• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.499-506
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• 2022

For autonomous ships to be commercialized and be able to navigate in coastal water, they must be able to detect maritime obstacles. One of the most common obstacles seen in coastal area are the farm buoys. In this study, a maritime object detection system was developed that detects buoys using the YOLO algorithm and visualizes the distance and bearing between buoys and the ship through geometric interpretation of camera images. After training the maritime object detection model with 1,224 pictures of buoys, the precision of the model was 89.0%, the recall was 95.0%, and the F1-score was 92.0%. Camera calibration had been conducted to calculate the distance and bearing of an object away from the camera using the obtained image coordinates and Experiment A and B were designed to verify the performance of the maritime object detection system. As a result of verifying the performance of the maritime object detection system, it can be seen that the maritime object detection system is superior to radar in its short-distance detection capability, so that it can be used as a navigational aid along with the radar.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.67-73
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• 2010

In this paper, a new face detection method that is more accurate than the conventional methods is proposed. This method utilizes a hybrid of Hausdorff distance based on the geometric similarity between the two sets of points and the LBP distance based on the distribution of local micro texture of an image. The parameters for normalization and the optimal blending factor of the two different metrics were calculated from training sample images. Popularly used face database was used to show that the proposed method is more effective and robust to the variation of the pose, illumination, and back ground than the methods based on the Hausdorff distance or LBP distance. In the particular case, the average error distance between the detected and the true face location was reduced to 47.9% of the result of LBP method, and 22.8% of the result of Hausdorff method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.1-9
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• 2012

In this paper, we propose a vision-based robust vehicle detection and inter-vehicle distance estimation algorithm for driving assistance system. We use the haar-like features of car rear-shadows, as well as the edge features for detecting of vehicles. The use of additional vehicle edge features greatly reduces the false-positive errors in the vehicle detection. And, after analyzing the conventional two inter-vehicle distance estimation methods: the location-based and the vehicle width-based, an improved inter-vehicle distance estimation algorithm which has the advantage of both method is proposed. Several experimental results show the effectiveness of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1237-1242
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• 2017

Computer vision is coming more interesting with new imaging sensors' new capabilities which enable it to understand more its surrounding environment by imitating human vision system with artificial intelligence techniques. In this paper, we made experiments with Kinect camera, a new depth sensor for object detection and distance measurement functions, most essential functions in computer vision such as for unmanned or manned vehicles, robots, drones, etc. Therefore, Kinect camera is used here to estimate the position or the location of objects in its field of view and measure the distance from them to its depth sensor in an accuracy way by checking whether that the detected object is real object or not to reduce processing time ignoring pixels which are not part of real object. Tests showed promising results with such low-cost range sensor, Kinect camera which can be used for object detection and distance measurement which are fundamental functions in computer vision applications for further processing.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.45-50
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• 2010

In this paper, we analysis the performance of cooperative spectrum sensing with distance based weight for cognitive radio (CR) systems and CR systems sense the spectrum of the licensed user by using a energy detection method. Threshold is determined in accordance with the constant false alarm rate (CFAR) algorithm for energy detection. The signal of licensed user is OFDM signal and the wireless channel between a licensed user and CR systems is modeled as Gaussian channel. From the simulation results, the cooperative spectrum sensing with distance based weight combining (DWC) and equal gain combing (EGC) methods shows higher spectrum sensing performance than single spectrum sensing does. And the detection probability performance with the DWC is higher than that with the EGC.

• Journal of Biomedical Engineering Research
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• v.25 no.2
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• pp.145-150
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• 2004

In this study for the prosthesis of the spatial and directional sensation for the blind, an ultrasonic scale system and an electronic compass system were developed. The ultrasonic scale utilizes 40 ㎑ sound for the detection of distance to the barrier and the spatial information is transferred to the blind by various sound interval, which is proportional to the distance. The electronic compass utilizes a magnetoresistor bridge for the detection of the magnetic field strength of earth in horizontal plane. The information for the direction of the earth's north is transferred by tactile stimuli by a vibrating motor band around upper head. Detection distance of the ultrasonic scale is ranged from 0.065 to 3.26 meters, and the detection angle resolution of the electronic compass is about 22.5 degrees. The integrated system of the ultrasonic scale and the electronic compass was developed. Distance information is converted to the location of the tactile stimulation along the clockwise direction by a vibrating motor according to the distance installed around upper head of the blind. The intent of this article is to provide an practical prosthetic tool of spatial and directional sensation for the blind. Daily practice of this system will improve the usefulness of this system.

