• Korean Journal of Remote Sensing
• /
• v.38 no.3
• /
• pp.283-298
• /
• 2022

As Synthetic Aperture Radar (SAR) image can be acquired regardless of the weather and day or night, it is highly recommended to be used for Automatic Target Recognition (ATR) in the fields of surveillance, reconnaissance, and national security. However, there are some limitations in terms of cost and operation to build various and vast amounts of target images for the SAR-ATR system. Recently, interest in the development of an ATR system based on simulated SAR images using a target model is increasing. Attributed Scattering Center (ASC) matching and template matching mainly used in SAR-ATR are applied to target classification. The method based on ASC matching was developed by World View Vector (WVV) feature reconstruction and Weighted Bipartite Graph Matching (WBGM). The template matching was carried out by calculating the correlation coefficient between two simulated images reconstructed with adjacent points to each other. For the performance analysis of the two proposed methods, the Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset was used, which has been recently published by the U.S. Defense Advanced Research Projects Agency (DARPA). We conducted experiments under standard operating conditions, partial target occlusion, and random occlusion. The performance of the ASC matching is generally superior to that of the template matching. Under the standard operating condition, the average recognition rate of the ASC matching is 85.1%, and the rate of the template matching is 74.4%. Also, the ASC matching has less performance variation across 10 targets. The ASC matching performed about 10% higher than the template matching according to the amount of target partial occlusion, and even with 60% random occlusion, the recognition rate was 73.4%.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.3044-3046
• /
• 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
• /
• v.6 no.3
• /
• pp.413-423
• /
• 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.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.17 no.3
• /
• pp.364-377
• /
• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.12
• /
• pp.659-666
• /
• 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.

• Proceedings of the Korean Institute of Communication Sciences Conference
• /
• 1987.04a
• /
• pp.60-66
• /
• 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.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.25 no.1
• /
• pp.63-71
• /
• 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.

• Phonetics and Speech Sciences
• /
• v.4 no.4
• /
• pp.139-146
• /
• 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)
• /
• v.17 no.6
• /
• pp.1635-1656
• /
• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.3
• /
• pp.9-16
• /
• 2018

The media facade technique requires the matching process of the content to the projection target. For this reason, each time the projection target is changed, the matching process of the same content must be performed again at each time. This problem can be solved by analyzing the elevation of the object and automatically performing matching process of the content in real time and projecting the matched content. In this paper, we propose and implement a new algorithm that can obtain the optimized matching content in real time by analyzing the elevation of the object to be projected. The proposed method processes the image matching by using the depth information of the elevation obtained by IR cameras.