• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.511-514
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• 2003

The Infrared Camera usually detects only Infrared waves emitted from the light in order to illustrate the temperature distribution. An Infrared diagnosis system can be applied to various fields. But the defect discrimination can be automatic or mechanized in the special shoes total inspection system. This study introduces a method for special shoes nondestructive total inspection. Performance of the proposed method is shown through thermo-Image.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.6
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• pp.14-21
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• 2003

With the increased use of lasers in industrial welding applications, techniques for monitoring and controlling these processes become increasingly important. It is very important that we understand the dynamic behaviors of the laser induced Plume in welding, because the laser induced plume has considerable effects on welding efficiency and the quality of materials. As the plume fluctuation was associated with keyhole instability, unstable vapor plume indicated the process was unstable and would result in poor welds. An Infrared Thermal-vision Camera can be utilized compensate for incurracies encountered in real-time monitoring during laser welding. We have results that instabilities of plume are closely related with hot cracking and defect of laser welding.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.125-130
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• 2001

Diagnosis or measurements using Infrared thermo-image hasn t been available. A quick diagnosis and thermal analysis can be possible when that kind of system is introduced to the investigation of each part. In this study, Infrared Camera, Thermo-vision 900 was used in order to investigate. Infrared Camera usually detects only Infrared wave from the light in order to illustrate the temperature distribution. Infrared diagnosis system can be applied to various field. Also, it is more effective to analyze temperature distribution on the machining center main-axis process.

• 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 the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.106-117
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• 2016

Recently, solar power plants have spread widely as part of the transition to greater environmental protection and renewable energy. Therefore, regular solar plant inspection is necessary to efficiently manage solar-light modules. This study implemented a test that can detect solar-light module faults using an UAV based thermal infrared camera and GIS spatial analysis. First, images were taken using fixed UAV and an RGB camera, then orthomosaic images were created using Pix4D SW. We constructed solar-light module layers from the orthomosaic images and inputted the module layer code. Rubber covers were installed in the solar-light module to detect solar-light module faults. The mean temperature of each solar-light module can be calculated using the Zonalmean function based on temperature information from the UAV thermal camera and solar-light module layer. Finally, locations of solar-light modules of more than $37^{\circ}C$ and those with rubber covers can be extracted automatically using GIS spatial analysis and analyzed specifically using the solar-light module's identifying code.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1354-1359
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• 2008

In this paper, we propose a vision based passenger monitoring system for passenger's safety in railway station. Since 2005, Korea Railroad Research Institute (KRRI) has developed a vision based monitoring system, funded by Korean government, for passenger's safety in railway station. The proposed system uses various types of sensors, such as, stereo camera, thermal-camera and infrared sensor, in order to detects danger situations in platform area. Especially, detection process of the system exploits the stereo vision algorithm to improve detection accuracy. The paper describes the overall system configuration and proposed detection algorithm, and then verifies the system performance with extensive experimental results in a real station environment.

• 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 Korean Society of Manufacturing Technology Engineers
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• v.18 no.3
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• pp.285-293
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• 2009

Thermal infrared cameras have been conducted actively in various application areas, such as military, medical service, industries and cars. Because of their characteristic of sensing the radiant heat emitted from subjects in the range of long-wavelength($3{\sim}5{\mu}m$ or $8{\sim}12{\mu}m$), and of materializing a vision system, when general optics materials are used, they don't react to the light in the range of long-wavelength, and can't display their optic functions. Therefore, the materials with the feature of higher refractive index, reacting to the range of long-wavelength, are to be used. The kinds of materials with the characteristic of higher refractive index are limited, and their features are close to those of metals. Because of these metallic features, the existing producing method of optical systems were direct manufacturing method using grinding method or CAD/CAM, which put limit on productivity and made it difficult to properly cope with the increasing demand of markets. GASIR, a material, which can be molded easily, was selected among infrared ray optics materials in this study, and the optical system was designed with two Aspheric lenses. Because the lenses are molded in the environment of high temperature and high pressure, they require a special metallic pattern. The metallic pattern was produced with materials with ultra hardness that can stand high temperature and high pressure. As for the lens mold, GMP(Glass Molding Press) of the linear transfer method was used in order to improve the productivity of optical systems for thermal infrared cameras, which was the goal of this paper.

• Smart Structures and Systems
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• v.33 no.1
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.