• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.6
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• pp.594-599
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• 2008

Image data produced from ADD water-tunnel test are currently analyzed manually. The accuracy and elapsed time of this process can be determined by observers. In this paper, the algorithm based on MATLAB for improved image data processing and analysis is proposed. This algorithm consists of camera calibration, gray-level transformation, noise filtering and binarization in image preprocessing, vortex trajectory measurement in image analysis. Experimental results show that the proposed algorithm has better accuracy and execution speed than those of the existing methods.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.289-294
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• 2002

A valid speech-sound block can be classified to provide important information for speech recognition. The classification of the speech-sound block comes from the MRA(multi-resolution analysis) property of the DWT(discrete wavelet transform), which is used to reduce the computational time for the pre-processing of speech recognition. The merging algorithm is proposed to extract valid speech-sounds in terms of position and frequency range. It needs some numerical methods for an adaptive DWT implementation and performs unvoiced/voiced classification and denoising. Since the merging algorithm can decide the processing parameters relating to voices only and is independent of system noises, it is useful for extracting valid speech-sounds. The merging algorithm has an adaptive feature for arbitrary system noises and an excellent denoising SNR(signal-to-nolle ratio).

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.279-279
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• 2022

최근 이미지분석 기술은 하드웨어 및 소프트웨어 기술의 급격한 발전으로 인해 의학, 생물학, 지리학, 재료공학 등에서 수많은 연구 분야에서 광범위하게 활용되고 있으며, 이미지분석은 다량의 토사에 대하여 입경을 포함한 형상학적 특성을 간편하게 정량화 할 수 있기 때문에 매우 효과적인 분석 방법으로 판단된다. 현재 모래의 입도분석 방법으로는 신뢰성 있는 체가름 시험법(KSF2302) 등이 있으나, 번거로운 처리과정과 많은 시간이 소요된다. 또한 입자형상은 입경이 세립 할수록 직접 측정이 어렵기 때문에, 최근에는 이미지 분석을 이용하는 방법이 시도되고 있다. 본 연구에서는 75㎛ 이상의 조립질 하상 토사 이미지를 취득하여, 입자들의 장·축단 길이, 면적, 둘레, 공칭직경 및 종횡비 등의 형상학적 특성인자를 자동으로 측정하는 프로그램 개발을 수행하였다. 프로그램은 이미지 분석에 특화된 라이브러리인 OpenCV(Open Source Computer Vision)를 적용하였다. 이미지 분석 절차는 크게 이미지 취득, 기하보정, 노이즈제거, 객체추출 및 형상인자 측정 단계로 구성되며, 이미지 취득시 패널의 하단에 Back light를 부착해 시료에 의해 발생되는 음영을 제거하였다. 기하보정은 원근변환(perspective transform)을 적용했으며, 노이즈 제거는 모폴로지 연산과 입자간의 중첩으로 인한 뭉침을 제거하기 위해 watershed 알고리즘을 적용하였다. 최종적으로 객체의 외곽선 추출하여 입자들의 다양한 정보(장축, 단축, 둘레, 면적, 공칭직경, 종횡비)를 산출하고, 분포형으로 제시하였다. 본 연구에서 제안하는 이미지분석을 적용한 토사의 형상학적 특성 측정 방법은 시간과 비용의 측면에서 보다 효율적으로 하상 토사에 대한 다양한 정보를 획득 할 수 있을 것으로 기대한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2192-2200
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• 2015

In this paper, we propose an efficient vehicle image compensation algorithm based on Histogram Equalization. The proposed a vehicle image compensation algorithm was elimination to the vehicle image shake using motion compensation and motion estimation. And, algorithm was calculated the histogram of pixel values from each sub-image by dividing the image as the constant size areas in order to image enhancement. Also, it had enhancement to the image by adjusting the gradient. The proposed algorithm was evaluate the difference between of performance and time, image by applied to the IP, and were confirmed the image enhancement with removing of vehicle camera image shake. In this paper, the proposed vehicle image enhancement algorithm was demonstrated effectiveness when compared to existing vehicle image stabilization, because the elimination of shake for the vehicle images used real-time processing without using a memory. And it was obtained the reduction effect of the computation time by the calculated through block matching, and obtained the better restoration result for naturalness of the image with the lowest noise.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.679-684
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• 2023

Venous puncture is widely used to obtain blood samples for pathological examination. Because the invasive venipuncture method using a needle is repeatedly performed, the pain suffered by the patient increases, so our research team pre-developed a miniaturized near-infrared (NIR) imaging system in advance. To improve the image quality of the acquired NIR images, this study aims to model the non-local means (NLM) algorithm, which is well known to be efficient in noise reduction, and analyze its applicability in the system. The developed NIR imaging system is based on the principle that infrared rays pass through dichroic and long-pass filters and are detected by a CMOS sensor module. The proposed NLM algorithm is modeled based on the principle of replacing the pixel from which noise is to be removed with a value that reflects the distances between surrounding pixels. After acquiring an NIR image with a central wavelength of 850 nm, the NLM algorithm was applied to segment the final vein area through histogram equalization. As a result, the coefficient of variation of the NIR image of the vein using the NLM algorithm was 0.247 on average, which was an excellent result compared to conventional filtering methods. In addition, the dice similarity coefficient value of the NLM algorithm was improved by 62.91 and 9.40%, respectively, compared to the median filter and total variation methods. In conclusion, we demonstrated that the NLM algorithm can acquire accurate segmentation of veins acquired with a NIR imaging system.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.724-733
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• 2017

