• 제목/요약/키워드: Military Image

검색결과 376건 처리시간 0.022초

컬러 영상의 RGB 화소 최대차분 기반 보간법을 이용한 정보은닉 기법 (Information Hiding Method based on Interpolation using Max Difference of RGB Pixel for Color Images)

  • 이준호;김평한;정기현;유기영
    • 한국멀티미디어학회논문지
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    • 제20권4호
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    • pp.629-639
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    • 2017
  • Interpolation based information hiding methods are widely used to get information security. Conventional interpolation methods use the neighboring pixel value and simple calculation like average to embed secret bit stream into the image. But these information hiding methods are not appropriate to color images like military images because the characteristics of military images are not considered and these methods are restricted in grayscale images. In this paper, the new information hiding method based on interpolation using RGB pixel values of color image is proposed and the effectiveness is analyzed through experiments.

국부영역의 동적범위 변화를 이용한 영상 개선 알고리즘 (Regional Dynamic Range Histogram Equalization for Image Enhancement)

  • 이의혁
    • 한국군사과학기술학회지
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    • 제7권3호
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    • pp.101-109
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    • 2004
  • Image enhancement for Infrared imaging system is mainly based on the global histogram equalization. The global histogram equalization(GHE) is a method in which each pixel is equalized by using a whole histogram of an image. GHE is speedy and effective for real-time imaging system but its method fails to enhance the fine details. On the other hand, the basic local histogram equalization(LHE) method uses sliding a window and. the pixels under the window region are equalized over the whole output dynamic range. The LHE is adequate to enhance the fine details. But this method is computationally slow and noises are over-enhanced. So various local histogram equalization methods have been already presented to overcome these problems of LHE. In this paper, a new regional dynamic range histogram equalization (RDRHE) is presented. RDRHE improves the equalization quality while reducing the computational burden.

CUDA를 이용한 초해상도 기법의 영상처리 속도개선 방법 (An Image Processing Speed Enhancement in a Multi-Frame Super Resolution Algorithm by a CUDA Method)

  • 김미정
    • 한국군사과학기술학회지
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    • 제14권4호
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    • pp.663-668
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    • 2011
  • Although multi-frame super resolution algorithm has many merits but it demands too much calculation time. Researches have shown that image processing time can be reduced using a CUDA(Compute unified device architecture) which is one of GPGPU(General purpose computing on graphics processing unit) models. In this paper, we show that the processing time of multi-frame super resolution algorithm can be reduced by employing the CUDA. It was applied not to the whole parts but to the largest time consuming parts of the program. The simulation result shows that using a CUDA can reduce an operation time dramatically. Therefore it can be possible that multi-frame super resolution algorithm is implemented in real time by using libraries of image processing algorithms which are made by a CUDA.

가변 길이 자료 은닉이 가능한 이미지 스테가노그래픽 방법 연구 (Image Steganographic Method using Variable Length for Data Embedding)

  • 정기현
    • 한국군사과학기술학회지
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    • 제11권3호
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    • pp.115-122
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    • 2008
  • Wu and Tsai's pixel-value differencing method and Chang and Tseng's side-match method are based on the theory that the number of bits which can be embedded is determined by the degree of the pixel's smoothness, or its proximity to the edge of the image. If pixels are located in the edge area, they may tolerate larger changes than those in smooth areas. However, both methods are subject to the fall off the boundary problem(FOBP). This study proposes a new scheme that can solve the FOBP. The experimental results demonstrate that the proposed method resolves the problem, and achieves a higher image quality index value than other methods.

다중센서-다중프레임 기반 표적분할기법 (A Target Segmentation Method Based on Multi-Sensor/Multi-Frame)

  • 이승연
    • 한국군사과학기술학회지
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    • 제13권3호
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    • pp.445-452
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    • 2010
  • Adequate segmentation of target objects from the background plays an important role for the performance of automatic target recognition(ATR) system. This paper presents a new segmentation algorithm using fuzzy thresholding to extract a target. The proposed algorithm consists of two steps. In the first step, the region of interest(ROI) including the target can be automatically selected by the proposed robust method based on the frame difference of each image sensor. In the second step, fuzzy thresholding with a proposed membership function is performed within the only ROI selected in the first step. The proposed membership function is based on the similarity of intensity and the adjacency of target area on each image. Experimental results applied to real CCD/IR images show a good performance and the proposed algorithm is expected to enhance the performance of ATR system using multi-sensors.

DCT 특징을 이용한 지표면 분류 기법 (A Method for Terrain Cover Classification Using DCT Features)

  • 이승연;곽동민;성기열
    • 한국군사과학기술학회지
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    • 제13권4호
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    • pp.683-688
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    • 2010
  • The ability to navigate autonomously in off-road terrain is the most critical technology needed for Unmanned Ground Vehicles(UGV). In this paper, we present a method for vision-based terrain cover classification using DCT features. To classify the terrain, we acquire image from a CCD sensor, then the image is divided into fixed size of blocks. And each block transformed into DCT image then extracts features which reflect frequency band characteristics. Neural network classifier is used to classify the features. The proposed method is validated and verified through many experiments and we compare it with wavelet feature based method. The results show that the proposed method is more efficiently classify the terrain-cover than wavelet feature based one.

