Based on Hidden Markov Random Field Model (은닉 마코프 랜덤 모델 기반의 전달 맵을 이용한 안개 제거)

  • Lee, Min-Hyuk;Kwon, Oh-Seol
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.1
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    • pp.145-151
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    • 2014
  • This paper proposes an image haze removal algorithm for a single image. The conventional Dark Channel Prior(DCP) algorithm estimates a transmission map using the dark information in an image, and the haze regions are then detected using a matting algorithm. However, since the DCP algorithm uses block-based processing, block artifacts are invariably formed in the transmission map. To solve this problem, the proposed algorithm generates a modified transmission map using a Hidden Markov Random Field(HMRF) and Expectation-Maximization(EM) algorithm. Experimental results confirm that the proposed algorithm is superior to conventional algorithms in image haze removal.

A Two-Stage Document Page Segmentation Method using Morphological Distance Map and RBF Network (거리 사상 함수 및 RBF 네트워크의 2단계 알고리즘을 적용한 서류 레이아웃 분할 방법)

  • Shin, Hyun-Kyung
    • Journal of KIISE:Software and Applications
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    • v.35 no.9
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    • pp.547-553
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    • 2008
  • We propose a two-stage document layout segmentation method. At the first stage, as top-down segmentation, morphological distance map algorithm extracts a collection of rectangular regions from a given input image. This preliminary result from the first stage is employed as input parameters for the process of next stage. At the second stage, a machine-learning algorithm is adopted RBF network, one of neural networks based on statistical model, is selected. In order for constructing the hidden layer of RBF network, a data clustering technique bared on the self-organizing property of Kohonen network is utilized. We present a result showing that the supervised neural network, trained by 300 number of sample data, improves the preliminary results of the first stage.

A study of hybrid neural network to improve performance of face recognition (얼굴 인식의 성능 향상을 위한 혼합형 신경회로망 연구)

  • Chung, Sung-Boo;Kim, Joo-Woong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.12
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    • pp.2622-2627
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    • 2010
  • The accuracy of face recognition used unmanned security system is very important and necessary. However, face recognition is a lot of restriction due to the change of distortion of face image, illumination, face size, face expression, round image. We propose a hybrid neural network for improve the performance of the face recognition. The proposed method is consisted of SOM and LVQ. In order to verify usefulness of the proposed method, we make a comparison between eigenface method, hidden Markov model method, multi-layer neural network.

A Partial Encryption Methods for Digital Holograms (디지털 홀로그램을 위한 부분 암호화 기법)

  • Choi, Hyun-Jun;Seo, Young-Ho;Kim, Dong-Wook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.1C
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    • pp.51-58
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    • 2007
  • The purpose of this paper is to find an efficient encryption scheme for digital holograms (fringe patterns) with low encryption cost. Therefore, we introduced several encryption attempts in both hologram-domain and frequency-domain (both DCT-domain and DWT-domain) on the bases of the results from analyzing the properties of the coefficients in each domain. To effectively hide the image information, 25%, 1.5625%, and 0.0244% of the original fringe pattern need to be encrypted for hologram-domain scheme, DWT-domain scheme, and DCT-domain scheme, respectively. Consequently the DCT-domain scheme was the most efficient and it is caused by the fact that the ability for DCT to concentrate the energy of a given 2-dimensional image into a small area is the best. The encryption schemes and the analyses in this paper are expected to be used effectively on the researches on encryption and others for digital holograms.