• 대한원격탐사학회지
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• 제38권3호
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• pp.283-298
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• 2022

Synthetic Aperture Radar (SAR)영상은 날씨와 주야에 관계없이 취득될 수 있어 감시, 정찰 및 국토안보 등의 목적을 위한 자동표적인식(Automatic Target Recognition, ATR)에 활용 가능성이 높다. 그러나, 식별 시스템 개발을 위해 다양하고 방대한 양의 시험영상을 구축하는 것은 비용, 운용측면에서 한계가 있다. 최근 표적 모델을 이용하여 시뮬레이션된 SAR 영상에 기반한 표적 식별 시스템 개발에 대한 관심이 높아지고 있다. SAR-ATR 분야에서 대표적으로 이용되는 산란점 매칭과 템플릿 매칭 기반 알고리즘을 적용하여 표적식별을 수행하였다. 먼저 산란점 매칭 기반의 식별은 점을 World View Vector (WVV)로 재구성 후 Weighted Bipartite Graph Matching (WBGM)을 수행하였고, 템플릿 매칭을 통한 식별은 서로 인접한 산란점으로 재구성한 두 영상간의 상관계수를 사용하였다. 개발한 두 알고리즘의 식별성능시험을 위해 최근 미국 Defense Advanced Research Projects Agency (DARPA)에서 배포한 표적 시뮬레이션 영상인 Synthetic and Measured Paired Labeled Experiment (SAMPLE) 자료를 사용하였다. 표준 환경, 표적의 부분 폐색, 랜덤 폐색 정도에 따른 알고리즘 성능을 분석하였다. 산란점 매칭 알고리즘의 식별 성능이 템플릿 매칭보다 전반적으로 우수하였다. 10개 표적을 대상으로 표준환경에서의 산란점 매칭기반 평균 식별률은 85.1%, 템플릿 매칭기반은 74.4%이며, 표적별 식별성능 편차 또한 산란점 매칭기법이 템플릿 매칭기법보다 작았다. 표적의 부분 폐색정도에 따른 성능은 산란점 매칭기반 알고리즘이 템플릿 매칭보다 약 10% 높고, 표적의 랜덤 폐색 60% 발생에도 식별률이 73.4% 정도로 비교적 높은 식별성능을 보였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.3044-3046
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• 2000

A Stereo matching has been an important tool for reconstructing three dimensional terrain. In this stereo matching process, DEM(Digitai Elevation Map) can be generated by the disparity from reference image to target image. Generally disparity map in matching process can be implemented by wraping from reference image to target image and if the role of reference and target is interchanged, the different DEM can be obtained. To evaluate the generated DEM from matching process, We adapted the Photorealistic synthetic image generator using ray tracing technique. The generator produce two simulated image from previous DEM and Ortho-image which is regard as Ground-truth. In this paper, we are concern about estimating more accurate DEM from these two DEMs. The several fusion methods of two DEMs are proposed to generate accurate DEM and compared with previous method. one of fusion methods is by using Cross-Correlation match score and the true DEM should have a high matching score.

• International Journal of Control, Automation, and Systems
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• 제6권3호
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• pp.413-423
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• 2008

The template matching method is used as a simple method to track objects or patterns that we want to search for in the input image data from image sensors. It recognizes a segment with the highest correlation as a target. The concept of this method is similar to that of SNF (Strongest Neighbor Filter) that regards the measurement with the highest signal intensity as target-originated among other measurements. The SNF assumes that the strongest neighbor (SN) measurement in the validation gate originates from the target of interest and the SNF utilizes the SN in the update step of a standard Kalman filter (SKF). The SNF is widely used along with the nearest neighbor filter (NNF), due to computational simplicity in spite of its inconsistency of handling the SN as if it is the true target. Probabilistic Strongest Neighbor Filter for m validated measurements (PSNF-m) accounts for the probability that the SN in the validation gate originates from the target while the SNF assumes at any time that the SN measurement is target-originated. It is known that the PSNF-m is superior to the SNF in performance at a cost of increased computational load. In this paper, we suggest an image tracking algorithm that combines the template matching and the PSNF-m to estimate the states of a tracked target. Computer simulation results are included to demonstrate the performance of the proposed algorithm in comparison with other algorithms.

• 한국군사과학기술학회지
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• 제17권3호
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• pp.364-377
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• 2014

In this paper, we have developed a target recognition algorithm based on a template matching technique using Synthetic Aperture Radar (SAR) images. For efficient computations, Radon transform-based azimuth estimation algorithm was used with the template matching. MSTAR data set was divided into two groups according to the depression angles, which were a train set and a test set. Template data were generated by rotating and cropping chips which were from MSTAR train set using the azimuth estimation algorithm. Then the template matching process between test data and template data was performed under various conditions. Performance variation according to contrast enhancement preprocessing which is scarce in open literature was also presented. The analysis results show that the target recognition algorithm could be useful for the automatic target recognition using SAR images.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권12호
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• pp.659-666
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• 2000

