• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.63-70
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• 2022

Although 2D Object detection has been largely improved in the past years with the advance of deep learning methods and the use of large labeled image datasets, 3D object detection from 2D imagery is a challenging problem in a variety of applications such as robotics, due to the lack of data and diversity of appearances and shapes of objects within a category. Google has just announced the launch of Objectron that has a novel data pipeline using mobile augmented reality session data. However, it also is corresponding to 2D-driven 3D object detection technique. This study explores more mature 2D object detection method, and applies its 2D projection to Objectron 3D lifting system. Most object detection methods use bounding boxes to encode and represent the object shape and location. In this work, we explore a stochastic representation of object regions using Gaussian distributions. We also present a similarity measure for the Gaussian distributions based on the Hellinger Distance, which can be viewed as a stochastic Intersection-over-Union. Our experimental results show that the proposed Gaussian representations are closer to annotated segmentation masks in available datasets. Thus, less accuracy problem that is one of several limitations of Objectron can be relaxed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.1044-1053
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• 2022

Time domain reflectometry (TDR) is a diagnostic technique to evaluate the physical integrity of cable and finds application in leak detection and localization of piping system. In this study, a cable-shaped leak detection sensor was proposed using the TDR technique for monitoring leakage detection of ship's engine room seawater piping system. The cable sensor was developed using a twisted pair arrangement and wound by an absorbent material. The availability and performance of the sensor for leak detection and localization were evaluated on a lab-scale pipeline set up. The developed sensor was installed onto the pipes and flanges of the lab-scale set up and various TDR waveforms were acquired and analyzed according to the dif erent variables including the number of twists and sheath thickness. The result indicated that the twisted cable sensor was able to produce clear and smooth signal as compared to the TDR sensor with a parallel arrangement. The optimal number of twist was determined to be above 10 per the unit length. The optimal diameter of sheath thickness that results in the desired sensitivity was determined to be ranging from 80% up to 120% of the diameter of the conductor. The linear regression analysis for estimation of leak localization was carried out to estimate the location of the leakage, and the result was a determination coefficient of 0.9998, indicating a positive relationship with the actual leakage point. The proposed TDR based leak detection method appears to be an effective method for monitoring leakage of ship's seawater piping system.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.113-119
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• 2023

Most infrastructure structures were completed during periods of economic growth. The number of infrastructure structures reaching their lifespan is increasing, and the proportion of old structures is gradually increasing. The functions and performance of these structures at the time of design may deteriorate and may even lead to safety accidents. To prevent this repercussion, accurate inspection and appropriate repair are requisite. To this end, demand is increasing for computer vision and deep learning technology to accurately detect even minute cracks. However, deep learning algorithms require a large number of training data. In particular, label images indicating the location of cracks in the image are required. To secure a large number of those label images, a lot of labor and time are consumed. To reduce these costs as well as increase detection accuracy, this study proposed a learning structure based on mean teacher method. This learning structure was trained on a dataset of 900 labeled image dataset and 3000 unlabeled image dataset. The crack detection network model was evaluated on over 300 labeled image dataset, and the detection accuracy recorded a mean intersection over union of 89.23% and an F1 score of 89.12%. Through this experiment, it was confirmed that detection performance was improved compared to supervised learning. It is expected that this proposed method will be used in the future to reduce the cost required to secure label images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.105-111
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• 2010

This paper proposes the recursive algorithm for passive proximity detection system based on signal strength. The system is designed to be used in the smart medicine chest in order to provide location-based service for the senior personnel. Due to the system profile, single receiver and uni-direction communication are applied over the signal attenuation model for the determination of user existence within certain proximity. The performance of conventional methods is subjective to the sight between the transmitter and receiver unless the direction of target is known. To appreciate the temporal and spatial locality of human subjects, the authors present exponential moving average (EMA) to compensate the unexpected position error from the direction and/or environment. By using optimal parameter, the experiments with EMA algorithm demonstrates 32.26% (maximum 40.80%) reduction in average of the error probability with 50% of consecutive sight in time.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.211-216
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• 2012

There are two kinks of processes could detect the laser pointer. One is the process which detects the location of the pointer. the other one is a possibility of dividing with the process which converts the coordinate of the laser pointer which is input in coordinate of the monitor. The previous Mean-Shift algorithm is not appropriately for real-time video image to calculate many quantity. In this paper, we proposed the context driven real-time laser pointer detection and tracking. The proposed method is a possibility of getting the result which is fixed from the situation which the background and the background which are complicated dynamically move. In the actual environment, we can get to give constant results when the object come in, when going out at forecast boundary. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed method. Accordingly, the accuracy and the quality of image recognition will be improved the surveillance system.

