• Title/Summary/Keyword: Ground truth

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High Accuracy Vision-Based Positioning Method at an Intersection

  • Manh, Cuong Nguyen;Lee, Jaesung
    • Journal of information and communication convergence engineering
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    • v.16 no.2
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    • pp.114-124
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    • 2018
  • This paper illustrates a vision-based vehicle positioning method at an intersection to support the C-ITS. It removes the minor shadow that causes the merging problem by simply eliminating the fractional parts of a quotient image. In order to separate the occlusion, it firstly performs the distance transform to analyze the contents of the single foreground object to find seeds, each of which represents one vehicle. Then, it applies the watershed to find the natural border of two cars. In addition, a general vehicle model and the corresponding space estimation method are proposed. For performance evaluation, the corresponding ground truth data are read and compared with the vision-based detected data. In addition, two criteria, IOU and DEER, are defined to measure the accuracy of the extracted data. The evaluation result shows that the average value of IOU is 0.65 with the hit ratio of 97%. It also shows that the average value of DEER is 0.0467, which means the positioning error is 32.7 centimeters.

The Effects of JPEG2000 Compression on Automated DSM Generation

  • Shih, Tian-Yuan;Liu, Jung-Kuan
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.997-999
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    • 2003
  • The effects of JPEG2000 compression on automated DSM extraction by using the area-based matching are evaluated in this paper. The influences on DSM heights obtained via PCI Geomatics OrthoEngine module are investigated using a single stereo model of 1:5,000 scale aerial photography at image resolution of 20 ${\mu}$m. The experiment design of elevation errors are computed for a range of compression rates from 2:1 to about 100:1, and the DSM which generated from uncompressed image is used as ‘ground truth’ data for comparison. The experimental results show that the standard deviation ranged from 0.9m to 2.5m with the compression ratio from 2 to 100. It is also observed that there is no significant degradation on DSM accuracy up to the compression ratio of 33.

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Detection of Individual Tree Stands by a Fusion of a Multispectral High-resolution Satellite Image and Laser Scanning Data

  • Teraoka, Masaki;Setojima, Masahiro;Imai, Yasuteru;Yasuoka, Yoshifumi
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1042-1044
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    • 2003
  • A methodology of the integrating the similar color circle search of the spectral data and segmentation of the height data is developed. The method is then applied to study areas, and the results by IKONOS, LIDAR and data fusion are verified with the ground truth, and examined in terms of the accuracy. Results show that with the data fusion the accuracy are improved by about 15% in most of the study areas. The methodology for the detection of individual tree stands by data fusion is explored, and the utility of combinatorial use of the spectral and the height information is demonstrated.

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Assessing Sea Surface Temperature in the Yellow Sea Using Satellite Remote Sensing Data

  • Lee, Kyoo-seock;Kang, Hee-Sook
    • Korean Journal of Remote Sensing
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    • v.6 no.1
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    • pp.39-47
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    • 1990
  • The first Marine Observation Satellite(MOS) was launched by National Space Development Agency of Japan on February 19, 1987, and it is equipped with three sensons covering visible, infrared, and microwave region. One of them is Visible and Thermal Infrared Radiometer(VTIR) whose main objective is to detect the Sea Surface Temperature(SST). The objective of this study was to process the MOS data using Cray-2 supercomputer, and to assess the SST in the Yellow Sea. In order to implement this objective, the linear regression model between the ground truth data and the corresponding digital number of VTIR in MOS was used to establish the relationship. After testing the significance of the regression model, the SST map of the whole Yellow Sea was derived based on the model. The digital SST map representing the study area showed certain pattern about the SST of Yellow Sea in March and April. In conclusion, the VTIR data in MOS is also useful in investigating SST which provides the information about the Yellow Sea water current in the spring.

Biotop Mapping Using High-Resolution Satellite Remote Sensing Data, GIS and GPS

  • Shin Dong-Hoon;Lee Kyoo-Seock
    • Korean Journal of Remote Sensing
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    • v.20 no.5
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    • pp.329-335
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    • 2004
  • Biotop map can be utilized for nature conservation and assessment of environmental impact for human activities in urban area. High resolution satellite images such as IKONOS and KOMPSAT1-EOC were interpreted to classify land use, hydrology, impermeable pavement ratio and vegetation for biotop mapping. Wildlife habitat map and detailed vegetation map obtained from former study results were used as ground truth data. Vegetation was investigated directly for the area where the detailed vegetation map is not available. All these maps were combined and the boundaries were delineated to produce the biotop map. Within the boundary, the characteristics of each polygon were identified, and named. This study investigates the possibility of biotop mapping using high resolution satellite remote sensing data together with field data with the goal of contributing to nature conservation in urban area.

