• Journal of the Korean Society of Radiology
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• v.2 no.2
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• pp.17-21
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• 2008

Image quality is improved if the high frequency domains of boundary surface are made distinct. We suggested a method of correcting indistinct defects in ultrasonic images resulting from dynamic imaging. According to the results of the experiment, boundaries in input ultrasonic images became distinct. However, we need to solve the problem that information on pixels of low signal intensity adjacent to boundaries is lost because high-frequency components in the boundaries are strong.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.1
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• pp.193-200
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• 2003

This paper proposes a novel algorithm to recognize the curve of a structured road. The proposed algorithm uses an LCF (Lane Curve Function) obtained by the transformation of a parabolic function defined on world coordinate into image coordinate. Unlike other existing methods, the algorithm needs no transformation between world coordinate and image coordinate owing to the LCF. In order to search for an LCF describing the lane best, the differential comparison between the slope of an assumed LCF and the phase angle of edge pixels in the LROI (Lane Region Of Interest) constructed by the LCF is implemented. As finding the true LCF, the lane curve is determined. The proposed method is proved to be efficient through various kinds of images, providing the reliable curve direction and the valid curvature compared to the real road.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1172-1179
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• 2015

A wireless license plate region extracting module is proposed for LPR system controlling multiple gates. This module is cheaply implemented using Raspberry Pi which is open source and high performance. First, as the upper 1/3 of the captured image is discarded as it has no useful information on license plate. Using the OpenCV libraries the edge image is got by Canny algorithm after applying Gaussian filtering to gray image, and the labeling is conducted for 4 consecutive numbers in license plate. These numbers are located using various decision equations, and expanding the numbers region the final license plate region can be extracted. The result image is transferred to Server using wifi direct. Using the proposed module it becomes easy to set up and maintain the LPR system. The experimental results showed that the successful extracting rate was 98.4% using 500 car images with 640 × 480 resolution.

• Journal of the Korean Mathematical Society
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• v.55 no.3
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• pp.719-734
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• 2018

An image restoration problem with Poisson noise arises in many applications of medical imaging, astronomy, and microscopy. To overcome ill-posedness, Total Variation (TV) model is commonly used owing to edge preserving property. Since staircase artifacts are observed in restored smooth regions, higher-order TV regularization is introduced. However, sharpness of edges in the image is also attenuated. To compromise benefits of TV and higher-order TV, the weighted sum of the non-convex TV and non-convex higher order TV is used as a regularizer in the proposed variational model. The proposed model is non-convex and non-smooth, and so it is very challenging to solve the model. We propose an iterative reweighted algorithm with the proximal linearized alternating direction method of multipliers to solve the proposed model and study convergence properties of the algorithm.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.4
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• pp.447-452
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• 1988

This paper proposes a hybrid image coding in order to improve the coding performance by combining the BTC with the DPCM. And utilizing the human perceptual characteristics, a new objective image quality evaluation method has been proposed to obtain an excellent result in good agreement with the subjective quality evaluation. A hyb-1 method consisting of the DPCM and the AMBTC has retained a good picture quality at the bit rate of 1.5 bits/pel. A hyb-3 method combining the EBTC-3 with the DPCM has scarcely degraded the picture quality compared with the original image at the bit rate of 2.1 bits/pel. A newly proposed mehtod of picture quality evaluation accumulating a blocky noise at the edge block and an impulsive noise at the flat block selectively has been coincident with the subjective evaluation of quality.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.118-126
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• 2020

In this paper, we present an effective single image fog removal by using the Joint Bright and Dark Channel (JBDC) and pixel-based transmission estimation to enhance the visibility of outdoor images susceptible to degradation due to weather and environmental conditions. The conventional methods include refinement process of coarse transmission with heavy computational complexity. The proposed transmission estimation reveals excellent edge-preserving performance and does not require the refinement process. We estimate the atmospheric light in pixel-based fashion, which can improve the transmission estimation performance and visual quality of the restored image. Moreover, we propose an adaptive transmission estimation to enhance the visual quality specifically in sky regions. Comprehensive experiments on various fog images show that the proposed method exhibits reduced computational complexity and excellent fog removal performance, compared with the existing methods; thus, it can be applied to various fields including real-time devices.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.80-85
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• 2008

Images are often corrupted by noises during signal acquisition and transmission. Among those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. For different types of noise have different characters, how to remove them separately from degraded image is one of the most fundamental problems. Thus, a modified image restoration algorithm is proposed in this paper, which can not only remove impulse noise of random values, but also remove the AWGN selectively. The noise detection step is by calculating the intensity difference and the spatial distance between pixels in a mask. To divide two different noises, the method is based on three weighted parameters. And the weighted parameters in the filtering mask depend on spatial distances, positions of impulse noise and standard deviation of AWGN. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, and simulation results demonstrate that the proposed method performs better than conventional median-type filters, in preserving edge details.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.365-368
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• 2001

This work describes a real-time method, based on motion energy detection, for detecting and tracking moving object in the consecutive image sequences. The motion of moving objects is detected by taking the difference of the two consecutive image frames. In addition an edge information of the current image is utilized in order to further increase the accuracy of detection. We can track the moving objects continuously by detecting the motion of objects from the sequence of image frames. A prototype system has been implemented using a TI TMS320C6201 EVM fixed-point DSP board, which can successfully track a moving human in real-time.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.346-349
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• 1993

A method for image compression based on decomposition is presented. We design the efficient coding technique for upper band image signals. This coding technique with directive 1-D DPCM is based on the statistical properties of upper bands. Lower band image signals is encoded using 2-D DPCM. The directive 1-D DPCM is performed, scanning upper bands according to edge direction. And then the predicted error signals of upper band sis coded using B1 and Huffman code, and the predicted error signals of lower band is coded using Huffman code. The proposed system shows improved performance when compared with other existing methods with respect to peak signal to noise ratio(PSMR) and human visual system(HVS) properties.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.923-924
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• 2008

Image completion is to repair a portion of removed image automatically. In this paper, we propose an image completion technique with inner structure estimation. Our method consists of two steps. An inner structure is first estimated by using sobel edge detector. Then, the removed pixels are repaired using similar patches in the known region. By experimental results, it is shown that our approach works well on natural images.