• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.4
• /
• pp.395-403
• /
• 2016

This paper introduces a multi-cell search method for heterogeneous networks (HetNet), in which user equipments need to search multiple cells in its vicinity simultaneously. Due to the difficulty of acquiring channel informations for multiple cells, a non-coherent approach is preferred. In this paper, a non-coherent single-cell search scheme using a weighted vector is proposed, and the successive interference cancellation based multi-cell search algorithm is devised. In order to improve cell search performance, the weighted vector is designed in a way to exploit the general characteristic of wireless channel. Based on the fact that the performance of the proposed single-cell search scheme deviates slowly from the one using the optimal weighted vector, a universal weighted vector is also proposed, which shows the performance close to the optimal ones for various channel environments and signal-to-noise ratio regimes. Simulation results confirm that the proposed multi-cell search algorithm is capable of identifying cells more accurately with the help of the proposed single-cell search scheme, and can detect the remaining cells more effectively by removing the signals of the identified cells from the received signal.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.12
• /
• pp.131-141
• /
• 2012

This paper proposes a method of analyzing unrecognizable numbers of license plate images, which are degraded by various factors such as low resolution, low light level, geometric distortion, and periodic noise, to name a few. With existing vehicle license plate recognition methods, it is difficult to recognize license plate if images are not recognizable in the pre-process of removing degradation factors. Although images of license plate have not been improved to be recognizable in the pre-process, the proposed method makes it possible to recognize numbers of license by distorting pre-saved reference images of license plate numbers same as sample plates, and by assuming likelihood ratio using statistical methods. The proposed method also makes it possible to identify suspect vehicle license plate under unstable light conditions and with low resolution images that are unrecognizable by the naked eye. This method has been used in real criminal investigation to recognize numbers of license plate of criminal vehicle, and has proved to be useful as criminal evidence through experiments under various conditions.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2003.04a
• /
• pp.3-8
• /
• 2003

모든 SAR 영상에는 전자기파 간의 간섭으로 인한 스페클 잡영(speckle)이 존재하며, 이를 제거하는 것은 양질의 SAR 영상을 얻기 위한 필수적인 전처리 과정 중 하나라고 할 수 있다. 그러나 이러한 스페클 잡영을 제거하기 위하여 기존에 제안되었던 알고리즘은 잡영은 효과적으로 감소시키는 반면 경계선과 같은 영상의 고유 정보까지 함께 감소시키는 한계가 있었다. 따라서 본 연구에서는 SAR 영상의 경계선은 보존시키면서 영상으로부터 불필요한 잡영을 제거할 수 있는 알고리즘을 구현하고, 기존의 알고리즘과 비교하여 그 효율성을 평가하고자 한다. 영상의 통계적 특성에 근거하는 기존의 알고리즘과는 달리 웨이블렛 변환(Wavelet transform)으로 경계선 및 특징 정보의 여부를 판별한 후 평균 필터(mean filter)를 적용하는 경계선 보존(edge sharpening) 알고리즘은 경계 정보의 신뢰성을 향상시킬 수 있으며, 1차원 필터를 수평, 수직, 대각선, 역대각선 방향으로 적용함으로써 하나의 영상소를 중심으로 모든 방향에 대한 경계선 여부를 확인할 수 있는 장점이 있다. 본 연구에서는 512 × 512로 절취한 1-look SAR 영상에 대하여 창 크기 5 × 5의 경계선 보존 필터를 적용하고 동일영상에 대하여 기존의 Lee, Kuan, Frost 필터 등의 실험결과를 비교함으로써 그 적합성을 판단하고자 하였다. 실험결과에 대한 수치적인 평가는 ①정규화 평균을 이용하여 평균값의 보존 여부, ②편차 계수를 이용한 스페클 잡영의 제거 여부, ③경계선 보존지수(EPI)를 이용한 경계선의 보존 정도를 통해 이루어졌다. 본 연구의 실험결과를 통해 경계선 보존 필터는 평균값의 보존 여부 및 스페클 잡영 제거 정도에 있어 다른 필터들과 큰 차이가 없지만 경계선보존지수는 다른 필터들에 비하여 가장 우수함을 확인할 수 있었다.rbon 탐식효율을 조사한 결과 B, D 및 E 분획에서 유의적인 효과를 나타내었다. 이상의 결과를 종합해볼 때, ${\beta}$-glucan은 고용량일 때 직접적으로 또는 $IFN-{\gamma}$ 존재시에는 저용량에서도 복강 큰 포식세로를 활성화시킬 뿐 아니라, 탐식효율도 높임으로써 면역기능을 증진 시키는 것으로 나타났고, 그 효과는 crude ${\beta}$-glucan의 추출조건에 따라 달라지는 것을 알 수 있었다.eveloped. Design concepts and control methods of a new crane will be introduced in this paper.and momentum balance was applied to the fluid field of bundle. while the movement of′ individual material was taken into account. The constitutive model relating the surface force and the deformation of bundle was introduced by considering a representative prodedure that stands for the bundle movement. Then a fundamental equations system could be simplified considering a steady state of the process. On the basis of the simplified model, the simulation was performed and the results could be confirmed by the experiments under various conditions.뢰, 결속 등 다차원