실측자료 기반 함정 RCS 측정 및 산란점 분석 연구 (A Study on RCS and Scattering Point Analysis Based on Measured Data for Maritime Ship)

  • 정회인;박상홍;최재호;김경태
    • 한국군사과학기술학회지
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    • 제23권2호
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    • pp.97-105
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    • 2020
  • In order to set up radar cross section(RCS) reduction factors for a target, the scattering point position of the target should be identified through inverse synthetic aperture radar(ISAR) image analysis. For this purpose, ISAR image focusing is important. Maritime ship is non-linear maneuvering in the sea, however, which blur the ISAR image. To solve this problem, translational and rotational motion compensation are essential to form focused ISAR image. In this paper, hourglass and ISAR image analysis are performed on the collected data in the sea instead of using the prediction software tool, which takes much time and cost to make computer-aided design(CAD) model of the ship.

영상처리기법을 이용한 소화기 조준감사 자동화에 관한 연구 (A Study on the Bore-Sighting Automation for Small Arms Using the Image Processing)

  • 여운주
    • 한국군사과학기술학회지
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    • 제9권3호
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    • pp.5-11
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    • 2006
  • This paper is launched to get an exact bore-sighting value in the process of assembling for a dual-barrel weapon. Image processing method with a CCD(Charged Coupled Device) camera is chosen for the error reduction of bore-sighting. The results of this method by using a CCD camera and the testing target method are described in this paper. After the performance of the dual-barrel weapon and that of the fire-control system in the dual barrel weapon system is confirmed, the bore-sighting which is a part of the process in the system assembly is accomplished. In this process, the position of the barrel is identified by using the testing target method that is an existing bore-sighting method. Then, the fixing line of the fire-control system is checked by a day-optical part. The precision of the bore-sighting is required within several mils, however the manual method using the naked eyes makes it worse. Therefore, a CCD camera is installed in the eyepieces. Next, we can get an image of the sighting and the center coordinate values of the laser-pointer from each barrel by image processing method. A required bore-sighting value is calculated from the eccentricity of the center coordinate. Finally, It can be applied to adopt this result in the assembling process of the dual-barrel weapon.

동아시아 표준 대기가 합성 적외선 영상에 미치는 효과 (Effect of the East Asian Reference Atmosphere on a Synthetic Infrared Image)

  • 신종진
    • 한국군사과학기술학회지
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    • 제9권4호
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    • pp.97-103
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    • 2006
  • A synthetic infrared image can be effectively utilized in various fields such as the recognition and tracking of targets as long as its quality is good enough to reflect the real situations. One way to improve its quality is to use the reference atmosphere which best describes atmospheric properties of regional areas. The east asian reference atmosphere has been developed to represent atmospheric properties of the east asia including Korean peninsula. However, few research has been conducted to examine the effects of this east asian reference atmosphere on the modeling and simulation. In this regard, this paper analyzes the effects of the east asian reference atmosphere on a synthetic infrared image. The research compares the atmospheric transmittance, the surface temperature, and the radiance obtained by using the east asian reference atmosphere with those of the midlatitude reference atmosphere which has been widely applied in the east asia. The results show that the differences of the atmospheric transmittance, the surface temperature, and the radiance between the east asian reference atmosphere and the midlatitude reference atmosphere are significant especially during the daytime. Therefore, it is recommended to apply the east asian reference atmosphere for generating a synthetic infrared image with targets in the east asia.

군 폐쇄망 환경에서의 모의 네트워크 데이터 셋 평가 방법 연구 (A study on evaluation method of NIDS datasets in closed military network)

  • 박용빈;신성욱;이인섭
    • 인터넷정보학회논문지
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    • 제21권2호
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    • pp.121-130
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    • 2020
  • 이 논문은 Generative Adversarial Network (GAN) 을 이용하여 증진된 이미지 데이터를 평가방식인 Inception Score (IS) 와 Frechet Inception Distance (FID) 계산시 inceptionV3 모델을 활용 하는 방식을 응용하여, 군 폐쇄망 네트워크 데이터를 이미지 형태로 평가하는 방법을 제안한다. 기존 존재하는 이미지 분류 모델들에 레이어를 추가하여 IncetptionV3 모델을 대체하고, 네트워크 데이터를 이미지로 변환 및 학습 하는 방법에 변화를 주어 다양한 시뮬레이션을 진행하였다. 실험 결과, atan을 이용해 8 * 8 이미지로 변환한 데이터에 대해 1개의 덴스 레이어 (Dense Layer)를 추가한 Densenet121를 학습시킨 모델이 네트워크 데이터셋 평가 모델로서 가장 적합하다는 결과를 도출하였다.