• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.372-379
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• 2013

In this paper, we proposed a content-based image retrieval algorithm using local binary patterns and HSV color histogram. Images are retrieved using image input in image retrieval system. Many researches are based on global feature distribution such as color, texture and shape. These techniques decrease the retrieval performance in images which contained background the large amount of image. To overcome this drawback, the proposed method extract background fast and emphasize the feature of object by shrinking the background. The proposed method uses HSV color histogram and Local Binary Patterns. We also extract the Local Binary Patterns in quantized Hue domain. Experimental results show that the proposed method 82% precision using Corel 1000 database.

• 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.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.173-176
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• 2001

In this thesis, a new measurement system is implemented for depth data extraction based on the camera calibration of the known pattern. The relation between 3D world coordinate and 2D image coordinate is analyzed. A new camera calibration algorithm is established from the analysis and then, the internal variables and external variables of the CCD camera are obtained. Suppose that the measurement plane is horizontal plane, from the 2D plane equation and coordinate transformation equation the approximation values corresponding minimum values using Newton-Rabbson method is obtained and they are stored into the look-up table for real time processing . A slit laser light is projected onto the object, and a 2D image obtained on the x-z plane in the measurement system. A 3D shape image can be obtained as the 2D (x-z)images are continuously acquired, during the object is moving to the y direction. The 3D shape images are displayed on computer monitor by use of OpenGL software. In a measuremental result, we found that the resolution of pixels have $\pm$ 1% of error in depth data. It seems that the error components are due to the vibration of mechanic and optical system. We expect that the measurement system need some of mechanic stability and precision optical system in order to improve the system.

• Imaging Science in Dentistry
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• v.50 no.2
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• pp.169-174
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• 2020

Purpose: Periodontal disease causes tooth loss and is associated with cardiovascular diseases, diabetes, and rheumatoid arthritis. The present study proposes using a deep learning-based object detection method to identify periodontally compromised teeth on digital panoramic radiographs. A faster regional convolutional neural network (faster R-CNN) which is a state-of-the-art deep detection network, was adapted from the natural image domain using a small annotated clinical data- set. Materials and Methods: In total, 100 digital panoramic radiographs of periodontally compromised patients were retrospectively collected from our hospital's information system and augmented. The periodontally compromised teeth found in each image were annotated by experts in periodontology to obtain the ground truth. The Keras library, which is written in Python, was used to train and test the model on a single NVidia 1080Ti GPU. The faster R-CNN model used a pretrained ResNet architecture. Results: The average precision rate of 0.81 demonstrated that there was a significant region of overlap between the predicted regions and the ground truth. The average recall rate of 0.80 showed that the periodontally compromised teeth regions generated by the detection method excluded healthiest teeth areas. In addition, the model achieved a sensitivity of 0.84, a specificity of 0.88 and an F-measure of 0.81. Conclusion: The faster R-CNN trained on a limited amount of labeled imaging data performed satisfactorily in detecting periodontally compromised teeth. The application of a faster R-CNN to assist in the detection of periodontally compromised teeth may reduce diagnostic effort by saving assessment time and allowing automated screening documentation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.4
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• pp.42-48
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• 2000

Generally an operator would take notice at putting a patient under anesthesia. If the operation is executed in mistake, the patient is exposed to danger. The object of this Paper is that a system is developed for an accuracy of system and a convenience of user interface to prevent an operation of several elements of risk by mistake. The part of electrical system particularly is made for convenience of a manipulation using electrical switch and encoder. A real-time monitoring system is developed for an airway pressure and a gas concentration of carbon dioxide of patient using graphic LCD(liquid crystal display). Moreover, this flow control system could be developed control with accuracy by feedback control method. This is implemented using flow control valve and flow sensor. The implemented system gives convenience and precision of a manipulation of variable value using developed technique. This system shows guaranteed stabilization and confidence of anesthesia ventilator by notifying us that patient's state and information in case of being out of alarm range of variable value.

