• 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 Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1503-1508
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• 2009

This study applied image processing techniques, constructed to real-time, to thermal infrared camera image. Thermal infrared image data was utilized for hot mapping, cool mapping, and rainbow mapping according to changing temperature. It was histogram image processing techniques so that detected shade contrast function of the thermal infrared image, and the thermal infrared image's edge was extracted to classification of object. Moreover, extraction of temperature from image was measured by using the image information program.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.3
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• pp.288-293
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• 2016

Electronic Image Stabilization(EIS) is widely used as a technique for correcting a shake of an image. The case requiring the EIS function has been increased in high magnification thermal image observation on portable military equipment. Projection Algorithm(PA) for EIS is easy to implement but its performance is sensitive to the projection area. Especially, projection profiles of thermal image have very modest change and are difficult to extract image shifts between frames. In this paper, we proposed algorithm to extract a feature image for the thermal image and compared Block Matching Algorithm(BMA) with PA using our proposed feature image. When using our proposed feature image, BMA was simply implemented using FPGA's internal small memory. And we were able to obtain 30 % PSNR improved results compared to PA.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.711-714
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• 2002

Thermal infrared camera have poor image qualities compared to commercial CCD cameras, as in contrast, brightness, and. resolution. To compensate the poor Image quality problems associated with the thermal infrared camera, the technique of superimposing thermal infrared image into real ccd image is proposed. The mobile robot KAEROT/m2, loaded with sensor head system at the mast, is entered to monitor leakage of heavy water and thermal abnormality of the calandria reactor area in overhaul period. The sensor head system is composed of thermal infrared camera and cod camera In parallel. When thermal abnormality on observation points and areas of calandria reactor area is occurred, unusual hot image taken from thermal infrared camera is superimposed on real CCD image. In this inspection experiment, more accurate positions of thermal abnormalities on calandria reactor area can be estimated by using technique of mapping thermal infrared image into CCD image, which include characters arranged in MPOQ order.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.1
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• pp.41-53
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• 2017

A thermal camera is used to obtain thermal information of a certain area. However, it is difficult to depict all the information of an area in an individual thermal image. To form a high-resolution panoramic thermal image, we propose an optimized FAST (feature from accelerated segment test) algorithm to combine two or more images of the same scene. The FAST is an accurate and fast algorithm that yields good positional accuracy and high point reliability; however, the major limitation of a FAST detector is that multiple features are detected adjacent to one another and the interest points cannot be obtained under no significant difference in thermal images. Our proposed algorithm not only detects the features in thermal images easily, but also takes advantage of the speed of the FAST algorithm. Quantitative evaluation shows that our proposed technique is time-efficient and accurate. Finally, we create a mosaic of the video to analyze a comprehensive view of the scene.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.5
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• pp.533-538
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• 2015

Thermal characterization of individual pixels in microbolometer infrared image sensors is needed for optimal design and improved performance. In this work, we used thermoreflectance microscopy on uncooled microbolometer image sensors to investigate the thermal characteristics of individual pixels. Two types of microbolometer image sensors with a shared-anchor structure were fabricated and thermally characterized at various biases and vacuum levels by measuring the temperature distribution on the surface of the microbolometers. The results show that thermoreflectance microscopy can be a useful thermal characterization tool for microbolometer image sensors.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.19-26
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• 2017

In this paper, we propose an efficient image equipment implementation for the detector characteristics of various detectors by analyzing un-cooled thermal detector that exhibits nonlinear changes due to external temperature effects. First, we explain Thermal Electric Cooler for un-cooled detector temperature control system and Non-image correction methode for IR system. Second, we present the results of a study on an efficient control technique that can minimize the deterioration of image quality by controlling a un-cooled thermal detector without a thermal electric cooler(TEC) inside. Third, we suggest Image Correction Methods for Uncooled IR TECless Detector with Non-linear characteristics due to Temperature Change. So, we analyze and present the results of Image correction methods for various un-cooled thermal detector.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.9-12
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• 2010

This paper presents design and implementation of infrared thermal image processing system based on the digital media processor for disaster monitoring. The digital thermal image processing board is designed and implemented by using commercial chips such as DM642 processor and video encoder, video decoder. The implemented functions for disaster monitoring are to analyze temperature distribution of a monitoring infrared thermal image and to detect disaster situation such as fire. For the input of infrared thermal image processing system, an infrared camera of type of the $320\;{\times}\;240\;{\mu}$-bolometer is used. The required functions are confirmed with 10 frame/second of processing performance by testing of the prototype and Practicality of the system was verified.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.30-38
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• 2021

In this paper, we propose a method for extracting thermal data from thermal image and improving detection of heating equipment using the data. The main goal is to read the data in bytes from the thermal image file to extract the thermal data and the real image, and to apply the composite image obtained by synthesizing the image and data to the deep learning model to improve the detection accuracy of the heating facility. Data of KHNP was used for evaluation data, and Faster-RCNN is used as a learning model to compare and evaluate deep learning detection performance according to each data group. The proposed method improved on average by 0.17 compared to the existing method in average precision evaluation.As a result, this study attempted to combine national data-based thermal image data and deep learning detection to improve effective data utilization.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.2
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• pp.97-103
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• 2017

Thermal imaging is mainly used in military equipment required for night observation. In particular, technologies of uncooled thermal imaging detectors are being developed as applied to low-cost night observation system. Many system integrators require different specifications of the uncooled thermal imaging camera but their development time is short. In this approach, EOSYSTEM has developed a small size, TEC-less uncooled thermal imaging camera module with $32{\times}32mm$ size and low power consumption. Both domestic detector and import detector are applied to the EOSYSTEM's thermal imaging camera module. The camera module contains efficient infrared image processing algorithms including : Temperature compensation non-uniformity correction, Bad/Dead pixel replacement, Column noise removal, Contrast/Edge enhancement algorithms providing stable and low residual non-uniformity infrared image.