• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.9-14
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• 2015

In this paper, we present an color quantization method by complementing the disadvantage of K-means color quantization that is one of the well-known color quantization. We named the proposed method "octree-means" color quantization. K-means color quantization does not use all of the clusters because it initializes the centroid of clusters with random value. The proposed method complements this disadvantage by using the octree color quantization which is fast and uses the distribution of colors in image. We compare the proposed method to six well-known color quantization methods on ten test images to evaluate the performance. The experimental results show 68.29 percent of mean square error(MSE) and processing time increased by 14.34 percent compared with K-means color quantization. Therefore, the proposed method improved the K-means color quantization and perform an effective color quantization.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.257-262
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• 2002

영상을 적은 비트로 표현할 때 먼저 양자화를 이용하여 칼라맵을 생성한다. 그리고 적은 비트의 칼라맵으로도 인간의 시각에 적합하게 표현하기 위해 디더링을 결합한다. 본 논문에서는 디더링 기법중 오차확산법이 주변화소로 양자화 에러를 확산한다는 것을 고려하여 칼라맵을 생성하는 새로운 방법을 제안한다. 제안방법은 LBG 알고리즘의 개선하여 클러스터의 양자화 벡터를 구하는 각각의 반복단계에서 현재 양자화 벡터와 새로운 중심값(centroid)을 연결하는 직선 상에서 새로운 양자화벡터를 구하는 기존의 알고리즘에 에러를 고려하여 새로운 양자화 벡터를 얻을 수 있도록 하였다. 제안방법을 적용하였을 때 기존의 LBG 알고리즘에 비해 양자화 영상과 디더영상의 화질이 개선되었다. 또한 각 칼라별 MSE 와 영상전체 MSE 에 대해서도 제안방법은 기존의 LBG 알고리즘에 대해 개선되었다.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.17-27
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• 2011

This paper investigates some critical errors influencing travel demand estimation in Korea Transportation Data Base (KTDB), and through this investigation reasonable traffic analysis zone (TAZ) size and internal trips ratio are analyzed. With varying zone size, the accuracy of travel demand estimation is studied and appropriate level of zone size in KTDB is also presented. For this purpose zonal structure consisting of location of zone centroid, number of centroid connecters has been constructed by social economic index, and then some descriptive statistical analyses such as F-test, coefficient of correlation are performed. From the results, this paper shows that the optimum levels of zone system were various according to the order and capacity of roads, and also shows that the smaller TAZ, the less error in this research. In conclusion, in order to improve accuracy of traffic demand estimation it is necessary to make zone size smaller.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.297-304
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• 2010

Since the change in Doppler centroid according to moving targets brings alteration to the phase in azimuth differential signals of synthetic aperture radar (SAR) data, one can measure the velocity of the moving targets using this effect. In this study, we will investigate theoretically measuring the velocity of an object from azimuth differential signals by using range compressed data which is the interim outcome of treatment from the simulated SAR raw data of moving targets on the background of sea clutter. Also, it will provide evaluation for the elements that affect the estimation error of velocity from a single SAR sensor. By making RADARSAT-1 simulated image as a specific case, the research includes comparisons for the means of velocity measurement classified by the directions of movement in the four following cases. 1. A case of a single target without currents, 2. A case of a single target with tidal currents of 0.5 m/s, 1 m/s, and 3 m/s, 3. A case of two targets on a same azimuth line moving in a same direction and velocity, 4. A case of a single target contiguous to land where radar backscatter is strong. As a result, when two moving targets exist in SAR image outside the range of approximately 256 pixels, the velocity of the object can be measured with high accuracy. However, when other moving targets exist in the range of approximately 128 pixels or when the target was contiguous to the land of strong backscatter coefficient (NRCS: normalized radar cross section), the estimated velocity was in error by 10% at the maximum. This is because in the process of assuming the target's location, an error occurs due to the differential signals affected by other scatterers.

• Journal of Biomedical Engineering Research
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• v.8 no.1
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• pp.41-48
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• 1987

In estimating the freguency-dependent attenuation coefficient, we analyzed the range-dependent ultrasonic beam and proposed the method of calculating the experimental equation of beam pattern in order to reduce the error on the influence of beam pattern. These experimental equations are divided into the spectral centroid and the spec ural standard deviation slope according to axial propagation length. These are repnesented by the first-order equation in the near field of the beam and the second- order eqLlatlon In the far field. In order to prove the validity of this method, the attenuation coefficients of the non-corrected ease and the corrected case are compared. Using the reflected signal from acryle plate, the attenuation coefficients were estimated by the spectral shift method ann the spectral difference method. The result shows attenuation coeffi talents after correction are better than attenuation coefficients before correction. And this method can be applied In vivo measurement.