• Smart Media Journal
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• v.7 no.2
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• pp.15-22
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• 2018

Pupil tracking technologies can be used as an efficient information provider means that provides convenience to the user by connecting with a smart device. In this paper, we measure the distance of user gaze point using the pupil tracking device which produced by Pupil-labs, also shows the experimental result with analyzing accuracy and precision. Based on that the pupil gaze point location which tracked by pupil tracking device is compared with object target in terms of error. Since the mobile pupil tracking device is also one kind of camera, we have to perform the calibration before using the device. Not only generally used 2-dimensional calibration, but also 3-dimensional calibration method is explained. To get the improved accuracy of 2-dimensional calibration result, the 3-dimensional calibration set an imaginary plane and executes the calibration in various 3-dimensional spaces. To show the efficiency of 3-dimensional calibration, we analyze the experimental result. It also introduces various using methods and information that can be obtained through the device.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.172-175
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• 2016

Time of Flight(ToF) LiDAR(Light Detection And Ranging) technology has been used for distance measurement and object detection by measuring ToF time information. This technology has been evolved into higher precision measurement field such like autonomous driving car and terrain analysis since the retrieval of exact ToF time information is of prime importance. In this paper, as a accuracy indicator of the ToF time information, timing jitter was measured and analyzed through Single-Shot LiDAR system(SSLs) mainly consisting of 1.5um wavelength MOPA LASER, InGaAs Avalanche Photodiode(APD) at 31M free space environment. Additionally, we applied spline interpolation and multiple-shot averaging method on measured data through SSLs to improve ToF timing information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.169-171
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• 2021

Image processing through cameras such as self-driving, CCTV, mobile phone security, and parking facilities is being used to solve many real-life problems. Simple classification is solved through image processing, but it is difficult to find images or in-image features of complexly mixed objects. To solve this feature point, we utilize deep learning techniques in classification, detection, and segmentation of image data so that we can think and judge closely. Of course, the results are better than just image processing, but we confirm that the results judged by the method of image segmentation using deep learning have deviations from the real object. In this paper, we study how to perform accuracy improvement through simple image processing just before outputting the output of deep learning image segmentation to increase the precision of image segmentation.

• Journal of Korea Multimedia Society
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• v.14 no.10
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• pp.1252-1261
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• 2011

In this paper, we propose the comparison method of pattern similarity for video segmentation algorithm. The shot boundary type is categorized as 2 types, abrupt change and gradual change. The representative examples of gradual change are dissolve, fade-in, fade-out or wipe transition. The proposed method consider the problem to detect shot boundary as 2-class problem. We concentrated if the shot boundary event happens or not. It is essential to define similarity between frames for shot boundary detection. We proposed 2 similarity measures, within similarity and between similarity. The within similarity is defined by feature comparison between frames belong to same shot. The between similarity is defined by feature comparison between frames belong to different scene. Finally we calculated the statistical patterns comparison between the within similarity and between similarity. Because this measure is robust to flash light or object movement, our proposed algorithm make contribution towards reducing false positive rate. We employed color histogram and mean of sub-block on frame image as frame feature. We performed the experimental evaluation with video dataset including set of TREC-2001 and TREC-2002. The proposed algorithm shows the performance, 91.84% recall and 86.43% precision in experimental circumstance.

• Journal of Radiation Protection and Research
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• v.42 no.2
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• pp.83-90
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• 2017

Background: Different cases exist in the measurement of thyroid radiobioassays owing to the individual characteristics of the subjects, especially the potential variation in the counting efficiency. An In situ Object Counting System (ISOCS) was developed to perform an efficiency calibration based on the Monte Carlo calculation, as an alternative to conventional calibration methods. The purpose of this study is to evaluate the applicability of ISOCS to thyroid radiobioassays by comparison with a conventional thyroid monitoring system. Materials and Methods: The efficiency calibration of a portable high-purity germanium (HPGe) detector was performed using ISOCS software. In contrast, the conventional efficiency calibration, which needed a radioactive material, was applied to a scintillator-based thyroid monitor. Four radioiodine samples that contained $^{125}I$ and $^{131}I$ in both aqueous solution and gel forms were measured to evaluate radioactivity in the thyroid. ANSI/HPS N13.30 performance criteria, which included the relative bias, relative precision, and root-mean-squared error, were applied to evaluate the performance of the measurement system. Results and Discussion: The portable HPGe detector could measure both radioiodines with ISOCS but the thyroid monitor could not measure $^{125}I$ because of the limited energy resolution of the NaI(Tl) scintillator. The $^{131}I$ results from both detectors agreed to within 5% with the certified results. Moreover, the $^{125}I$ results from the portable HPGe detector agreed to within 10% with the certified results. All measurement results complied with the ANSI/HPS N13.30 performance criteria. Conclusion: The results of the intercomparison program indicated the feasibility of applying ISOCS software to direct thyroid radiobioassays. The portable HPGe detector with ISOCS software can provide the convenience of efficiency calibration and higher energy resolution for identifying photopeaks, compared with a conventional thyroid monitor with a NaI(Tl) scintillator. The application of ISOCS software in a radiation emergency can improve the response in terms of internal contamination monitoring.