• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.2
• /
• pp.63-73
• /
• 2011

The Pseudorange Corrections (PRC), which are used in DGPS as calibration messages, can contain outliers, noise, and anomalies, and these abnormal events are unpredictable. When those irregular PRC are used, the positioning error gets higher. In this paper, we propose a strategy of detecting and correcting outliers, noise, and anomalies by modeling the changing pattern of PRC through polynomial curve fitting techniques. To validate our strategy, we compared positioning errors obtained without PRC calibation with those with PRC calibration. As a result, we found that our algorithm performs very well; the horizontal RMS error was 3.84 m before the correction and 1.49 m after the correction.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2003.05a
• /
• pp.663-666
• /
• 2003

이 논문에서는 특징점 정보를 이용한 세선화 보정 알고리즘에 대하여 연구하였다. 세선화된 지문에서 교차수를 이용하여 추출된 특징점으로부터 세선화 보정을 수행하였다. 세선화 보정 과정은 특징점인 단점과 분기점을 시작점으로 하여 융선을 추적하면서 불필요한 융선을 제거해 나가는 방법으로 더 이상 제거할 융선이 없을 때까지 반복하여 처리한다. 세선화 보정이 끝나면 CN과 SN을 이용하여 특징점을 재추출하였다. 기존의 세선화된 지문으로부터 추출된 특징점과 제안한 세선화 보정 알고리즘으로부터 추출된 특징점을 비교하였다. 이 비교를 통하여 기존방법보다 세선화 지문이 개선되고 많은 의사 특징점들이 제거되었음을 알 수 있었다.

• Communications for Statistical Applications and Methods
• /
• v.18 no.3
• /
• pp.367-376
• /
• 2011

BLS weight adjustment is a widely used method for business surveys with non-responses and outliers. Recent surveys show that the non-response weight adjustment of the BLS method is the same as the ratio imputation method. In this paper, we suggested a modified BLS weight adjustment method by imputing missing values instead of using weight adjustment for non-response. Monthly labor survey data is used for a small Monte-Carlo simulation and we conclude that the suggested method is superior to the original BLS weight adjustment method.

• The Korean Journal of Applied Statistics
• /
• v.29 no.7
• /
• pp.1185-1199
• /
• 2016

Two phase sampling (double sampling) is often used when there is inadequate population information for proper stratification. Many recent papers have been devoted to the estimation method to improve the precision of the estimator using first phase information. In this study we suggested outlier weight adjustment methods to improve estimation precision based on the weight of the generalized ratio-cum-product estimator. Small simulation studies are conducted to compare the suggested methods and the usual method. Real data analysis is also performed.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2015.07a
• /
• pp.252-253
• /
• 2015

군중의 이상행동을 검출하는 것은 군중 모니터링, 보안 및 CRM 시스템의 관점에서 중요한 요소 중의 하나이다. 기존의 방법은 대다수가 옵티컬플로우를 기반으로한 검출방법으로 객체가 움직이지 않는 경우에는 객체로 인식할 수 없는 문제점이 생긴다. 또한, 많은 데이터량을 처리하기 때문에 실시간성이 보장되지 않는다는 단점이 있다. 이를 극복하기 위해서, 본 논문에서는 특징점 맵 보정과 분포분석을 통한 군중의 밀집과 대피하는 현상을 검출하는 방법을 제안한다. 먼저, 군중에서 옵티컬플로우 기반으로 움직이는 FAST 특징점을 추출하고 추출된 특징점의 분포에따라 특징점맵을 복원한다. 복원된 특징점 맵과 특징점의 분포에 기반하여 군중의 이상정도를 결정하게 된다. PETS2009 데이터베이스를 사용하여 결과를 측정하였다.

• The Korean Journal of Applied Statistics
• /
• v.26 no.4
• /
• pp.635-647
• /
• 2013

Imputation is a commonly used method to handle missing survey data. The performance of the imputation method is influenced by various factors, especially an outlier. The removal of the outlier in a data set is a simple and effective approach to reduce the effect of an outlier. In this paper in order to improve the precision of multiple imputation, we study a imputation method which reduces the effect of outlier using various weight adjustment methods that include the removal of an outlier method. The regression method in PROC/MI in SAS is used for multiple imputation and the obtained final adjusted weight is used as a weight variable to obtain the imputed values. Simulation studies compared the performance of various weight adjustment methods and Monthly Labor Statistic data is used for real data analysis.

• Proceedings of the KSEEG Conference
• /
• 2007.04a
• /
• pp.415-417
• /
• 2007

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.2
• /
• pp.281-287
• /
• 2010

This study compares transformation algorithms for co-registration of terrestrial laser scan data. Pair-wise transformation which is used for transformation of scan data from more than two different view accumulates errors. ICP algorithm commonly used for co-registration between scan data needs initial geometry information. And it is difficult to co-register simultaneously because of too many control points when managing scan at the same time. Therefore, this study perform global registration technique using matching points. Matching points are extracted automatically from intensity image by SIFT and global registration is performed using GP analysis. There are advantages for operation speed, accuracy, automation in suggested global registration algorithm. Through the result from it, registration algorithms can be developed by considering accuracy and speed.

• Proceedings of the Korean Information Science Society Conference
• /
• 2004.04b
• /
• pp.706-708
• /
• 2004

본 논문에서는 영상 시퀀스(image sequence)에서 얻은 특징점(feature point) 중 outlier를 제거 및 보정할 수 있는 방법을 제시한다. 영상 시퀀스가 주어졌을 때, 우리는 이 영상에서 특징점 추적(tracking)을 하여, 영상의 중요한 정보로 이용한다. 이러한 자동적으로 얻어낸 특징점 추적 데이터는 올바르지 못하게 추적 된 것이 있기 마련인데, 이렇게 올바르지 못한 데이터. 즉, outlier를 제거하기 위하여, 기존의 방법들은 trifocal tensor를 주로 사용하였다. 그러나 trifocal tensor 는 영상이 3장으로 제한되어 있다. 또한 outlier를 찾은 후에는 제 거 만 하게되어, 입력 데이터의 개수를 줄이게 되는 단점이 있다. 따라서, 우리는 triangulation방법을 이용하여, 3장 이상의 영상에서도, outlier의 제거와 보정이 동시에 가능한 방법을 제시한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.05a
• /
• pp.339-342
• /
• 2017

Geometric transform of an image is used to image correction. Ridid-Body, Simlilary transform, etc, many correction methods are exist in computer vision. Image warping is used to correction for image with perspective. To image warping I extracted 4 feature point about warping position. But It is difficult to extract 4 points accurately and warping result with these point is occurs error over 3 or 4 pixel at warping position. So I used template matching to extract 4 points correctly and selected repeatedly 2 points of 4 points because to confirm result correctly. positions of 2 points are changed in near of 3 by 3 pixel and warped each change. So I selected optimal 4 points with a error of less than 1 pixel and finally, warped image using optimal points. For this way is possible to obtain optimum result.