• Journal of Korea Society of Industrial Information Systems
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• v.18 no.4
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• pp.53-60
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• 2013

We propose a method for improving detection speed of small target detection system using SAD algorithm. First, the proposed method deletes clutters using a median filter. Next, it does closing and opening operation using various size of structure elements, and extracts candidate pixels for a target with subtraction operation between the results of closing and opening operation. It finally detects a small target using a gaussian distance function from the candidate pixels. To improve detection speed, it detects a target performing SAD algorithm only for the predicted target areas for next every 7 frames. The proposed method not only enables a real time process because it considers only predicted area but also shows detecting rate of 97%.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.111-125
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• 2015

In this study, the target detection using both high-resolution satellite SAR and Elecro-Optical (EO) images such as TerraSAR-X and WorldView-2 is performed, considering the characteristics of targets. The targets of our interest are featured by being stationary and appearing as cluster targets. After the target detection of SAR image by using Constant False Alarm Rate (CFAR) algorithm, a series of processes is performed in order to reduce false alarms, including pixel clustering, network clustering and coherence analysis. We extend further our algorithm by adopting the fast and effective ellipse detection in EO image using randomized hough transform, which is significantly reducing the number of false alarms. The performance of proposed algorithm has been tested and analyzed on TerraSAR-X SAR and WordView-2 EO images. As a result, the average false alarm for group of targets is 1.8 groups/$64km^2$ and the false alarms of single target range from 0.03 to 0.3 targets/$km^2$. The results show that groups of targets are successfully identified with very low false alarms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.9
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• pp.736-743
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• 2013

In IRST(infrared search and track) system, the small target detection is very difficult because the IR(infrared) image have various clutter and sensor noise. The noise and clutter similar to the target intensity value produce many false alarms. In this paper. We propose the adaptive detection method which obtains optimal target detection using the image intensity information and the prior information of target. In order to enhance the target, we apply the human visual system. we determine the adaptive threshold value using image intensity and distance measure in target enhancement image. The experimental results indicate that the proposed method can efficiently extract target region in various IR images.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.2
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• pp.1-13
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• 2017

In This Paper, we find the Target Candidate Region and the Location of the Candidate Region by Performing the Morphological Difference Calculation and Pixel Labeling for Robust Small Target Detection in Infrared Image with low SNR. Conventional Target Detection Methods based on Morphology Algorithms are low in Detection Accuracy due to their Vulnerability to Clutter in Infrared Images. To Address the Problem, Target Signal Enhancement and Background Clutter Suppression are Achieved Simultaneously by Combining Moravec Algorithm and LCM (Local Contrast Measure) Algorithm to Classify the Target and Noise in the Candidate Region. In Addition, the Proposed Algorithm can Efficiently Detect Multiple Targets by Solving the Problem of Limited Detection of a Single Target in the Target Detection method using the Morphology Operation and the Gaussian Distance Function Which were Developed for Real time Target Detection.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.3
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• pp.1-8
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• 2000

In this paper, we formulate an optimal control problem to obtain the optimal signal strength and detection threshold for tracking with NN filter, First, we predict the tracking performance of NN filter by using the HYCA method. Based on this method, the predicted tracking performance is represented with respect to signal strength and detection threshold. Using this relation, we find the optimal parameters for following three examples： 1) the sequence of optimal detection threshold which minimizes sum of position estimation error； 2) the sequence of optimal detection threshold which minimizes sum of validation gate volume； and 3) the sequence of optimal signal strength and detection threshold which minimizes sum of signal strength.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.4
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• pp.61-70
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• 2012

We propose a method that finds candidate targets based on morphology and detects a small target from them using modified gaussian distance function. The existing small target detection methods use predictive filters or morphology. The methods using predictive filters take long to approach least errors. The methods using morphology are weak at clutters and need to consider size of a small target when selecting size of structure elements. We propose a robust method for small target detection to complete the existing methods. First, the proposed method deletes clutters using a median filter. Next, it does closing and opening operation using various size of structure elements, and figures target candidate pixels with subtraction operation between the results of closing and opening operation. It detects an exact small target using a gaussian distance function from the candidates target areas. The proposed method is less sensitive to clutters, and shows a detection rate of 98%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.179-186
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• 2015

This paper proposes the target path detection algorithm using statistical characteristics of an activated time lag along a moving path of target from a neighboring sensor in PDR(Pulse Doppler Radar) sensor node environment based on USN(Ubiquitous Sensor Network) with a limitation detecting only an existence of moving target. In the proposed algorithm, detection and non-detection time lag obtained from the experimental data are used. The experimental data are through repetitive action of each 500 times about three path scenarios such as passing in between two sensors, moving parallel to two sensors, and turning through two sensors. From this experiments, error detection percentages of three path scenarios are 5.67%, 5.83%, and 7.17%, respectively. They show that the proposed algorithm can exactly detect a target path using the limited PDR sensor nodes.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.114-125
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• 2014

In a conventional sonar system, which uses LFM signal for detecting targets with varying speed, the results of multiple LFM Doppler correlators are aligned and the maximum alined result are selected as a test cell for detecting targets. As the number of the LFM Doppler correlators are increased for accurate target detection, as the required computational complexity and the memory are also increased. This fact makes it difficult to implement the accurate LFM target detector. In this paper, we propose a new fast target detection which is robust for the variation of target speed. Because the proposed method uses the summation of alined results of large numbers of LFM Doppler correlators, the proposed method increase SNR and provide robust SNR for the variation of target speed. And the proposed method can provide very fast target detection by implementing the process, the summation of alined results of large numbers of LFM Doppler correlators, as one summation filter.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.665-671
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• 2010

This paper propose the DDEGST(divergent-direction-emphasis generalized symmetry transform) which emphasis the symmetry of divergent intensity orientation for effective target extraction in FLIR(forward looking infra-red) images. In the proposed method, we use the exponential function instead of cosine function as a phase weight function in the generalized symmetry transform for effective target extraction in FLIR images which contain a target with higher intensity than a background intensity. To evaluate the performance of the proposed method, we compare the proposed mehtod with conventional GST method in experiments. We prove that the proposed method have better performance in IR images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1593-1600
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• 1999

This paper describes the acquisition modeling of an airborne target for target tracking simulation of infrared homing missiles. The modeling, of which key technologies are the sub-modeling for target infrared signature, atmospheric transmission, and receiver characteristics, shows the acquisition process of an airborne target under various tracking conditions determined by line-of-sight, distance, and atmospheric conditions. We confirm the validity of the modeling by applying it to simulations concerned with target tracking. The modeling gives a guideline to determine an optimum detector and a defection band for effective discrimination of the target among false targets.