• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.16-23
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• 2011

Muzzle flash based on gunnery is the target that has huge energy. So, gunnery target in a long range over xx km is distinguishable in the IR(infrared) images, on the other hand, is not distinguishable in the CCD images. In this paper, we propose the classification method of gunnery targets in a infrared images and in a long range. The energy from gunnery have an effect on varous pixel values in infrared images as a property of infrared image sensor, distance, and atmosphere, etc. For this reason, it is difficult to classify gunnery targets using pixel values in infrared images. In proposed method, we take the profile of pixel values using high performance infrared sensor, and classify gunnery targets using modeling GMM and shape of profile. we experiment on the proposed method with infrared images in the ground and aviation. In experimental result, the proposed method provides about 93% classification rate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.712-715
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• 2011

When simulate long distance infrared image in the laboratory the Infrared Refractive Collimator is used. In this case, infrared light reflected from the surface of the lens and target. The reflected infrared light causes Narcissus. Narcissus degrades the quality of the infrared image. To minimize Narcissus optimize the reflective index and placement of the lenses, lenses and target surface coated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1464-1480
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• 2019

Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.699-701
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• 2017

Typical operating method for long-range observation cameras are to detect the target at a wide angle of view and to recognize/identify the target with a telephoto angle of view. And the detection/recognition range performance is an important item to evaluate the performance of the defense infrared camera. To increased the detection range performance, the camera's field of view should be narrowed. Due to the narrow field of view, the probability of finding target is relatively low. In this paper, we propose a method to search for target by providing a wide angle view while maintaining detection range performance. M&S and optimized design were used to develop infrared camera with extended field of view and the results of the test summarized.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.63-73
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• 2021

This paper presents a algorithm for automatic target recognition robust to the influence of the flame in order to track the target by EOTS(Electro-Optical Targeting System) equipped on UAV(Unmanned Aerial Vehicle) when there is aerial target or marine target with flame at the same time. The proposed method converts infrared images of targets and flames into a gradient vector field, and applies each gradient magnitude to a polynomial curve fitting technique to extract polynomial coefficients, and learns them in a shallow neural network model to automatically recognize targets and flames. The performance of the proposed technique was confirmed by utilizing the various infrared image database of the target and flame. Using this algorithm, it can be applied to areas where collision avoidance, forest fire detection, automatic detection and recognition of targets in the air and sea during automatic flight of unmanned aircraft.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.3
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• pp.248-253
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• 2014

Camera calibration is an indispensable process for improving measurement accuracy in industry fields such as machine vision. However, existing calibration cannot be applied to the calibration of mid-wave and long-wave infrared cameras. Recently, with the growing use of infrared thermal cameras that can measure defects from thermal properties, development of an applicable calibration target has become necessary. Thus, based on heat conduction analysis using finite element analysis, we developed a calibration target that can be used with both existing visible cameras and infrared thermal cameras, by implementing optimal design conditions, with consideration of factors such as thermal conductivity and emissivity, colors and materials. We performed comparative experiments on calibration target images from infrared thermal cameras and visible cameras. The results demonstrated the effectiveness of the proposed calibration target.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.1-7
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• 2018

In this paper, we propose soft dead pixels detection method by analysing different response at hot and cold images. Abnormal pixels are able to effect detecting a small target. It also makes confusing real target or not cause of changing target size. Almost exist abnormal pixels after image signal processing even if dead pixels are removed by dead pixel compensation are called soft dead pixels. They are showed defect in final image. So removing or compensating dead pixels are very important for detecting object. The key idea of this proposed method, detecting dead pixels, is that most of soft deads have different response characteristics between hot image and cold image. General infrared cameras do NUC to remove FPN. Working 2-reference NUC must be needed getting data, hot & cold images. The way which is proposed dead pixel detection is that we compare response, NUC gain, at each pixel about two different temperature images and find out dead pixels if the pixels exceed threshold about average gain of around pixels.

• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.11
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• pp.898-905
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• 2018

In this work, infrared targets for a developed hardware-in-the-loop simulation(HILS) system are proposed for a performance test of a dual-sensor imaging seeker equipped with an infrared and a visible sensor that can lock and track for ground and air targets. This integrated system is composed of 100 modules of heat and light sources to simulate various kinds of target and the trajectory of moving targets based on scenarios. It is possible to simulate not only the position, velocity, and direction for these targets but also background clutter and jamming environments. The design and measurement results of an infrared target, such as the HILS system configuration, developed for testing and evaluation of a dual-sensor imaging seeker are described. In the future, it is planned to test the lock-on and tracking performance of an imaging seeker equipped with single or dual sensors dynamically in real time based on a simulation flight scenario in the developed HILS system.

• Journal of the Optical Society of Korea
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• v.18 no.1
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• pp.1-8
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• 2014

Spin reticle infrared seekers have good linearity, and the pulse-modulated reticle seekers have good digital characteristics for anti-jamming processing. A basic design for a spin pulse-modulated reticle is introduced. This design uses the rotating design of the optical system in the spin infrared seekers and an improved design of the reticle in the pulse-modulated seekers. The reticle contains a unique well-designed slit to produce one pulse for each target in the spinning period. The target data will be carried by the unique pulse parameters. A simulation tool is implemented using the MATLAB packages for analyzing and evaluating the new design.