• Imaging Science in Dentistry
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• v.54 no.2
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• pp.121-127
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• 2024

Purpose: Preoperative identification of the intraosseous posterior superior alveolar artery (PSAA) is critical when planning sinus surgery. This study was conducted to determine the distance between the cementoenamel junction and the PSAA, as well as to identify factors influencing the detection of the PSAA on cone-beam computed tomography (CBCT). Materials and Methods: In total, 254 CBCT scans of maxillary sinuses, acquired with 2 different scanners, were examined to identify the PSAA. The distance from the cementoenamel junction (CEJ) to the PSAA was recorded at each maxillary posterior tooth position. Binomial logistic regression and multiple linear regression were employed to evaluate the effects of scanner type, CBCT parameters, sex, and age on PSAA detection and CEJ-PSAA distance, respectively. P-values less than 0.05 were considered to indicate statistical significance. Results: The mean CEJ-PSAA distances at the second molar, first molar, second premolar, and first premolar positions were 17.0±4.0 mm, 21.8±4.1 mm, 19.5±4.7 mm, and 19.9±4.9 mm for scanner 1, respectively, and 17.3±3.5 mm, 16.9±4.3 mm, 18.5±4.1 mm, and 18.4±4.3 mm for scanner 2. No independent variable significantly influenced PSAA detection. However, tooth position (b=-0.67, P<0.05) and scanner type (b=-1.3, P<0.05) were significant predictors of CEJ-PSAA distance. Conclusion: CBCT-based estimates of CEJ-PSAA distance were comparable to those obtained in previous studies involving cadavers, CT, and CBCT. The type of CBCT scanner may slightly influence this measurement. No independent variable significantly impacted PSAA detection.

• Structural Engineering and Mechanics
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• v.44 no.2
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• pp.179-196
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• 2012

An eigenspace projection clustering method is proposed for structural damage detection by combining projection algorithm and fuzzy clustering technique. The integrated procedure includes data selection, data normalization, projection, damage feature extraction, and clustering algorithm to structural damage assessment. The frequency response functions (FRFs) of the healthy and the damaged structure are used as initial data, median values of the projections are considered as damage features, and the fuzzy c-means (FCM) algorithm are used to categorize these features. The performance of the proposed method has been validated using a three-story frame structure built and tested by Los Alamos National Laboratory, USA. Two projection algorithms, namely principal component analysis (PCA) and kernel principal component analysis (KPCA), are compared for better extraction of damage features, further six kinds of distances adopted in FCM process are studied and discussed. The illustrated results reveal that the distance selection depends on the distribution of features. For the optimal choice of projections, it is recommended that the Cosine distance is used for the PCA while the Seuclidean distance and the Cityblock distance suitably used for the KPCA. The PCA method is recommended when a large amount of data need to be processed due to its higher correct decisions and less computational costs.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.535-543
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• 2018

Recently, level meters have been associated with the safety and maintenance of industrial sites and require a wide measurement range. Generally, to ensure the measurement range of the level meter, the measurement environment is improved to reduce the noise or to compensate the distortion of the signal through signal processing. The noise of FMCW (Frequency Modulated Continuous Wave) radar level meter or the distortion of the signal affects the near region characteristics of the level gauge, resulting in a reduction of the minimum detection distance. In this paper, an equalizer filter considering characteristics of window function and bit spectrum is applied to remove the noise in the near region of the level meter to improve the minimum detection distance performance and to improve the measurement reliability in the vicinity of the level meter, which is relatively difficult to detect, we want to improve the detection range.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.1
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• pp.51-62
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• 2020

This study was conducted to develop a method for depth assessment of embedded sources using gamma-spectrum ratio and for the evaluation of field applicability. To this end, Peak to Compton and Peak to valley ratio changes were evaluated according to ¹³⁷Cs, ⁶⁰Co, ¹⁵²Eu point source depth using HPGe detector and MCNP simulation. The effects of measurement distance of PTV and PTC methods were evaluated. Using the results, the source depth assessment equation using the PTC and PTV methods was derived based on the detection distance of 50 cm. In addition, the sensitivity of detection distance changes was assessed when using PTV and PTC methods, and error increased by 3 to 4 cm when detection distance decreased by 20 cm based on 50 cm. However, it was confirmed that if the detection distance was increased to 100 cm, the effects of detection distance were small. And PTV and PTC methods were compared with the two distance measurement method which evaluates the depth of source by the change of net peak counting rate according to the detection distance. As a result of source depth assessment, the PTV and PTC showed a maximum error of 1.87 cm and the two distance measurement method showed maximum error of 2.69 cm. The results of the experiment confirmed that the accuracy of the PTV and PTC methods was higher than two distance measurement. In addition, Sensitivity evaluation by horizontal position error of source has maximum error of less than 25.59 cm for the two distance measurement method. On the other hand, PTV and PTC method showed high accuracy with maximum error of less than 8.04 cm. In addition, the PTC method has lowest standard deviation for the same time measurement, which is expected to enable rapid measurement.