• Journal of Korean Society for Geospatial Information Science
• /
• v.25 no.2
• /
• pp.31-37
• /
• 2017

Recently, governmental authority and local government are looking for a method of utilizing location information of smart phone for urgent rescue in fire and kidnap situation. Under this background, in this study, a method of rapidly collecting, constructing location determination based Wi-Fi AP data utilizing location information of smart phone and mobile mapping system was suggested in order to construct precise positioning information that could be utilized under urgent situation. By performing compensation work for GPS/INS/DMI through collected outcome, position of collected vehicle was acquired. In addition, source data integrating Wi-Fi information and collected position by coupling based on Wi-Fi AP collector and GPS time was constructed and Wi-Fi radiomap was constructed by removing Wi-Fi signal noise that reduces precise position performance. As a result of performing location determination performance assess ment by selecting 10 test positions by each local government, result value of 25.46cm for total local government average and 27.76m for SD could be obtained. It is considered that this result could be utilized as a technology of being able to supplement or substituting GPS location determination technology that is impossible in plocation determination of mobile communication company's base station (200m~2km) and indoor being used at present.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.3
• /
• pp.511-516
• /
• 2006

In this raper, we propose the Sequentiel Couleur Avec Memoire or Sequential Color with Memory (SECAM) video encoder system using modified anti-cloche filters and the SECAM video decoder system using a band pass filter (BPF) and an error-free square root. The SECAM encoder requires an anti-cloche filter recommended by International Telecommunication Union-Recommendation (ITU-R) Broadcasting service Television (BT) 470. However, the design of the anti-cloche filter is difficult because the frequency response of the anti-cloche filter is very sharp around rejection-frequency area. So, we convert the filter into a hish pass filter (HPF) by shifting the rejection frequency of 4.286MHz to 0Hz frequency. The design of HPF becomes very easy, compared to that of the anti-cloche filter. The proposed decoder also uses an error-free square root, two differentiators and trigonometric functions to extract color-component information of Db and Dr accurately from frequency modulation (FM) signals in SECAM systems. Also, the BPF in decoder it used for removing color noise in chrominance and dividing CVBS into chrominance and luminance. The proposed systems are experimentally demonstrated with Altera FPGA APEX20KE EP20K1000EBC652-3 device and TV sets.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.20 no.2
• /
• pp.205-213
• /
• 2018

Development and validation of crop models often require measurements of biomass for the crop of interest. Considerable efforts would be needed to obtain a reasonable amount of biomass data because the destructive sampling of a given crop is usually used. The Kinect sensor, which has a combination of image and depth sensors, can be used for estimating crop biomass without using destructive sampling approach. This approach could provide more data sets for model development and validation. The objective of this study was to examine the applicability of the Kinect sensor for estimation of chinese cabbage fresh weight. The fresh weight of five chinese cabbage was measured and compared with estimates using the Kinect sensor. The estimates were obtained by scanning individual chinese cabbage to create point cloud, removing noise, and building a three dimensional model with a set of free software. It was found that the 3D model created using the Kinect sensor explained about 98.7% of variation in fresh weight of chinese cabbage. Furthermore, the correlation coefficient between estimates and measurements were highly significant, which suggested that the Kinect sensor would be applicable to estimation of fresh weight for chinese cabbage. Our results demonstrated that a depth sensor allows for a non-destructive sampling approach, which enables to collect observation data for crop fresh weight over time. This would help development and validation of a crop model using a large number of reliable data sets, which merits further studies on application of various depth sensors to crop dry weight measurements.

