• 한국군사과학기술학회지
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• 제24권4호
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• pp.392-400
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• 2021

Unlike optical equipment, SAR(Synthetic Aperture Radar) has the advantage of obtaining images in all weather, and object detection in SAR images is an important issue. Generally, deep learning-based object detection was mainly performed in real-valued network using only amplitude of SAR image. Since the SAR image is complex data consist of amplitude and phase data, a complex-valued network is required. In this paper, a complex-valued ResNet network is proposed. SAR image object detection was performed by combining the ROI transformer detector specialized for aerial image detection and the proposed complex-valued ResNet. It was confirmed that higher accuracy was obtained in complex-valued network than in existing real-valued network.

• 한국멀티미디어학회논문지
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• 제10권4호
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• pp.432-440
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• 2007

본 논문에서는 복잡한 배경을 가지는 전방 관측 열상(FLIR; forward looking infrared) 영상에서의 소형 표적 탐지 기법을 제안하였다. 제안한 기법에서는 먼저 이전 프레임과 현재 프레임의 차를 구하여 표적의 움직임 정보를 획득할 뿐만 아니라 시간적으로 발생하는 배경 잡음을 제거한다. 이때 먼 거리에서 다가오는 표적이나 속도가 느린 표적의 경우 차 영상 내에서의 표적의 움직임 정보는 매우 작은 명암도 값을 가진다. 이런 작은 명암도 값을 두드러지게 하여 표적 탐지를 용이하게 하기 위하여 프레임 차 영상에 국부 감마교정을 행한다. 이렇게 표적이 개선된 영상에서 국부적인 통계적인 특성을 이용하여 탐지 지표를 계산한 후 가장 낮은 탐지 지표 값을 탐지하고자하는 표적으로 선정한다. 실험을 통하여 제안한 기법이 표적의 탐지성능이 기존의 탐지기법보다 우수하였음을 확인하였다.

• 한국컴퓨터정보학회논문지
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• 제21권6호
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• pp.21-28
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• 2016

Circle detection has long been studied as one of fundamental image processing applications. It is used in divers areas including industrial inspection, medial image analysis, radio astronomy data analysis, and other object recognition applications. The most widely used class of circle detection techniques is the circle Hough transform and its variants. Management of 3 dimensional parameter histogram used in these methods brings about spatial and temporal overheads, and a lot of studies have dealt the problem. This paper proposes a robust circle detection method using maximal symmetry property of circle. The basic idea is that if perpendicular bisectors of pairs of edges are accumulated in image space, center of circle is determined to be the location of highest accumulation. However, directly implementing the idea in image space requires a lot of calculations. The method of this paper reduces the number of calculations by mapping the perpendicular bisectors into parameter space, selecting small number of parameters, and mapping them inversely into image space. Test on 22 images shows the calculations of the proposed method is 0.056% calculations of the basic idea. The test images include simple circles, multiple circles with various sizes, concentric circles, and partially occluded circles. The proposed method detected circles in various situations successfully.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.100-103
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• 2014

현재 에지 검출은 여러 분야에서 사용되고 있으며, 대부분의 영상처리의 전처리 과정 및 영상처리에 있어서 필수불가결한 기술이다. 이에 따라 관련 연구가 끊임없이 진행되어 오고 있다. 이러한 에지는 영상의 물체에 대한 크기, 방향, 위치 등의 중요한 영상 요소를 가지고 있다. 이를 검출하기 위한 여러 방법들이 제안되어 왔으며, 그 중 대표적인 방법은 Sobel, Prewitt, Roberts, Laplacian, LoG(Laplacian of Gaussian) 등이 있다. 그러나 이러한 기존의 방법들은 복합잡음이 첨가된 영상에서 에지 검출 특성이 미흡하다. 따라서 본 연구에서는 국부 마스크의 크기와 위치에 따라 요소에 대한 중앙값 및 평균값을 이용한 에지 검출 방법을 제안하였다.

• 제어로봇시스템학회논문지
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• 제19권1호
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• pp.65-71
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• 2013

In this work, new smart phone based moving target detection is proposed. In order to implement the task, methods of real time image transmission from network camera, motion detecting algorithm and its effective implementation are also addressed. The network camera transfers image data by MJPEG format which contains various information such as data and IP address, and the smart phone separates the image data received through a WiFi module. Later, the image data is converted to a Bitmap image format, and with the help of the embedded OpenCV library on a smart phone and algorithm, it was found that the moving object was identified effectively in terms of real time monitoring and detection.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.225-227
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• 1995

An object detection algorithm using a modified IDM(Image Differential Method) is proposed for detecting an object in a level crossing area. The conventional object detection method using LASER light has the deadzone that it cannot detect small objects, while the object detection method using image data in a level crossing area can detect such small objects. But the image data in a level crossing area can be changeable easily because the data is outdoor and sensitive to such surrounding environments as the change of the sun beam, the shadow of cars, and so on. So we resolve these problems by adding the normalization and the process for shadow of the image data in a level crossing area to the basic IDM(Image Differential Method).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권6호
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• pp.2005-2021
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• 2014

This paper proposes a novel image authentication scheme, aiming at tampering detection for block truncation coding (BTC) compressed image. The authentication code is generated by using the random number generator with a seed, and the size of the authentication code is based on the user's requirement, with each BTC-compressed image block being used to carry the authentication code using the data hiding method. In the proposed scheme, to obtain a high-quality embedded image, a reference table is used when the authentication code is embedded. The experimental results demonstrate that the proposed scheme achieves high-quality embedded images and guarantees the capability of tamper detection.

• 한국안전학회지
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• 제18권4호
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• pp.23-27
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• 2003

To improve the road transportation safety, the road traffic data is monitored by applying an image detection system. The road traffic safety is analysed using image processing techniques. For more accurate measurement, the coordinate matching of real road data to image is one of the most essential parts of the image detection technique. The road image is skewed at the input screen, because the video camera is installed at the roadside. A fast and precise algorithm for the coordinate matching is developed to convert image coordinates into road coordinates.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1268-1271
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• 2003

In the edge detection of RS image, the useful detail losing and the spurious edge often appear. To solve the problem, we use the dyadic wavelet to detect the edge of surface features by combining the edge detecting with the multi-resolution analyzing of the wavelet transform. Via the dyadic wavelet decomposing, we obtain the RS image of a certain appropriate scale, and figure out the edge data of the plane and the upright directions respectively, then work out the grads vector module of the surface features, at last by tracing them we get the edge data of the object therefore build the RS image which obtains the checked edge. This method can depress the effect of noise and examine exactly the edge data of the object by rule and line. With an experiment of a RS image which obtains an airport, we certificate the feasibility of the application of dyadic wavelet in the object edge detection.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1288-1296
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• 2016

The reliable detection of the limited defect in TFT-LCD images is difficult due to the small intensity difference with the background. However, the proposed detection method reliably detects the limited defect by enhancing the TFT-LCD image based on the cumulative histogram and then detecting the defect through the mean and standard deviation of the enhanced image. Notably, an image enhancement using a cumulative histogram increases the intensity contrast between the background and the limited defect, which then allows defects to be detected by using the mean and standard deviation of the enhanced image. Furthermore, through the comparison with the histogram equalization, we confirm that the proposed algorithm suppresses the emphasis of the noise. Experimental comparative results using real TFT-LCD images and pseudo images show that the proposed method detects the limited defect more reliably than conventional methods.