• 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.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.05a
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• pp.511-514
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• 2005

Recently, to obtain the reliable data on the state of the structure, various non-destructive techniques are available. The infrared thermography technique is used in detection of cracks, flaws of concrete structures and buildings. In this paper the infrared thermography technique using the difference of surface temperature was studied. Also this paper is case study that the inspection of building's tile using infrared thermal video.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.396-403
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• 2000

A thermal imaging system is implemented for the measurement and the analysis of the thermal distribution of the target objects. The main part of the system is a thermal camera in which a focal plane array typed sensor is introduced. The sensor detects the mid-range infrared spectrum of target objects and then it outputs a generic video signal which should be processed to form a frame thermal image. Here, a digital signal processor(DSP) is applied for the high speed processing of the sensor signals. The DSP controls analog-to-digital converter, performs correction algorithms and outputs the frame thermal data to frame buffers. With the frame buffers can be generated a NTSC signal and transferred the frame data to personal computer(PC) for the analysis and a monitoring of the thermal scenes. By performing the signal processing functions in the DSP the overall system achieves a simple configuration. Several experimental results indicate the performance of the overall system.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.91-96
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• 2014

This paper proposed an adaptive threshold method for detecting flame candidate regions in a infrared image and it adapts according to the contrast and intensity changes in the image. Conventional flame detection systems uses fixed threshold method since surveillance environment does not change, once the system installed. But it needs a adaptive threshold method as requirements of surveillance system has changed. The proposed adaptive threshold algorithm uses the dynamic behavior of flame as featured parameter. The test result is analysed by comparing test result of proposed adaptive threshold algorithm and conventional fixed threshold method. The analysed data shows, the proposed method has 91.42% of correct detection rate and false detection is reduced by 20% comparing to the conventional method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.1 no.2
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• pp.27-31
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• 2000

Thermal imaging system is implemented for the measurement and the analysis of the thermal distribution of the target objects. The main Part of the system is thermal camera in which a focal plane array typed sensor is introduced The sensor detects mid-range infrared spectrum or target objects and then it output generic video signal which should be processed to form a thermal image frame. A digital signal processor(DSP) in the system inputs analog to digital converted data. performs algorithms to improve the thermal images and then outputs the corrected frame data to frame buffers for NTSC encoding and for digital outputs.. To enhance the quality of the thermal images, two point correction method is applied. Figures indicate that the corrected thermal images are much improved.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.738-747
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• 2021

Today, with the improvement of deep learning technology, computer vision areas such as image classification, object detection, object segmentation, and object tracking have shown remarkable improvements. Various applications such as intelligent surveillance, robots, Internet of Things, and autonomous vehicles in combination with deep learning technology are being applied to actual industries. Accordingly, the requirement of an efficient compression method for video data is necessary for machine consumption as well as for human consumption. In this paper, we propose an object-based compression of thermal infrared images for machine vision. The input image is divided into object and background parts based on the object detection results to achieve efficient image compression and high neural network performance. The separated images are encoded in different compression ratios. The experimental result shows that the proposed method has superior compression efficiency with a maximum BD-rate value of -19.83% to the whole image compression done with VVC.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.33-37
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• 2011

This paper presents the frequency spectral analysis based on FFT of the infrared ray fire thermal image, it is an object to deduce the conditions for determining fire alarm through the image processing with the frequency domain. After the candidate regions are separated by using pre-defined brightness value, the fast fourier transform is performed for consecutive infrared thermal images, the frequency spectral analysis of the thermal image analyzed DC and AC frequency distribution. The fire criterion of the thermal image was presented based on the analyzed result and a practicality was confirmed through the computer simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3475-3489
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• 2014

Here we present a simple flame detection method for an infrared (IR) thermal camera based real-time fire surveillance digital signal processor (DSP) system. Infrared thermal cameras are especially advantageous for unattended fire surveillance. All-weather monitoring is possible, regardless of illumination and climate conditions, and the data quantity to be processed is one-third that of color videos. Conventional IR camera-based fire detection methods used mainly pixel-based temporal correlation functions. In the temporal correlation function-based methods, temporal changes in pixel intensity generated by the irregular motion and spreading of the flame pixels are measured using correlation functions. The correlation values of non-flame regions are uniform, but the flame regions have irregular temporal correlation values. To satisfy the requirement of early detection, all fire detection techniques should be practically applied within a very short period of time. The conventional pixel-based correlation function is computationally intensive. In this paper, we propose an IR camera-based simple flame detection algorithm optimized with a compact embedded DSP system to achieve early detection. To reduce the computational load, block-based calculations are used to select the candidate flame region and measure the temporal motion of flames. These functions are used together to obtain the early flame detection algorithm. The proposed simple algorithm was tested to verify the required function and performance in real-time using IR test videos and a real-time DSP system. The findings indicated that the system detected the flames within 5 to 20 seconds, and had a correct flame detection ratio of 100% with an acceptable false detection ratio in video sequence level.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.2
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• pp.85-90
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• 2010

The infrared energy is emitted in the infrared wavelength range that corresponds to the surface temperature of a object which has temperature that is over the absolute the temperature(OK). The infrared thermography (IRT) is a non-destrnctive testing method that provides thermal video for the user in real-time by converting the infrared quantity that is detected by the infrared detector into temperature. The pipes of nuclear power plant(NPP) could be thinned by the corrosion and fatigue and the defect could lead to a big accident. For this reason, the effective non-destructive testing method is necessary. In this study, the relationship between the measured temperature and the defect depth or size of NPP pipes were recognized and that was applied to detect the wall thinning defects of NPP pipes.

• Journal of Satellite, Information and Communications
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• v.8 no.4
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• pp.100-104
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• 2013

In this paper, we present an optimal threshold setting method for flame detection of infrared thermal image. Conventional infrared flame detection methods used fixed intensity threshold to segment candidate flame regions and further processing is performed to decide correct flame detection. So flame region segmentation step using the threshold is important processing for fire detection algorithm. The threshold should be change in input image depends on camera types and operation conditions. We have analyzed the conventional thresholds composed of fixed-intensity, average, standard deviation, maximum value. Finally, we extracted that the optimal threshold value is more than summation of average and standard deviation, and less than maximum value. it will be enhance flame detection rate than conventional fixed-threshold method.