• 한국의류학회지
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• 제32권8호
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• pp.1309-1321
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• 2008

Military style is not limited to a single period but represents various image communications related to items, synthetic images and different periodical culture backgrounds. The purpose of this study is to define the communicational function of the military style beginning from the 1st world war up to the modern days, and furthermore explain the characteristics and contents of military styles in different periods by studying the nowadays various symbols of the military style in denotative and connotative aspects. The research method is documentary studies through the literature and academic paper, and examined masters' and doctors' thesis, domestic and overseas books and fashion magazines, photographs and materials collected from the internet. As a result, first, the military style is a significant fashion code in understanding modern fashion by serving as a strong communication function representing people’s ritual through various image items called the 'military look'. Second, the meaning of the image communication through military look changed throughout the different periods. During the 1st and 2nd World war the military look supported Fascism by serving as a media representing extreme patriotism and at the same time social images like functionalism, women liberation, regulation and saving. During the cold war period it was used by young progressives like hippies and punks to send an opposing message towards war and commercialism. Since then up to the 80s it was a medium representing the ‘new role of women’, who possess same social rights and power as the men. However in the 90s the military style had to go through a paradigm transition period. Since this period it got affected by the post modernism and designers, consumers alike adopted military style to create unique beauty It can also be said that it began to be used as a pure fashion code representing intertextuality. It was rather expressed as a metonymy than a metaphor and combined with elegance and feminine factor, which contrasts to the original military concept, it now represents totally new hybrids such as difference, dissemination and varieties.

• 한국멀티미디어학회논문지
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• 제21권8호
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• pp.858-863
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• 2018

In this paper, we propose and implement a multi-level convolutional neural network (CNN) algorithm to identify the sexually explicit and lewdness of various image files, and verify its effectiveness by using unauthorized image files generated in the actual military. The proposed algorithm increases the accuracy by applying the convolutional artificial neural network step by step to minimize classification error between similar categories. Experimental data have categorized 20,005 images in the real field into 6 authorization categories and 11 non-authorization categories. Experimental results show that the overall detection rate is 99.51% for the image files. In particular, the excellence of the proposed algorithm is verified through reducing the identification error rate between similar categories by 64.87% compared with the general CNN algorithm.

• 한국군사과학기술학회지
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• 제26권5호
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• pp.392-399
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• 2023

This research paper investigates the effectiveness of using computer graphics(CG) based synthetic data for deep learning in military vehicle detection. In particular, we explore the use of synthetic image generation techniques to train deep neural networks for object detection tasks. Our approach involves the generation of a large dataset of synthetic images of military vehicles, which is then used to train a deep learning model. The resulting model is then evaluated on real-world images to measure its effectiveness. Our experimental results show that synthetic training data alone can achieve effective results in object detection. Our findings demonstrate the potential of CG-based synthetic data for deep learning and suggest its value as a tool for training models in a variety of applications, including military vehicle detection.

• 한국군사과학기술학회지
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• 제10권1호
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• pp.101-106
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• 2007

In this paper, we propose chain code based decision technique of edge orientation. Edge Information is one of the most important information for handling image signals, and is applied to various civilian and military area, such as image surveillance for military reconnaissance, restoration of noised image signal, fingerprint recognition, and so on. The conventional methods to find edge orientations exploit a certain size of mask which weights for a certain direction, so they showed limitations in the case of diagonal edges except 45 degrees. We find edge orientations using chain code. According to the experiments, the proposed method shows better performance than the conventional approaches. The exact edge orientations including diagonal directions are well found.

• 한국군사과학기술학회지
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• 제25권3호
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• pp.300-310
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• 2022

A vast amount of labeled data is required for deep neural network training. A typical strategy to improve the performance of a neural network given a training data set is to use data augmentation technique. The goal of this work is to offer a novel image augmentation method for improving object detection accuracy. An object in an image is removed, and a similar object from the training data set is placed in its area. An in-painting algorithm fills the space that is eliminated but not filled by a similar object. Our technique shows at most 2.32 percent improvements on mAP in our testing on a military vehicle dataset using the YOLOv4 object detector.

