• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.25-33
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• 2009

In the paper, we proposed a new system to retrieve 3D wrinkle data based on stereo images. Usually, 3D reconstruction based on stereo images or video is very popular and it is the research focus, which has been applied for culture heritage, building and other scene. The target is object measurement, the scene depth calculation and 3D data obtained. There are several challenges in our research. First, it is hard to take the full information wrinkle images by cameras because of light influence, skin with non-rigid object and camera performance. We design a particular computer vision system to take winkle images with a long length camera lens. Second, it is difficult to get the dense stereo data because of the hard skin texture image segmentation and corner detection. We focus on semi-dense stereo matching algorithm for the wrinkle depth. Compared with the 3D scanner, our system is much cheaper and compared with the physical modeling based method, our system is more flexible with high performance.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.83-90
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• 2023

Blurred image is an important factor in lowering image recognition rates in Computer vision. This mainly occurs when the camera is unstablely out of focus or the object in the scene moves quickly during the exposure time. Blurred images greatly degrade visual quality, weakening visibility, and this phenomenon occurs frequently despite the continuous development digital camera technology. In this paper, it replace the modified building module based on the Deep multi-patch neural network designed with convolution neural networks to capture details of input images and Attention techniques to focus on objects in blurred images in many ways and strengthen the image. It measures and assigns each weight at different scales to differentiate the blurring of change and restores from rough to fine levels of the image to adjust both global and local region sequentially. Through this method, it show excellent results that recover degraded image quality, extract efficient object detection and features, and complement color constancy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.137-147
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• 2023

LiDAR is used in autonomous driving and various industrial fields to measure the size and distance of an object. In addition, the sensor also provides intensity images based on the amount of reflected light. This has a positive effect on sensor data processing by providing information on the shape of the object. LiDAR guarantees higher performance as the resolution increases but at an increased cost. These conditions also apply to LiDAR intensity images. Expensive equipment is essential to acquire high-resolution LiDAR intensity images. This study developed artificial intelligence to improve low-resolution LiDAR intensity images into high-resolution ones. Therefore, this study performed parameter analysis for the optimal super-resolution neural network model. The super-resolution algorithm was trained and verified using 2,500 LiDAR intensity images. As a result, the resolution of the intensity images were improved. These results can be applied to the autonomous driving field and help improve driving environment recognition and obstacle detection performance

• Fire Science and Engineering
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• v.24 no.2
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• pp.178-184
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• 2010

In this study, a smoke or a heat which occurs by a fire is perceived by wireless detector, this signal is transmitted to the receiving device by the wireless installation which is not the wire device and wire/wireless integration system which sends this signal to main server via wire system is proposed. In addition wireless heat/smoke detector, wireless module, firmware and wire/wireless integration controller were developed and for verifying regarding the efficiency and applicability of wire/wireless installation actual place application experiment was really accomplished with a transmission tower, a multipurpose building, and a station etc of the subway. The experimental result, it could operate the system which is proposed normally with all experimental object ones and, future actual place application possibility could verify.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.84-86
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• 2010

Time information and time synchronization are fundamental building blocks in wireless sensor networks since many sensor network applications need time information for object tracking, consistent state updates, duplicate detection and temporal order delivery. Various time synchronization protocols have been proposed for sensor networks because of the characteristics of sensor networks which have limited computing power and resources. However, none of these protocols have been designed with time representation scheme in mind. Global time format such as UTC TOD (Universal Time Coordinated, Time Of Day) is very useful in sensor network applications. In this paper we propose time keeping and synchronization method for global time presentation in wireless sensor networks.