• Smart Structures and Systems
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• v.20 no.4
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• pp.427-440
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• 2017

One of the suitable structural damage detection methods using vibrational characteristics are damage-index-based methods. In this study, a damage index for identifying damages in plate structures using frequency response function (FRF) data has been provided. One of the significant challenges of identifying the damages in plate structures is high number of degrees of freedom resulting in decreased damage identifying accuracy. On the other hand, FRF data are of high volume and this dramatically decreases the computing speed and increases the memory necessary to store the data, which makes the use of this method difficult. In this study, FRF data are compressed using two-dimensional principal component analysis (2D-PCA), and then converted into damage index vectors. The damage indices, each of which represents a specific condition of intact or damaged structures are stored in a database. After computing damage index of structure with unknown damage and using algorithm of lookup tables, the structural damage including the severity and location of the damage will be identified. In this study, damage detection accuracy using the proposed damage index in square-shaped structural plates with dimensions of 3, 7 and 10 meters and with boundary conditions of four simply supported edges (4S), three clamped edges (3C), and four clamped edges (4C) under various single and multiple-element damage scenarios have been studied. Furthermore, in order to model uncertainties of measurement, insensitivity of this method to noises in the data measured by applying values of 5, 10, 15 and 20 percent of normal Gaussian noise to FRF values is discussed.

• Journal of Welding and Joining
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• v.13 no.2
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• pp.42-52
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• 1995

In the evaluation of aging degradation on the structural materials based on the fracture mechanics, the detection and size prediction of defect are very important. Aiming at nondestructive detection and size prediction ol defect with high accuracy and resolution, therefore, an lnduced Current Focusing Potential Drop(ICFPD) technique has been developed. The principle of this technique is to induce a focusing current at an exploratory region by an induction wire flowing an alternating current(AC) that is a constant ampere and frequency. Defects are assessed with the potential drops that are measured the induced current on the surface of metallic material by the potential pick-up pins. In this study, the lCFPD technique was applied for evaluating the location and size of the surface crack and blind crack made in plate specimens, and also for detecting the defects existing in valve, a field component, that were developed by SCC etc. during the service. The results of this present study show that surface crack and blind crack are able to defect with potential drop. these cracks are distinguished with the distribution of potential drop, and the crack depths can be estimated with each normalized potential drop that are parameters estimating the depth of each type crack. In the field component, the defects estimated by experiment result correspond with those in the cutting face of the measuring point within a higher sensitivity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.160-168
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• 2001

Change detection using difference picture has been used to detect the location of moving targets and to track them. This method needs the assumption of static camera, and the global motion compensation is required in case of a moving camera. This paper suggests a method for finding a minimum bounding rectangles(MBR) of moving targets in the image sequences using moving region detection, especially with a moving camera. If the global motion parameter is inaccurately estimated, the estimated locations of targets will be accurate either To alleviate this problem, we introduce the concept of the confidence measure and achieve more accurate estimation of global motion. Experimental results show that the proposed method successfully removes background region and extracts MBRs of the targets. Even with a moving camera, the new global motion estimation algorithm performs more precise]y and it reduces the background compensation errors of change detection.

• KSBB Journal
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• v.13 no.5
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• pp.577-584
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• 1998

A sensitive membrane strip assay for plasma lipoprotein cholesterol that can be performed without handling reagents has been investigated. We previously developed an assay system with immobilized enzymes (cholesterol esterase and cholesterol oxidase) on the surfaces of nitrocellulose membrane(1). In such a case, the amount of enzymes present on the membrane was limited by its surface area and, thus, the detection capability was relatively poor (> 50 mg/dL cholesterol). To overcome this problem, we devised a new system with non-immobilized enzymes by placing them within interstitial spaces of a celullose membrane pad in a dry state. Upon contact with sample medium, the enzymes were immediately dissolved and participated in the reactions with cholesterol in a liquid phase. We constructed a user-friendly system consisting of four membrane pads fro sample application, cholesterol decomposition, color development as signal, and medium absorption to invoke a continuous flow (sequential location from the bottom). A sample containing lipoproteins was added into the application pad by capillary action and transferred to the next pad for decomposition. The decomposition pad (namely, enzyme pad) contained a detergent (sodium cholate) for the destruction of lipoprotein particles, the two enzymes for cholesterol decomposition, and a chromogen (3,3'-diaminobenzidine). As a consequence of the enzyme reactions, hydrogen peroxide was produced, and then reacted in the presence of the chromogen with horseradish peroxidase immobilized on the signal generation pad. Finally, a colorimetric signal directly proportional to the cholesterol concentration was produced. The detection limit determined from this system under optimal conditions was at least 2 times lower than of the enzyme-immobilized system.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.5
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• pp.465-475
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• 2004

This paper is the first part of the study on the development of a smart active layer (SAL) sensor, which consists of two parts. In this first part, the theory and concept of the SAL sensor is investigated, which is designed for the detection of elastic waves caused by internal cracks and damages in structures. For the development SAL sensor, (i) the basic theory of elastic waves was studied, (ii) the feasible study of the SAL as an elastic waves detection sensor using the finite element analysis (FEA) with respect to a piezoceramic disc was performed. (iii) the comparison of performances between some piezoceramic sensors and a commercial acoustic emission (AE) sensor was accomplished to ensure the applicability by the experimental means, such as a pencil lead break test. Also, the conceptional study for the SAL sensor, which can be utilized for the effective detection and locating of defects by the arrangement of regularly distributed sensors, was discussed.