• Journal of the Optical Society of Korea
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• v.10 no.1
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• pp.16-22
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• 2006

Wavefront sensing using a Shack-Hartmann sensor has been widely used for estimating wavefront errors or distortions. The sensor combines the local slopes, which are estimated from the centroids of each lenslet image, to give the overall wavefront reconstruction. It was previously shown that the pupil-plane irradiance profile effects the centroid estimation. Furthermore, a previous study reported that the reconstructed wavefront from a planar wavefront with a Gaussian pupil irradiance profile contains large focus and spherical aberration terms when there is a focus error. However, it has not been reported yet how seriously the pupil irradiance profiles, which can occur in practical applications, effect the sensing errors. This paper considered two cases when the irradiance profiles are not uniform: 1) when the light source is Gaussian and 2) when there is a partial interference due to a double reflection by a beam splitting element. The images formed by a Shack-Hartmann sensor were simulated through fast Fourier transform and were then supposed to be detected by a noiseless CCD camera. The simulations found that sensing errors, due to the Gaussian irradiance profile and the partial interference, were found to be smaller than RMS ${\lambda}/50$ when ${\lambda}$ is $0.6328\;{\mu}m$, which can be ignored in most practical cases where the reference and test beams have the same irradiance profiles.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.648-661
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• 1997

This paper presents a new method for post-processing of coded images based upon the low-pass filtering followed by the projection onto the NQCS (narrow quantization constraint set). We also investigate how the proposed method works on JPEG-coded real images. The starting point of the QCS-based post-processing techniques is the centroid of the QCS, where the original image belongs. The low-pass filtering followed by the projection onto the QCS makes the images lie on the boundary of the QCS. It is likely that, however, the original image is inside the QCS. Hence projection onto the NQCS gives a lower MSE (mean square error) than does the projection onto the QCS. Simulation results show that setting the narrowing coefficients of the NQCS to be 0.2 yields the best performance in most cases. Even though the JPEG-coded image is low-pass filtered and projected onto the NQCS repeatedly, there is no guarantee that the resultant image has a lower MSE and goes closer to the original image. Thus only one iteration is sufficient for the post-processing of the coded images. This is interesting because the main drawback of the iterative post-processing techniques is the heavy computational burden. The single iteration method reduces the computational burden and gives us an easy way to implement the real time VLSI post-processor.

• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.201-211
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• 2021

Purpose: This paper proposes a density adaptive grid algorithm for the k-NN regression model to reduce the computation time for large datasets without significant prediction accuracy loss. Methods: The proposed method utilizes the concept of the grid with centroid to reduce the number of reference data points so that the required computation time is much reduced. Since the grid generation process in this paper is based on quantiles of original variables, the proposed method can fully reflect the density information of the original reference data set. Results: Using five real-life datasets, the proposed k-NN regression model is compared with the original k-NN regression model. The results show that the proposed density adaptive grid-based k-NN regression model is superior to the original k-NN regression in terms of data reduction ratio and time efficiency ratio, and provides a similar prediction error if the appropriate number of grids is selected. Conclusion: The proposed density adaptive grid algorithm for the k-NN regression model is a simple and effective model which can help avoid a large loss of prediction accuracy with faster execution speed and fewer memory requirements during the testing phase.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.399-408
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• 2020

The construction industry is suffering from aging workers, frequent accidents, as well as low productivity. With the rapid development of information technologies in recent years, automatic construction, especially automatic cranes, is regarded as a promising solution for the above problems and attracting more and more attention. However, in practice, limited by the complexity and dynamics of construction environment, manual inspection which is time-consuming and error-prone is still the only way to recognize the search object for the operation of crane. To solve this problem, an image-processing-based automated object recognition approach is proposed in this paper, which is a fusion of Convolutional-Neutral-Network (CNN)-based and traditional object detections. The search object is firstly extracted from the background by the trained Faster R-CNN. And then through a series of image processing including Canny, Hough and Endpoints clustering analysis, the vertices of the search object can be determined to locate it in 3D space uniquely. Finally, the features (e.g., centroid coordinate, size, and color) of the search object are extracted for further recognition. The approach presented in this paper was implemented in OpenCV, and the prototype was written in Microsoft Visual C++. This proposed approach shows great potential for the automatic operation of crane. Further researches and more extensive field experiments will follow in the future.

• Current Optics and Photonics
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• v.8 no.1
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• pp.38-44
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• 2024

Under the influence of atmospheric turbulence, a star's point image will shake back and forth erratically, and after exposure the originally small star point will spread into a huge spot, which will affect the ground calibration of the star sensor. To analyze the impact of atmospheric turbulence on the positioning accuracy of the star's center of mass, this paper simulates the atmospheric turbulence phase screen using a method based on a sparse spectrum. It is added to the static-star-simulation device to study the transmission characteristics of atmospheric turbulence in star-point simulation, and to analyze the changes in star points under different atmospheric refractive-index structural constants. The simulation results show that the structure function of the atmospheric turbulence phase screen simulated by the sparse spectral method has an average error of 6.8% compared to the theoretical value, while the classical Fourier-transform method can have an error of up to 23% at low frequencies. By including a simulation in which the phase screen would cause errors in the center-of-mass position of the star point, 100 consecutive images are selected and the average drift variance is obtained for each turbulence scenario; The stronger the turbulence, the larger the drift variance. This study can provide a basis for subsequent improvement of the ground-calibration accuracy of a star sensitizer, and for analyzing and evaluating the effect of atmospheric turbulence on the beam.