• Journal of Broadcast Engineering
• /
• v.15 no.4
• /
• pp.474-486
• /
• 2010

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.377-382
• /
• 2005

본 논문에서는 출입국자 관리의 효율성과 체계적인 출입국 관리를 위하여 여권 코드를 자동으로 인식하는 방법을 제안한다. 여권 이미지는 기울어진 상태로 스캔 되어 획득되어질 수도 있으므로 기울기 보정은 문자 분할 및 인식에 있어 매우 중요하다. 따라서 본 논문에서는 여권 영상을 스미어링한 후, 추출된 문자열 중에서 가장 긴 문자열을 선택하고 이 문자열의 좌측과 우측 부분의 두께 중심을 연결하는 직선과 수평선과의 기울기를 이용하여 여권 영상에 대한 각도 보정을 수행한다. 여권 코드 추출은 소벨 연산자와 수평 스미어링, 8방향 윤관선 추적 알고리즘을 적용하여 여권 코드의 문자열 영역을 추출하고, 추출된 여권 코드 문자열 영역에 대해 반복 이진화 방법을 적용하여 코드의 문자열 영역을 이진화 한다, 이진화된 문자열 영역에 대해 여권 코드의 인식율을 높이기 위하여 잡영 가지 제거 알고리즘을 적용하여 개별 문자의 잡영을 제거한 후에 개별 코드를 추출하며, CDM 마스크를 적용하여 추출된 개별코드를 복원한다. 추출된 개별코드는 개선된 퍼지 ART 알고리즘을 제안하여 인식에 적용한다. 실제 여권 영상을 대상으로 실험한 결과, CDM 마스크를 이용하여 추출된 개별 코드를 개선된 퍼지 ART 알고리즘을 적용하여 인식한 방법보다 잡영 제거 알고리즘과 CDM 마스크를 적용하여 개선된 퍼지 ART 알고리즘으로 개별 코드를 인식하는 것이 효율적인 것을 확인하였다. 그리고 기존의 퍼지 ART 알고리즘을 이용하여 개별 코드를 인식하는 경우보다 본 논문에서 제안한 개선된 퍼지 ART 알고리즘을 이용하여 개별 코드를 인식하는 경우가 서로 다른 패턴들이 같은 클러스터로 분류되지 않아 인식 성능이 개선되었다.생산하고 있다. 또한 이러한 자료를 바탕으로 지역통계 수요에 즉각 대처할 수 있다. 더 나아가 이와 같은 통계는 전 국민에 대한 패널자료이기 때문에 통계적 활용의 범위가 방대하다. 특히 개인, 가구, 사업체 등 사회 활동의 주체들이 어떻게 변화하는지를 추적할 수 있는 자료를 생산함으로써 다양한 인과적 통계분석을 할 수 있다. 행정자료를 활용한 인구센서스의 이러한 특징은 국가의 교육정책, 노동정책, 복지정책 등 다양한 정책을 정확한 자료를 근거로 수립할 수 있는 기반을 제공한다(Gaasemyr, 1999). 이와 더불어 행정자료 기반의 인구센서스는 비용이 적게 드는 장점이 있다. 예를 들어 덴마크나 핀란드에서는 조사로 자료를 생산하던 때의 1/20 정도 비용으로 행정자료로 인구센서스의 모든 자료를 생산하고 있다. 특히, 최근 모든 행정자료들이 정보통신기술에 의해 데이터베이스 형태로 바뀌고, 인터넷을 근간으로 한 컴퓨터네트워크가 발달함에 따라 각 부처별로 행정을 위해 축적한 자료를 정보통신기술로 연계${cdot}$통합하면 막대한 조사비용을 들이지 않더라도 인구센서스자료를 적은 비용으로 생산할 수 있는 근간이 마련되었다. 이렇듯 행정자료 기반의 인구센서스가 많은 장점을 가졌지만, 그렇다고 모든 국가가 당장 행정자료로 인구센서스를 대체할 수 있는 것은 아니다. 행정자료로 인구센서스통계를 생산하기 위해서는 각 행정부서별로 사용하는 행정자료들을 연계${cdot}$통합할 수 있도록 국가사회전반에 걸쳐 행정 체제가 갖추어져야 하기 때문이다. 특히 모든 국민 개개인에 관한 기본정보, 개인들이 거주하며 생활하는 단위인 개별 주거단위에 관한 정보가 행정부에 등록되어

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.10
• /
• pp.447-454
• /
• 2015

This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.

• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1083-1093
• /
• 2021

It is an essential to predict water usage for establishing an optimal supply operation plan and reducing power consumption. However, the water usage by consumer has a non-linear characteristics due to various factors such as user type, usage pattern, and weather condition. Therefore, in order to predict the water consumption, we proposed the methodology linking various techniques that can consider non-linear characteristics of water use and we called it as KWD framework. Say, K-means (K) cluster analysis was performed to classify similar patterns according to usage of each individual consumer; then Wavelet (W) transform was applied to derive main periodic pattern of the usage by removing noise components; also, Deep (D) learning algorithm was used for trying to do learning of non-linear characteristics of water usage. The performance of a proposed framework or model was analyzed by comparing with the ARMA model, which is a linear time series model. As a result, the proposed model showed the correlation of 92% and ARMA model showed about 39%. Therefore, we had known that the performance of the proposed model was better than a linear time series model and KWD framework could be used for other nonlinear time series which has similar pattern with water usage. Therefore, if the KWD framework is used, it will be possible to accurately predict water usage and establish an optimal supply plan every the various event.