• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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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.

• Journal of Korea Multimedia Society
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• v.10 no.4
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• pp.432-440
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• 2007

In this paper, we propose a small target detection algorithm for FLIR image with complex background. First, we compute the motion information of target from the difference between the current frame and the created background image. However, the slow speed of target cause that it has the very low gray level value in the difference image. To improve the gray level value, we perform the local gamma correction for difference image. So, the detection index is computed by using statistical characteristics in the improved image and then we chose the lowest detection index a true target. Experimental results show that the proposed method has significantly the good detection performance.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.100-103
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• 2014

Currently, edge detection is utilized in various areas. Edge detection is the preprocessing process for image processing in general, and this is a technology that is considered essential for image processing. According, research on this subject is carried out incessantly. Edge has important image related elements such as size, direction and location of the object of an image. Numerous methods were proposed for the detection. Among them, the representative methods are Sobel, Prewitt, Roberts, Laplacian. However, these existing methods are rather lacking when it comes to the edge detection characteristics in case of the image with mixed noise. Therefore, this study presented edge detection method that utilizes median and average values for the elements depending on the size and location of local mask.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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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.

• Proceedings of the KIEE Conference
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• 1995.11a
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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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• v.8 no.6
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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.

• Journal of the Korean Society of Safety
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• v.18 no.4
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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.

• Proceedings of the KSRS Conference
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• 2003.11a
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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.

• Journal of Korea Multimedia Society
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• v.19 no.8
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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.