• 농촌지도와개발
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• 제17권4호
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• pp.827-849
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• 2010

The study aims to examine the brand image for developing place name and local brand to create effective development. The data were collected purposive sampling technique by face-to face interview. 154 of resident and 152 of visitor in Seocheon county were used for analysis. Collected data were analyzed by ANOVA and factor analysis. The study found that it was deducted as passionate, comfortable, conservative image through exploring factor analyze that was about brand image's individuality in Seocheon county. And, it had an order that was Konmoe (29.2%), Solli(20.8%), Soya(17.5%) on resident, Konmoe(30.9%), Solli(19.7%), Munitgol(16.4%) on visitor, in place name favorable degree of the nature village. Results suggest that place name be utilized by brand individuality for place marketing effectively.

• 한국수산과학회지
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• 제28권3호
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• pp.309-315
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• 1995

This paper describes a monitoring system for fish farm formation effect based on personal computer by using an image processing technique. This method is based on image processing technique incorporating concept of window and threshold processing to track the target object and to distinguish it from background. The image processing program runs in the veal time so that all program modules are able to process multi-task. The effectiveness is evaluated through the comparative study on the motion of lantern net for the scallop culturing by wave action in an experimental wave tank.

• Current Optics and Photonics
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• 제1권4호
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• pp.344-350
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• 2017

We present a new design approach and an example design for an image-space telecentric two-mirror system that has a fast f-number and a wide-field line image. The initial design of the telecentric mirror system is a conventional axially symmetric system, consisting of a flat primary mirror with fourth-order aspheric deformation and an oblate ellipsoidal secondary mirror to correct spherical aberration, coma, and field curvature. Even though in the optimized design the primary mirror is tilted, to avoid ray obstruction by the secondary mirror, the image-space telecentric two-mirror system shows quite good imaging performance, for a line imager.

• 산업경영시스템학회지
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• 제18권35호
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• pp.1-8
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• 1995

Automatic inspection system software for display image characteristic of CRT is developed. There are two major contributions of this software development. One is that the data from measuring equipments which was usually collected manually is automatically collected through RS-232C port and is saved in computer, then, trend analysis graph and final reports are generated. The other is that evauation of characteristic of electron gun was automatically processed by CCD camera and image processing technique. The system is developed under MS-Windows environment utilizing Borland C++4.0 Compiler and DT 3852-8 image processor board. This system can save the time and man power to measure and to anayze the image characteristics relative to current method.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 봄 학술논문 발표대회
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• pp.162-163
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• 2021

Currently, the depth of cracks is measured using ultrasonic detectors in maintenance practice. This method consists of measuring the depth of cracks by attaching ultrasonic depth measuring equipment to the concrete surface, and there are restrictions on the timing and location of the inspection. These limitations can be addressed through the development of image-based crack depth measurement AI technology. If crack depth measurements are made based on images, restrictions on the timing and location of inspections can be lifted because images acquired with simple filming equipment can be used as input information. To efficiently develop these artificial intelligence technologies, it is essential to identify the interrelationship between crack depth measurements and image characteristic information. Thus, this study is a basic study of the development of image-based crack depth measurement AI technology and aims to identify image characteristic information related to crack depth.

• 한국의류학회지
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• 제46권4호
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• pp.704-722
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• 2022

Current studies validate the Body Positive Scale (BP Scale) as a self-assessment instrument that captures four dimensions of the positive body image construct. We developed and evaluated a 17-item BP Scale using two focus group interviews and four independent samples (n = 1,379) of Korean women who completed online survey questionnaires. We generated an initial pool of items via literature review, content validation with experts, and focus group interviews, subsequently refining the items through exploratory analysis (Study 1). We confirmed the BP Scale's underlying dimensions with young Korean female samples (Study 2, Study 4) and with a community sample (Study 3). We also examined the construct validity, internal consistency, and test-retest reliability over a six-week interval. Overall, the results supported that the four-factor BP Scale demonstrates adequate validity and reliability in measuring positive body image among Korean women. The BP Scale provides a method for researchers and practitioners to understand and assess individuals' positive body image in a multifaceted manner.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.739-742
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• 2005

In this paper, an efficient detection algorithm for the flicker, which is caused by mismatching between light frequency and exposure time at CMOS image sensor (CIS), is proposed. The flicker detection can be implemented by specific hardware or complex signal processing logic. However it is difficult to implement on single chip image sensor, which has pixel, CDS, ADC, and ISP on a die, because of limited die area. Thus for the flicker detection, the simple algorithm and high accuracy should be achieved on single chip image sensor,. To satisfy these purposes, the proposed algorithm organizes only simple operation, which calculates the subtraction of horizontal luminance mean between continuous two frames. This algorithm was verified with MATLAB and Xilinx FPGA, and it is implemented with Magnachip 0.18 standard cell library. As a result, the accuracy is 95% in average on FPGA emulation and the consumed gate count is about 7,500 gates (@40MHz) for implementation using Magnachip 0.18 process.

• 한국콘텐츠학회논문지
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• 제10권2호
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• pp.138-145
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• 2010

입체영상 기술은 차세대 입체 멀티미디어 정보통신 분야에서 공통적으로 요구되는 핵심 기반기술이라 할 수 있다. 현실과 가까운 자연스러운 영상을 표현하고자 하는 입체영상의 구현은 인간이 끊임없이 노력해온 부분으로, 초기의 시각 인식체계에서 시작해 양안시차를 이용한 입체사진을 거쳐 동영상 입체시대로 이행 되었다. 생활이 변화하고, 새로운 문화가 형성되고, IT산업 확장 등 핵심 트렌드의 바탕에는 가상을 실제처럼 구현하는 기술의 발전이 있으며, 그 중심에는 3D 입체영상 기술이 있다. 본 논문에서는 3D 입체영상 기술개발 동향 및 개발전략을 살펴보고, 지속적인 시장 확대를 위한 3D 입체영상 기술의 효율적 활용방안을 제시하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권7호
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• pp.3268-3283
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• 2018

With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

• 시스템엔지니어링학술지
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• 제1권2호
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• pp.26-33
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• 2005

In this paper, an algorithm is presented to recognize road based on unpaved test courses image. The road images obtained by a video camera undergoes a pre-processing that includes filtering, gray level slicing, masking and identification of unpaved test courses. After this pre-processing, a part of image is grouped into 27 sub-windows and fed into a three-layer feed-forward neural network. The neural network is trained to indicate the road direction. The proposed algorithm has been tested with the images different from the training images, and demonstrated its efficacy for recognizing unpaved road. Based on the test results, it can be said that the algorithm successfully combines the traditional image processing and the neural network principles towards a simpler and more efficient driver warning or assistance system.