• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.550-558
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• 2013

The infrared and visible images are represented by different information due to the different wavelength of the light. The infrared image has thermal information and the visible image has texture information. Desirable results are obtained by fusing infrared and visible information. To enhance a visible image, we extract a weight map from a visible image using saturation, brightness. After that, the weight map is adjusted using thermal information in the infrared image. Finally, an enhanced image is resulted from combining an infrared image and a visible image. Our experiment results show that our proposed algorithm is working well to enhance the smoke in the original image.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.437-443
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• 2015

This paper presents face recognition based on the fusion of visible image and thermal infrared (IR) texture estimated from the face image in the visible spectrum. The proposed face recognition scheme uses a multi- layer neural network to estimate thermal texture from visible imagery. In the training process, a set of visible and thermal IR image pairs are used to determine the parameters of the neural network to learn a complex mapping from a visible image to its thermal texture in the low-dimensional feature space. The trained neural network estimates the principal components of the thermal texture corresponding to the input visible image. Extensive experiments on face recognition were performed using two popular face recognition algorithms, Eigenfaces and Fisherfaces for NIST/Equinox database for benchmarking. The fusion of visible image and thermal IR texture demonstrated improved face recognition accuracies over conventional face recognition in terms of receiver operating characteristics (ROC) as well as first matching performances.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.51-56
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• 2016

This paper proposes a new image enhancement method for an infrared thermal image. The proposed method uses both Laplacian and Prewitt edge detectors. Without a visible light, it uses an infrared image for the edge detection. The method subtracts contour images from the infrared thermal image. It results black contours of objects in the infrared thermal image. That makes the objects in the infrared thermal image distinguished clearly. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using various infrared thermal images. The results show that the proposed method is successful for image enhancement of an infrared thermal image.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.707-713
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• 2021

Symptoms of foot-and-mouth disease include fever and drooling a lot around the hoof, blisters in the mouth, poor appetite, blisters around the hoof, and blisters around the hoof. Research is underway on smart barns that remotely manage these symptoms through cameras. Visible light cameras can measure the condition of livestock such as blisters, but cannot measure body temperature. On the other hand, infrared thermal imaging cameras can measure body temperature, but it is difficult to measure the condition of livestock. In this paper, we propose an object detection system using deep learning-based livestock detection using visible and infrared thermal imaging composite camera modules for preemptive response

• Journal of Sensor Science and Technology
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• v.9 no.1
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• pp.44-50
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• 2000

Every object emits some energy from its surface. The emission energy forms surface heat distribution which we can capture by using an infrared thermal imager. The infrared thermal image may include valuable information regarding to the subsurface anomaly of the object. Since a thermal image reflects surface clutter and subsurface anomaly, we have difficulty in extracting the information on the subsurface anomaly only with thermal images taken under a wavelength. Thus, we use visible wavelength images of the object surface to remove exterior clutter. We, therefore in this paper, visualize the infrared image for overlaying it with a visible wavelength image. First, we make an interpolated image from two ordinary images taken from both sides of an infrared sensor. Next, we overlay the intermediate image with an infrared image taken from the infrared camera. The technique suggested in this paper can be utilized for analyzing the infrared images on non-destructive inspection against disaster and for safety.

• Journal of Sensor Science and Technology
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• v.27 no.5
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• pp.300-305
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• 2018

The uncooled microbolometer thermal sensor for low cost and mass volume was designed to target the new infrared market that includes smart device, automotive, energy management, and so on. The microbolometer sensor features 80x60 pixels low-resolution format and enables the use of wafer-level vacuum packaging (WLVP) technology. Read-out IC (ROIC) implements infrared signal detection and offset correction for fixed pattern noise (FPN) using an internal digital to analog convertor (DAC) value control function. A reliable WLVP thermal sensor was obtained with the design of lid wafer, the formation of Au80%wtSn20% eutectic solder, outgassing control and wafer to wafer bonding condition. The measurement of thermal conductance enables us to inspect the internal atmosphere condition of WLVP microbolometer sensor. The difference between the measurement value and design one is $3.6{\times}10-9$ [W/K] which indicates that thermal loss is mainly on account of floating legs. The mean time to failure (MTTF) of a WLVP thermal sensor is estimated to be about 10.2 years with a confidence level of 95 %. Reliability tests such as high temperature/low temperature, bump, vibration, etc. were also conducted. Devices were found to work properly after accelerated stress tests. A thermal camera with visible camera was developed. The thermal camera is available for non-contact temperature measurement providing an image that merged the thermal image and the visible image.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1203-1209
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• 2011