Conventional methods of automatically recording Go game positions do not properly consider obstacles (hand or object) on a Go board during the Go game. If the Go board is blocked by obstacles, the position of a Go stone may not be correctly recognized, or the sequences of moves may be stored differently from the actual one. In the proposed algorithm, only the complete Go board image without obstacles is stored as a background image and the obstacle is recognized by comparing the background image with the current input image. To eliminate the phenomenon that the shadow is mistaken as obstacles, this paper proposes the new obstacle detection method based on the gradient image instead of the simple differential image. When there is no obstacle on the Go board, the background image is updated. Finally, the successive background images are compared to recognize the position and type of the Go stone. Experimental results show that the proposed algorithm has more than 95% recognition rate in general illumination environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.388-393
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• 2010

Cultural Content Technology(CT, Culture Technology) for the development of cultural industry and the commercialization of technology, cultural contents, media, mount, pass the value chain process and increase the added value of cultural products that are good for all forms of intangible technology. In the field of Culture Technology, Music by analyzing the characteristics of the development of a variety of applications has been studied. Associated with EEG measures and the results of their research in response to musical stimuli are used to detect and study is getting attention. In this paper, the musical stimuli in EEG signals by amplifying the corresponding reaction to the averaging method, ERP (Event-Related Potentials) experiments based on the process of extracting sound methods for removing noise from the ICA algorithm to extract the tone and noise removal according to the results are applied to analyze the characteristics of EEG.

• Journal of KIBIM
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• v.10 no.4
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• pp.32-39
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• 2020

In recent years, the construction industry is getting bigger and more complex, so it is becoming difficult to acquire point cloud data for construction equipments and workers. Point cloud data is measured using a drone and MMS(Mobile Mapping System), and the collected point cloud data is used to create a 3D digital map. In particular, the construction site is located at outdoors and there are many irregular terrains, making it difficult to collect point cloud data. For these reasons, adopting a noise reduction algorithm suitable for the characteristics of the construction industry can affect the improvement of the analysis accuracy of digital maps. This is related to various environments and variables of the construction site. Therefore, this study reviewed and analyzed the existing research and techniques on the noise reduction algorithm. And based on the results of literature review, performance evaluation of major noise reduction algorithms was conducted for digital maps of construction sites. As a result of the performance evaluation in this study, the voxel grid algorithm showed relatively less execution time than the statistical outlier removal algorithm. In addition, analysis results in slope, space, and earth walls of the construction site digital map showed that the voxel grid algorithm was relatively superior to the statistical outlier removal algorithm and that the noise removal performance of voxel grid algorithm was superior and the object preservation ability was also superior. In the future, based on the results reviewed through the performance evaluation of the noise reduction algorithm of this study, we will develop a noise reduction algorithm for 3D point cloud data that reflects the characteristics of the construction site.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.55-63
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• 2008

Ridge orientations of fingerprint image are crucial informations in many parts of fingerprint recognition such as enhancement, matching and classification. Therefore it is essential to extract the ridge orientations of image accurately because it directly affects the performance of the system. The two main properties of ridge orientation are 1) global characteristic(gradual change in whole part of fingerprint) and 2) local characteristic(abrupt change around core and delta points). When we only consider the local characteristic, estimated ridge orientations are well around singular points but not robust to noise. When the global characteristic is only considered, to estimate ridge orientation is robust to noise but cannot represent the orientation around singular points. In this paper, we propose a novel method for estimating ridge orientation which represents local characteristic specifically as well as be robust to noise. We reduce the noise caused by scar using iterative outlier rejection. We apply adaptive measurement resolution in each fingerprint area to estimate the ridge orientation around singular points accurately. We evaluate the performance of proposed method using synthetic fingerprint and FVC 2002 DB. We compare the accuracy of ridge orientation. The performance of fingerprint authentication system is evaluated using FVC 2002 DB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.673-682
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• 2004

The adaptive beam-forming is promising approach for noise reduction in hearing aids. This approach has come in the focus of interest only recently, because of the availability of new and powerful digital signal processors. The adaptation U using usually a Least Mean Squares algorithm, updates the weight vector. In this Paper, we propose a fast wavelet based adaptive algorithm using variable step size algorithm which varies adaptive constant by the change of signal environment. We compared the performance of the proposed algorithm with the known adaptive algorithm using computer simulation of multi channel adaptive bemformer in hearing aids. As the result the proposed algorithm is suitable for adaptive signal processing area using hearing aids and has advantages reducing computational complexity. And we show the beam-forming system using proposed algorithm converges stably in a sudden change of system environment.