• Korean Journal of Remote Sensing
• /
• v.40 no.1
• /
• pp.103-114
• /
• 2024

The escalating demands for high-resolution satellite imagery necessitate the dissemination of geospatial data with superior accuracy.Achieving precise positioning is imperative for mitigating geometric distortions inherent in high-resolution satellite imagery. However, maintaining sub-pixel level accuracy poses significant challenges within the current technological landscape. This research introduces an approach wherein upsampling is employed on both the satellite image and ground control points (GCPs) chip, facilitating the establishment of a high-resolution satellite image precision sensor orientation. The ensuing analysis entails a comprehensive comparison of matching performance. To evaluate the proposed methodology, the Compact Advanced Satellite 500-1 (CAS500-1), boasting a resolution of 0.5 m, serves as the high-resolution satellite image. Correspondingly, GCP chips with resolutions of 0.25 m and 0.5 m are utilized for the South Korean and North Korean regions, respectively. Results from the experiment reveal that concurrent upsampling of satellite imagery and GCP chips enhances matching performance by up to 50% in comparison to the original resolution. Furthermore, the position error only improved with 2x upsampling. However,with 3x upsampling, the position error tended to increase. This study affirms that meticulous upsampling of high-resolution satellite imagery and GCP chips can yield sub-pixel-level positioning accuracy, thereby advancing the state-of-the-art in the field.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.29B no.8
• /
• pp.66-73
• /
• 1992

This paper proposes a new motion estimation algorithm which takes into account the rate-distortion relation in encoding motion compensated error images. The proposed algorithm is based on a new block-matching criterion which is the function of not only the mean squared block-matching error but also the code length for the entropy coded motion vector. The proposed algorithm optimizes the trade-off between the bit rate for motion compensated error images and the bit rate for the motion vectors. Simulation results show that in the motion compensated image coding the proposed motion estimator improves the overall performance by 0.5 dB when compared to the motion estimator which uses MSE only.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.8
• /
• pp.678-687
• /
• 2005

This paper describes a relative localization algorithm using odometry data and consecutive local maps. The purpose of this paper is the odometry error correction using the area matching of two consecutive local maps. The local map is built up using a sensor module with dual laser beams and USB camera. The range data form the sensor module is measured using the structured lighting technique (active stereo method). The advantage in using the sensor module is to be able to get a local map at once within the camera view angle. With this advantage, we propose the AVS (Aligned View Sector) matching algorithm for. correction of the pose error (translational and rotational error). In order to evaluate the proposed algorithm, experiments are performed in real environment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.29 no.7
• /
• pp.484-490
• /
• 2018

This paper describes an algorithm for calculating load impedance by measuring voltage and current components using a VI sensor in a 13.56 MHz impedance automatic matching system. We propose an algorithm that improves the error rate by using an arbitrary complex calibration load instead of the conventional $50{\Omega}$ calibration load. The error rate is targeted to attain average values of $R_{IN}$ and $X_{IN}$ at 1% and 20% or less, respectively. First, the IF frequency is calculated using a mixer to reduce the error rate. Second, when the arbitrary complex load is used as the calibration load, the error rate $R_{IN}$ decreased from 4.7 % to 0.3 % on average, and $X_{IN}$ decreased from 102 % to 18.3 % on average.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.3
• /
• pp.41-56
• /
• 2000

In this paper, we propose a two-stage fast block matching algorithm using the mean absolute error (MAE) of neighbor search point that can reduce the computational complexity to estimate motion vector while the motion estimation error performance is nearly the same as full search algorithm (FSA) In the proposed method, the lower bound of MAE 6at current search point IS calculated using the MAE of neighbor search point And we reduce the computational complexity by performing the block matching process only at the search point that has to be block matched using the lower bound of MAE The proposed algorithm is composed of two stages The experimental results show that the proposed method drastically reduces the computational complexity while the motion compensated error performance is nearly kept same as that of FSA.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_1
• /
• pp.907-917
• /
• 2019