A stereo matching has been an important tool for reconstructing three dimensional terrain. By using stereo matching technique, DEM(Digital Elevaton Map) can be generated by the disparity from a reference image to a target image. Generally disparity map can be evaluated by matching the reference image to the target image and if the role of the reference and the target are interchanged, a different DEM can be obtained. In this paper, we propose a new fusion technique to estimate the optimal DEM by eliminating the false DEM due to occlusion. To detect the false DEM, we utilize two measure of accuracy: self-consistency and cross-correlation score. We test the effectiveness of the proposed methods with a quantitative analysis using simulated images. Experimental result indicate that the proposed methods show 24.4% and 33.1% improvement over either DEM.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1987년도 춘계학술발표회 논문집
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• pp.60-66
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• 1987

In this paper a fast matching method using subtemplate and search and down technique to reduce very heavy computational load of the conventional matching method, is presented The proposed method is spplied to an automatic target tracker in order to track one moving object in comparatively simple backgoriund. Experimental results show that istperformanced is not so degraded in spite of high computational reduction as that of the conventional matching method.

• 대한전자공학회논문지
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• 제25권1호
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• pp.63-71
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• 1988

In this paper, a fast matching method using hierarchical neighborhood search and subtemplate to reduce very heavy computational load of the conventional matching method, is presented. Some parameters of the proposed method are chosen so that an automatic target tracker to which it is applied can track one moving object well in comparatively simple background. Experimental results show that its performance is not so degraded in spite of high computational reduction over that of the matching method using 3-step search.

• 말소리와 음성과학
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• 제4권4호
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• pp.139-146
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• 2012

This study was designed to examine comfort levels of pitch and loudness with target matching and their effects on electroglottographic (EGG) and acoustic measures. Twelve speakers, six males and six females, were instructed to produce /a/ sustained vowel for three seconds at a comfortable pitch and loudness level without any instruction and with a target matching procedure of either a certain f0 or SPL separately with visual and auditory feedback. The range of pitch for females and males were presented by progressing up and down randomly at intervals of 5Hz from 150 Hz to 310 Hz (total 33 frequency targets) and from 85 Hz to 190 Hz (total 22 frequency targets), respectively. The loudness levels were 65, 75, 85, 95 dB (total of four intensity targets) for both males and females. Subjective estimations of comfortable levels were obtained using a 10-point equal-appearing interval rating scale following each phonation. The results showed that males and females demonstrated similar trends in loudness levels with greatest comfort at 75 dB, whereas pitch comfort ratings showed a greater variability with females having a wider range with target matching. In the comfort levels of individuals, most male and female speakers rated higher comfort at soft, rather than loud phonations. On the other hand, most male speakers perceived highest comfort levels below the comfort pitch levels they phonated under natural conditions. Higher frequency ranges, however, were perceived to be more comfortable than those of natural condition in most female speakers, although the comfortable pitch levels in spontaneous phonations were within the comfort level ranges determined by targeted phonations. When comparing acoustic (%jitter, %shimmer, SNR) and EGG measures (CQ%) between spontaneous comfortable phonations and targeted phonations produced by the same subject at similar f0 and intensity, no significant differences were observed (p>0.05). Thus, target matching procedures may be considered a compatible and alternative method to reduce the variability of comfortable pitch and loudness levels by eliciting consistent comfortable phonations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권6호
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• pp.1635-1656
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• 2023

In Bayesian multi-target tracking, the Poisson multi-Bernoulli mixture (PMBM) filter is a state-of-the-art filter based on the methodology of random finite set which is a conjugate prior composed of Poisson point process (PPP) and multi-Bernoulli mixture (MBM). In order to improve the random finite set-based filter utilized in multi-target tracking of sensor scanning, this paper introduces the Poisson multi-Bernoulli mixture filter into time-matching Bayesian filtering framework and derive a tractable and principled method, namely: the time-matching Poisson multi-Bernoulli mixture (TM-PMBM) filter. We also provide the Gaussian mixture implementation of the TM-PMBM filter for linear-Gaussian dynamic and measurement models. Subsequently, we compare the performance of the TM-PMBM filter with other RFS filters based on time-matching method with different birth models under directional continuous scanning and out-of-order discontinuous scanning. The results of simulation demonstrate that the proposed filter not only can effectively reduce the influence of sampling time diversity, but also improve the estimated accuracy of target state along with cardinality.

• 한국인터넷방송통신학회논문지
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• 제18권3호
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• pp.9-16
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• 2018

미디어파사드 기술은 투사할 대상의 입면(立面, elevation)에 정합처리가 된 콘텐츠를 필요로 한다. 이런 이유로 투사될 대상체가 바뀔 때마다 같은 콘텐츠라도 정합처리를 매번 다시 수행해 주어야 한다. 이런 문제점은 투사 대상체의 입면을 분석하여 콘텐츠를 실시간으로 자동 정합 처리하여 투사하는 방법으로 해결 가능하다. 그러나 아직까지 콘텐츠의 실시간 매핑에 대해서는 뚜렷하고 획기적인 연구결과를 찾기 어렵기 때문에 새로운 연구가 반드시 필요하다. 본 논문에서는 투사될 대상의 입면정보를 분석하여 최적화된 투사영상을 실시간으로 얻을 수 있는 새로운 알고리즘을 제안하고 구현한다. 제안된 방법은 IR카메라를 이용하여 얻어지는 입면의 깊이정보를 이용하여 영상 정합을 실시간 처리한다.