• 한국군사과학기술학회지
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• 제14권3호
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• pp.482-491
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• 2011

The purpose of this study is to design and implement a 2-level secret information transmission system which can be used for information hiding of images transmitted over various IT communication media. To increase the robustness of the hiding power, we combined the steganography method which inserts secret object into cover object to hide the very fact of information hiding itself, and the preprocessing stage to encrypt the secret object before the stego-insertion stage. As a result, even when the stego-image is broken by an attacker, the secret image is protected by encryption. We implemented the 2-level image insertion and extraction algorithm by using C++ programming language. Experiment shows that the PSNR values of stego-images of ours exceed 30.00db which is the threshold of human recognition. The methodology of this study can be applied broadly to the information hiding and protection of the military secret images.

• 한국심리학회지 : 문화 및 사회문제
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• 제16권4호
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• pp.469-485
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• 2010

본 연구는 현역 병사들의 입대 동기가 군 생활 전반에 미치는 영향을 알아보기 위해 육군 병사와 해병대원을 대상으로 수행되었다. 입대 동기란 군 복무를 하고자 하는 동기를 말하며, 본 연구에서는 외재적 입대 동기와 내재적 입대 동기로 나누어 측정하였다. 입대 동기에 따라 군 생활 만족도와 군 조직 이미지에 대한 평가, 그리고 군 복무 경험이 앞으로의 삶에 미칠 영향에 대한 평가가 어떻게 달라지는지 알아보았다. 그 결과 육군 병사들의 입대 동기는 외재적 동기가 더 높았으며, 해병대원들의 입대 동기는 내재적 동기가 더 높은 것으로 나타났다. 또한 내재적 입대 동기수준이 높을수록 군 생활 만족도가 높고, 군 조직에 대한 이미지도 긍정적으로 형성된 것으로 나타났으며, 미래의 삶에 군 생활 경험이 긍정적인 영향을 미칠 것으로 평가한 것으로 나타났다. 반대로 외재적 입대 동기수준이 높을수록 군 조직에 대해 부정적으로 평가하고, 병영생활 스트레스 수준이 높은 것으로 나타났으며, 앞으로의 삶에 군 생활 경험이 부정적인 영향을 미칠 것으로 평가하였다. 마지막으로, 징병제 여부에 관계없이 입대를 결정한 집단과 징병제가 아니면 군대를 오지 않을 집단을 비교한 결과 군 생활 영향 평가, 군 조직 이미지 평가, 병영 스트레스 수준에서 유의한 차이가 나타나는 것을 확인할 수 있었다. 이러한 결과를 통해 입대 전 입대 동기 유발의 중요성에 대해 논의하였다.

• 한국군사과학기술학회지
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• 제22권1호
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• pp.49-59
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• 2019

Generative adversarial networks(GANs) have received great attention in the machine learning field for their capacity to model high-dimensional and complex data distribution implicitly and generate new data samples from the model distribution. This paper investigates the model training methodology, architecture, and various applications of generative adversarial networks. Experimental evaluation is also conducted for generating synthetic image dataset for defense using two types of GANs. The first one is for military image generation utilizing the deep convolutional generative adversarial networks(DCGAN). The other is for visible-to-infrared image translation utilizing the cycle-consistent generative adversarial networks(CycleGAN). Each model can yield a great diversity of high-fidelity synthetic images compared to training ones. This result opens up the possibility of using inexpensive synthetic images for training neural networks while avoiding the enormous expense of collecting large amounts of hand-annotated real dataset.

• 한국군사과학기술학회지
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• 제16권2호
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• pp.207-213
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• 2013

An infrared image synthetic method is proposed for infrared system simulation. The synthesis image uses a background IR image captured from real scene and a target IR modeling image. The radiances related with maximum and minimum temperatures of the background and target images are calculated from the Planck's blackbody equation. Based on them, the background and target images are compensated and synthesized. The proposed method is simulated and the IR target images are generated by RadThermIR software.

• 한국군사과학기술학회지
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• 제1권1호
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• pp.238-248
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• 1998

This paper presents an image analysis method for mearurement correction using the object contour based analysis, which measure the shape features of the imitation missile object. The image analysis is divided into object's tilting angle analysis and corner points detection. The tilting angle is calculated by edge extracting the region-of-interest image and by Radon transform it. The corner points are obtained by contour tracking of binary image and its curvature data processing and analysis. The ability of this presented method is simulated and evaluated by the results of accuracy testing.