Recently, the demand for high-resolution satellite images increases in many fields such as land monitoring and terrain analysis. Therefore, the need for geometric correction is increasing. As an automatic precision geometric correction method, there is a method of automatically extracting the GCP by matching between the GCP Chip and the satellite image. For automatic precision geometric correction, the success rate of matching GCP Chip and satellite image is important. Therefore, it is important to evaluate the matching performance of the manufactured GCP Chip. In order to evaluate the matching performance of GCP Chips, a total of 3,812 GCP Chips in South Korea were used as experimental data. The GCP Chip matching results of KOMPSAT-3A and Google Map showed similar matching results. Therefore, we determined that Google Map satellite imagery could replace high-resolution satellite imagery. Also, presented a method using center point and error radius of Google Map to reduce the time required to verify matching performance. As a result, it is best to set the optimum error radius to 8.5m. Evaluated the matching performance of GCP Chips in South Korea using Google Maps. And verified matching result using presented method. As a result, the GCP Chip s in South Korea had a matching success rate of about 94%. Also, the main matching failure factors were analyzed by matching failure GCP Chips. As a result, Except for GCP Chips that need to be remanufactured, the remaining GCP Chips can be used for the automatic geometric correction of satellite images.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.19 no.3
• /
• pp.11-25
• /
• 2009

Fingerprint sample quality is one of major factors influencing the matching performance of fingerprint recognition systems. The error rates of fingerprint recognition systems can be decreased significantly by removing poor quality fingerprints. The purpose of this paper is to assess the effectiveness of individual sample quality measures on the performance of minutiae-based fingerprint recognition algorithms. Initially, the authors examined the various factors that influenced the matching performance of the minutiae-based fingerprint recognition algorithms. Then, the existing measures for fingerprint sample quality were studied and the more effective quality measures were selected and compared with two image quality software packages, (NFIQ from NIST, and QualityCheck from Aware Inc.) in terms of matching performance of a commercial fingerprint matcher (Verifinger 5.0 from Neurotechnologija). The experimental results over various Fingerprint Verification Competition (FVC) datasets show that even a single sample quality measure can enhance the matching performance effectively.

• Journal of information and communication convergence engineering
• /
• v.9 no.6
• /
• pp.671-675
• /
• 2011

DVC (Distributed Video Coding) and FRUC (Frame Rate Up Conversion) techniques need to have an efficient motion compensated frame interpolation algorithms. Conventional works of these applications have mainly focused on the performance improvement of overall system. But, in some applications, it is necessary to evaluate how well the MCI (Motion Compensated Interpolation) frame matches the original frame. For this aim, this paper deals with the modeling methods for evaluating the block-based matching cost. First, several matching criteria, which have already been dealt with the motion compensated frame interpolation, are introduced and then combined to make estimate models for the size of MSE (Mean Square Error) noise of the MCI frame to original one. Through computer simulations, it is shown that the block-based matching criteria are evaluated and the proposed model can be effectively used for estimating the MSE noise.

• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.436-441
• /
• 2008

One of important factors in designing array-type MEMS resonators is obtaining a desired frequency response function (FRF) within a specific range. In this paper Krylov subspace-based model order reduction using moment-matching with non-zero expansion points is represented to calculate the FRF of array-type resonators. By matching moments at a frequency around a specific range of the array-type resonators, required FRFs can be efficiently calculated with significantly reduced systems regardless of their operating frequencies. In addition, because of the characteristics of moment-matching method, a minimal order of reduced system with a specified accuracy can be determined through an error indicator using successive reduced models, which is very useful to automate the order reduction process and FRF calculation for structural optimization iterations.

• Journal of Biomedical Engineering Research
• /
• v.17 no.3
• /
• pp.305-312
• /
• 1996

A new three dimensional fractal coding is proposed with a perceptually enhanced matching. Since most of medical images (e.g. computed tomoyaphy or magnetic resonance images) have three dimensional characters, searching regions are extended to adjacent slices. For a perceptually enhanced matching, a high frequency boost filter is used for pre-filtering images to be encoded, and a least mean square error matching is applied to the edge enhanced Images rather than the original images. From simulation with magnetic resonance images($255\times255$, 8bits/pixel), reconstructed images by the proposed compression algorithm show much improved subjective image quality with higher peak signnal-to-noise ratio compared to those by existing fractal coding algorithms at compression ratios of about 10.