• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1376-1382
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• 2016

In this paper, we present a visual quality enhancement technique for conventional three-dimensional (3D) photon counting integral imaging using background noise removal algorithm. Photon counting imaging can detect a few photons from desired objects and visualize them under severely photon-starved conditions such as low light level environment. However, when a lot of photons are generated from background, it is difficult to detect photons from desired objects. Thus, the visual quality of the reconstructed image may be degraded. Therefore, in this paper, we propose a new photon counting imaging method that removes unnecessary background noise and detects photons from only desired objects. In addition, integral imaging can be used to obtain 3D information and visualize the 3D image by statistical estimations such as maximum likelihood estimation. To prove and evaluate our proposed method, we implement the optical experiment and calculate mean square error.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.583-588
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• 2015

Flexible tactile sensors can provide valuable feedback to intelligent robots regarding the environment around them. This is especially important when robots such as, service robots share a workspace with humans. This paper presents a contact force measurement algorithm of a flexible tactile sensor. This sensor is manufactured by a direct-writing technique, which is one 3D printing method, using multi-walled carbon nano-tubes. An analog signal processing circuit has been designed and implemented to reduce noise contained in the sensor output. In addition, a digital version of the Butterworth filter was implemented by software running on a microcontroller. Through various experiments, characteristics of the sensor system have been identified. Based on three traits, an algorithm to detect the contact and measure the contact force has been developed. The entire system showed a promising prospect to detect the contact over a large and curved area.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1697-1704
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• 2018

As a key component of lighting location system (LLS) for lightning warning, the atmospheric electric field measuring is required to have high accuracy. The Conventional methods of the existent electric field measurement meter can only detect the vertical component of the atmospheric electric field, which cannot acquire the realistic electric field in the thunderstorm. This paper proposed a three dimensional (3D) electric field system for atmospheric electric field measurement, which is capable of three orthogonal directions in X, Y, Z, measuring. By analyzing the relationship between the electric field and the relative permittivity of ground surface, the permittivity is calculated, and an efficiency 3D measurement model is derived. On this basis, a three-dimensional electric field sensor and a permittivity sensor are adopted to detect the spatial electric field. Moreover, the elevation and azimuth of the detected target are calculated, which reveal the location information of the target. Experimental results show that the proposed 3D electric field meter has satisfactory sensitivity to the three components of electric field. Additionally, several observation results in the fair and thunderstorm weather have been presented.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.67-76
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• 1997

In radar signal processing, an A/D converter with sufficient dynamic range and high sampling speed is required to detect the weakest target signals in heavy clutter and ECM environments. As the sampling frequency increases, the amount of digital data transfered to the signal processing module is also increased. To overcome these massive data transfer burden, we need an A/D conversion module with an enough data transfer rate. In this paper, we proposed an implementation scheme of a new A/D conversio module that can be used in multi-mode 3-D phased array radar signal processing system, and evaluated the performance. The proposed A/D conversion module is implemented with a standard A/D converter and a 6U-standard VME bus.

• Journal of the Korean Society of Hazard Mitigation
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• v.5 no.2 s.17
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• pp.1-8
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• 2005

Microwave tomographic imaging technology using a bi-focusing operator has been developed in order to detect the internal voids/objects inside concrete structures. The imaging system consists of several cylindrical or planar array antennas for transmitting and receiving signals, and a numerical focusing operator is applied to the external signals both in transmitting and in receiving fields. In this study, the authors developed 3-dimensional (3D) electromagnetic (EM) imaging technology to detect such damage and to identify exact location of steel rebars or dowel. The authors have developed sub-surface two-dimensional (2D) imaging technique using tomographic antenna array in previous works. In this study, extending the earlier analytical and experimental works on 2D image reconstruction, a 3D microwave imaging system using tomographic antenna way was developed, and multi-frequency technique was applied to improve quality of the reconstructed image and to reduce background noises. Numerical simulation demonstrated that a sub-surface image can be successfully reconstructed by using the proposed tomographic imaging technology. For the experimental verification, a prototype antenna array was fabricated and tested on a concrete specimen.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.800-816
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• 2018