• Current Optics and Photonics
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• v.6 no.4
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• pp.381-391
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• 2022

Two-photon-polymerization additive-manufacturing systems feature high resolution and precision. However, there are few reports on specific methods and possible problems concerning the use of small lasers to independently build such platforms. In this paper, a femtosecond-laser two-photon-polymerization additive-manufacturing system containing an optical unit, control unit, monitoring unit, and testing unit is built using a miniature femtosecond laser, with a detailed building process and corresponding control software that is developed independently. This system has integrated functions of light-spot detection, interface searching, micro-/nanomanufacturing, and performance testing. In addition, possible problems in the processes of platform establishment, resin preparation, and actual polymerization for two-photon-polymerization additive manufacturing are explained specifically, and the causes of these problems analyzed. Moreover, the impacts of different power levels and scanning speeds on the degree of polymerization are compared, and the influence of the magnification of the object lens on the linewidth is analyzed in detail. A qualitative analysis model is established, and the concepts of the threshold broadening and focus narrowing effects are proposed, with their influences and cooperative relation discussed. Besides, a linear structure with micrometer accuracy is manufactured at the millimeter scale.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.689-697
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• 2023

Purpose: The purpose of this study is to automatically extract information on underground facilities using a general-purpose smartphone in the process of applying the mini-trenching method. Method: Data sets for image learning were collected under various conditions such as day and night, height, and angle, and the object detection algorithm used the R-CNN algorithm. Result: As a result of the study, F1-Score was applied as a performance evaluation index that can consider the average of accurate predictions and reproduction rates at the same time, and F1-Score was 0.76. Conclusion: The results of this study showed that it was possible to extract information on underground buried materials based on smartphones, but it is necessary to improve the precision and accuracy of the algorithm through additional securing of learning data and on-site demonstration.

• Journal of the Korean Wood Science and Technology
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• v.38 no.6
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• pp.518-525
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• 2010

Infrared (IR) thermography which is the technique for detecting invisible infrared light emitted by objects due to their surface thermal condition and for producing an image of the light has been applied in various field without damaging the objects. It also could be used indirectly to examine the inside of an object. In this study, insulation property of wooden house in Korea Forest Research Institute (KFRI) was evaluated with according to "Thermal performance of building - Quantitative detection of thermal irregularities in building envelopes - infrared method (KS F 2829)". This method uses "Temperature Difference Ratio (TDR)" between outdoor wall surface and indoor wall surface of wooden building for evaluating its thermal performance. The thermal performance of a room on the 2nd floor of the wooden house was focused in this study and IR thermography on the indoor and outdoor surface of the house was captured by IR camera. Heat loss from the corner and the window of the wooden house as well as wall of the house was quantitatively evaluated and the invisible heat loss in the wall was detected. It is expected that the results from this study could contribute to improve the wooden building energy efficiency.

• Journal of the HCI Society of Korea
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• v.2 no.2
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• pp.35-43
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• 2007

This paper presents a system for image matching and recognition based on image feature detection and description techniques from artificial satellite photographs. We propose some kind of parameters from the varied environmental elements happen by image handling process. The essential point of this experiment is analyzes that affects match rate and recognition accuracy when to change of state of each parameter. The proposed system is basically inspired by Lowe's SIFT(Scale-Invariant Transform Feature) algorithm. The descriptors extracted from local affine invariant regions are saved into database, which are defined by k-means performed on the 128-dimensional descriptor vectors on an artificial satellite photographs from Google earth. And then, a label is attached to each cluster of the feature database and acts as guidance for an appeared building's information in the scene from camera. This experiment shows the various parameters and compares the affected results by changing parameters for the process of image matching and recognition. Finally, the implementation and the experimental results for several requests are shown.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.251-256
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• 2021

Unlike general cameras, a high-speed camera capable of capturing a large number of frames per second can enable the advancement of some image processing technologies that have been limited so far. This paper proposes a method of removing undesirable noise from an high-speed input color image, and then detecting a human face from the noise-free image. In this paper, noise pixels included in the ultrafast input image are first removed by applying a bidirectional filter. Then, using RetinaFace, a region representing the person's personal information is robustly detected from the image where noise was removed. The experimental results show that the described algorithm removes noise from the input image and then robustly detects a human face using the generated model. The model-based face-detection method presented in this paper is expected to be used as basic technology for many practical application fields related to image processing and pattern recognition, such as indoor and outdoor building monitoring, door opening and closing management, and mobile biometric authentication.