In this paper, the degradation evaluation method of VLC (Visible Light Communication) wireless module after high dose rate gamma-ray irradiation using the thermal infrared camera is proposed. First, the heating characteristics of the active devices embedded in the VLC wireless module during the condition of normal operation is monitored by thermal infrared camera. By the image processing technique, the trends of the intensity of the heat emitted by the active devices are calculated and stored. The feature of the blob area including the area of the active devices in the thermal infrared image is extracted and stored. The feature used in this paper is the mean value of the gray levels in the blob area. The same VLC module has been gamma irradiated at the dose rate of about 4.0 kGy/h during 72 hours up to a total dose of 288 kGy. And then, the heating characteristics of the active devices embedded in the VLC wireless module after high dose gamma ray irradiation is observed by thermal infrared camera. The high dose gamma-ray induced degradation of the active devices embedded in the VLC module was evaluated by comparing the mean value of the blob area to the one of the same blob area of the VLC module before the gamma ray irradiation.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.48-52
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• 2023

Many studies have been conducted to ensure that Visual Place Recognition is reliable in various environments, including edge cases. However, existing approaches use visible imaging sensors, RGB cameras, which are greatly influenced by illumination changes, as is widely known. Thus, in this paper, we use an invisible imaging sensor, a long wave length infrared camera (LWIR) instead of RGB, that is shown to be more reliable in low-light and highly noisy conditions. In addition, although the camera sensor used to solve this problem is an LWIR camera, but since the thermal image is converted into RGB image the proposed method is highly compatible with existing algorithms and databases. We demonstrate that the proposed method outperforms the baseline method by about 0.19 for recall performance.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.71-91
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• 2018

In recent years, application of UAV(Unmanned Aerial Vehicle) to seed sowing and pest control has been actively carried out in the field of agriculture. In this study, UAS(Unmanned Aerial System) is constructed by combining image sensor of various wavelength band and SfM((Structure from Motion) based image analysis technique in UAV. Utilization of UAS based vegetation survey was investigated and the applicability of precision farming was examined. For this purposes, a UAS consisting of a combination of a VIS_RGB(Visible Red, Green, and Blue) image sensor, a modified BG_NIR(Blue Green_Near Infrared Red) image sensor, and a TIR(Thermal Infrared Red) sensor with a wide bandwidth of $7.5{\mu}m$ to $13.5{\mu}m$ was constructed for a low cost UAV. In addition, a total of ten vegetation indices were selected to investigate the chlorophyll, nitrogen and water contents of plants with visible, near infrared, and infrared wavelength's image sensors. The images of each wavelength band for the test area were analyzed and the correlation between the distribution of vegetation index and the vegetation index were compared with status of the previously surveyed vegetation and ground cover. The ability to perform vegetation state detection using images obtained by mounting multiple image sensors on low cost UAV was investigated. As the utility of UAS equipped with VIS_RGB, BG_NIR and TIR image sensors on the low cost UAV has proven to be more economical and efficient than previous vegetation survey methods that depend on satellites and aerial images, is expected to be used in areas such as precision agriculture, water and forest research.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07a
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• pp.191-194
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• 2003

Through using aspheric lens can result in advantages such as an improved optical transfer function, a reduced distortion path or the realization of special image field curvatures. Using the diamond turning method for generating aspherics, the company claim to be able to generate surfaces with a form error of less than $0.33\;{\mu}\;m$ and a surface roughness of less than $0.025\;{\mu}\;m$. In this paper, we are manufacturing thermal image aspheric lens. Thermal image system is electro-optical imaging device which can make visible the difference of infrared energy naturally emitted by objected. In the result of aspherical surface, the form accuracy of about $0.24\;{\mu}\;m$ P-V was obtained and the surface roughness Ra $0.004\;{\mu}\;m$. Also, a brief review of Ultra-precision system Korea photonics technology institute(KOPTI) is present in this paper.