Fuzzy Training Based on Segmentation Using Spatial Region Growing

  • Lee Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.20 no.5
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    • pp.353-359
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    • 2004
  • This study proposes an approach to unsupervisedly estimate the number of classes and the parameters of defining the classes in order to train the classifier. In the proposed method, the image is segmented using a spatial region growing based on hierarchical clustering, and fuzzy training is then employed to find the sample classes that well represent the ground truth. For cluster validation, this approach iteratively estimates the class-parameters in the fuzzy training for the sample classes and continuously computes the log-likelihood ratio of two consecutive class-numbers. The maximum ratio rule is applied to determine the optimal number of classes. The experimental results show that the new scheme proposed in this study could be used to select the regions with different characteristics existed on the scene of observed image as an alternative of field survey that is so expensive.

Radar Measurement of Slow Deformation in the Baekdusan Stratovolcano

  • Kim, Sang-Wan;Won , Joong-Sun
    • Korean Journal of Remote Sensing
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    • v.21 no.3
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    • pp.221-228
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    • 2005
  • Baekdusan is a Cenozoic stratovolcano in which a series of micro-seismic events and gaseous emissions have been reported in 1990s. Two-pass DInSAR technique was applied to determine displacement in the volcano by using 10 ERS SAR and 41 JERS-1 SAR datasets. Most interferometric phases out of 58 JERS-1 differential interferograms showed concentric fringe patterns that correlated with elevation. From an analysis of fringe-duration relation, the fringe patterns were found to be severely distorted specifically by stratified troposphere. To estimate the tropospheric delay, we used the data in the Sobaeksan located about 20 km away from the summit of Baekdusan. The maximum and mean magnitudes of the phase delay in the Baekdusan were respectively 13.8 cm and 3.8 cm over 1200 m in altitude. After removing tropospheric effects, a mean inflation rate was estimated to be about 3 mm per year from 1992 to 1998. Although the inflation rate of the volcano is inconclusive without ground truth data, the results indicate that there exists slow upward deformation in the Baekdusan volcano.

An Approach to the Spectral Signature Analysis and Supervised Classification for Forest Damages - An Assessment of Low Altitued Airborne MSS Data -

  • Kim, Choen
    • Korean Journal of Remote Sensing
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    • v.7 no.2
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    • pp.149-163
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    • 1991
  • This paper discusses the capabilities of airborne remotely sensed data to detect and classify forest damades. In this work the AMS (Aircraft Multiband Scanner) was used to obtain digital imagery at 300m altitude for forest damage inventory in the Black Forest of Germany. MSS(Multispectral Scanner) digital numbers were converted to spectral emittance and radiance values in 8 spectral bands from the visible to the thermal infrared and submitted to a maximum-likelihood classification for : (1) tree species ; and. (2) damage classes. As expected, the resulted, the results of MSS data with high spatial resolution 0.75m$\times$0.75m enabled the detection and identification of single trees with different damages and were nearly equivalent to the truth information of ground checked data.

An Efficient Rectification Algorithm for Spaceborne SAR Imagery Using Polynomial Model

  • Kim, Man-Jo
    • Korean Journal of Remote Sensing
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    • v.19 no.5
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    • pp.363-370
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    • 2003
  • This paper describes a rectification procedure that relies on a polynomial model derived from the imaging geometry without loss of accuracy. By using polynomial model, one can effectively eliminate the iterative process to find an image pixel corresponding to each output grid point. With the imaging geometry and ephemeris data, a geo-location polynomial can be constructed from grid points that are produced by solving three equations simultaneously. And, in order to correct the local distortions induced by the geometry and terrain height, a distortion model has been incorporated in the procedure, which is a function of incidence angle and height at each pixel position. With this function, it is straightforward to calculate the pixel displacement due to distortions and then pixels are assigned to the output grid by re-sampling the displaced pixels. Most of the necessary information for the construction of polynomial model is available in the leader file and some can be derived from others. For validation, sample images of ERS-l PRI and Radarsat-l SGF have been processed by the proposed method and evaluated against ground truth acquired from 1:25,000 topography maps.

Box Feature Estimation from LiDAR Point Cluster using Maximum Likelihood Method (최대우도법을 이용한 라이다 포인트군집의 박스특징 추정)

  • Kim, Jongho;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.13 no.4
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    • pp.123-128
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    • 2021
  • This paper present box feature estimation from LiDAR point cluster using maximum likelihood Method. Previous LiDAR tracking method for autonomous driving shows high accuracy about velocity and heading of point cluster. However, Assuming the average position of a point cluster as the vehicle position has a lower accuracy than ground truth. Therefore, the box feature estimation algorithm to improve position accuracy of autonomous driving perception consists of two procedures. Firstly, proposed algorithm calculates vehicle candidate position based on relative position of point cluster. Secondly, to reflect the features of the point cluster in estimation, the likelihood of the particle scattered around the candidate position is used. The proposed estimation method has been implemented in robot operating system (ROS) environment, and investigated via simulation and actual vehicle test. The test result show that proposed cluster position estimation enhances perception and path planning performance in autonomous driving.