In recent years, video surveillance research has been able to recognize various behaviors of pedestrians and analyze the overall situation of objects by combining image analysis technology and deep learning method. Human Activity Recognition (HAR), which is important issue in video surveillance research, is a field to detect abnormal behavior of pedestrians in CCTV environment. In order to recognize human behavior, it is necessary to detect the human in the image and to estimate the pose from the detected human. In this paper, we propose a novel approach for 2D Human Pose Estimation based on object detection using RGB-D information. By adding depth information to the RGB information that has some limitation in detecting object due to lack of topological information, we can improve the detecting accuracy. Subsequently, the rescaled region of the detected object is applied to ConVol.utional Pose Machines (CPM) which is a sequential prediction structure based on ConVol.utional Neural Network. We utilize CPM to generate belief maps to predict the positions of keypoint representing human body parts and to estimate human pose by detecting 14 key body points. From the experimental results, we can prove that the proposed method detects target objects robustly in occlusion. It is also possible to perform 2D human pose estimation by providing an accurately detected region as an input of the CPM. As for the future work, we will estimate the 3D human pose by mapping the 2D coordinate information on the body part onto the 3D space. Consequently, we can provide useful human behavior information in the research of HAR.

• Journal of the Korean Geophysical Society
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• v.7 no.3
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• pp.161-170
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• 2004

Examples of GPR survey results at a variety of archaeological sites are presented. Several new analyses which include static corrections for the tilt of the GPR antenna are shown for imaging of burial mounds with significant topography. Example archaeological site plans developed from GPR remote sensing of Roman and Japanese sites are given. The first completely automated GPR survey, using only Global Positioning Satellite navigation to create 3D data volumes, is employed for a site in Louisiana to detect lost graves of the Choctaw Indian Tribe.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.61-67
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• 2017

Recently, CCTV has been combined with areas such as big data, artificial intelligence, and image analysis to detect various abnormal behaviors and to detect and analyze the overall situation of objects such as people. Image analysis research for this intelligent video surveillance function is progressing actively. However, CCTV images using 2D information generally have limitations such as object misrecognition due to lack of topological information. This problem can be solved by adding the depth information of the object created by using two cameras to the image. In this paper, we perform background modeling using Mixture of Gaussian technique and detect whether there are moving objects by segmenting the foreground from the modeled background. In order to perform the depth information-based segmentation using the RGB information-based segmentation results, stereo-based depth maps are generated using two cameras. Next, the RGB-based segmented region is set as a domain for extracting depth information, and depth-based segmentation is performed within the domain. In order to detect the center point of a robustly segmented object and to track the direction, the movement of the object is tracked by applying the CAMShift technique, which is the most basic object tracking method. From the experiments, we prove the efficiency of the proposed object detection and tracking method using the RGB-D model.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.883-886
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• 1998

In order to detect the user's gaze position on a monitor by computer vision, the accurate estimations of 3D positions and 3D motion of facial features are required. In this paper, we apply a EKF(Extended Kalman Filter) to estimate 3D motion estimates and assumes that its motion is "smooth" in the sense of being represented as constant velocity translational and rotational model. Rotational motion is defined about the orgin of an face-centered coordinate system, while translational motion is defined about that of a camera centered coordinate system. For the experiments, we use the 3D facial motion data generated by computer simulation. Experiment results show that the simulation data andthe estimation results of EKF are similar.e similar.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.1
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• pp.64-70
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• 2019

Dirofilaria immitis (D. immitis) is a filarial nematode that causes cardiopulmonary dirofilariasis in dogs. In the late stages of infection, infected dogs show one or more symptoms and advanced heart disorder with perivascular inflammation. To detect D. immitis specifically and efficiently in the early stages of infection, a duplex TaqMan qPCR assay was developed based on previous studies using primers and probes specialized to detect D. immitis cytochrome c oxidase subunit I (COI) and dog glyceraldehyde-3-phosphate dehydrogenase (GAPDH). As positive controls, plasmid DNAs were constructed from D. immitis COI or dog GAPDH and a TA-cloning vector. Simplex and duplex TaqMan qPCR assays were performed using the specific primers, probes, and genomic or plasmid DNA. The duplex reaction developed could detect D. immitis COI and dog GAPDH in the same sample simultaneously after optimization of the primer concentrations. The limit of detection was 25 copies for the simplex and duplex assays, and both showed good linearity, high sensitivity, and excellent PCR efficiency. The duplex assays for pathogen detection reduce the costs, labor, and time compared to simplex reactions. Therefore, the duplex TaqMan qPCR assay developed herein will allow efficient D. immitis detection and quantification from a large number of samples simultaneously.