• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.300-305
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• 2007

In this study, we have studied the fabrication and the performance evaluation of digital radiation detector of the based on selenium (a-Se) prototype which is widely researched about recently. The detector was fabricated using amorphous selenium in the specification of active area size $7{\times}8.5"$, pixel pitch $139{\mu}m$, and 12 bit ADC. In order for the performance evaluation of the fabricated detector, we used radiation quality RQA 5 that is suggested by the International Electrotechnical Commission (IEC), and evaluated modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE). Concerning MTF measurement, we used slit camera (Nuclear Associates, Model : 07-624-2222), and evaluated in the slit method. Also so as to compare the performance evaluation on the detector fabricated in this study, we used Hologic Direct-Ray (DR-1000) and GE Revolution XQ/I system, and evaluated and compared in the same method MTF, NPS, and DQE which are image quality factors. And as a result, the MTF of each detector In Nyquist frequency were evaluated to be 58% (at 3.5 lp/mm) in the case of DR-1000 and 65% (at 2.5 lp/mm) in the case of XQ/I, and that for the detector fabricated in this study was evaluated to be 36% (at 3.51 lp/mm). Also in the case of DQE(0), the detector fabricated in this study, DR-1000 of Hologic company, and XQ/I system of GE company respectively were evaluated as 36%, 32%, and 50%.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.241-246
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• 2016

Nowadays many people have an interest in facial expression and the behavior of people. These are human-robot interaction (HRI) researchers utilize digital image processing, pattern recognition and machine learning for their studies. Facial feature point detector algorithms are very important for face recognition, gaze tracking, expression, and emotion recognition. In this paper, a cascade facial feature point detector is used for finding facial feature points such as the eyes, nose and mouth. However, the detector has difficulty extracting the feature points from several images, because images have different conditions such as size, color, brightness, etc. Therefore, in this paper, we propose an algorithm using a modified cascade facial feature point detector using a convolutional neural network. The structure of the convolution neural network is based on LeNet-5 of Yann LeCun. For input data of the convolutional neural network, outputs from a cascade facial feature point detector that have color and gray images were used. The images were resized to $32{\times}32$. In addition, the gray images were made into the YUV format. The gray and color images are the basis for the convolution neural network. Then, we classified about 1,200 testing images that show subjects. This research found that the proposed method is more accurate than a cascade facial feature point detector, because the algorithm provides modified results from the cascade facial feature point detector.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.2
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• pp.49-56
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• 2008

Image registration is one of the critical techniques of image mosaic which has many applications such as generating panoramas, video monitoring, image rendering and reconstruction, etc. The fundamental tasks of image registration are point features extraction and tracking which take much computation time. KLT(Kanade-Lucas-Tomasi) feature tracker has proposed for extracting and tracking features through image sequences. The aim of this study is to demonstrate the usage of effective and robust KLT feature detector and tracker for an image registration using the sequence image frames captured by UAV video camera. In result, by using iterative implementation of the KLT tracker, the features extracted from the first frame of image sequences could be successfully tracked through all frames. The process of feature tracking in the various frames with rotation, translation and small scaling could be improved by a careful choice of the process condition and KLT pyramid implementation.

• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.263-270
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• 2014

Corner detection and feature extraction are essential aspects of computer vision problems such as object recognition and tracking. Feature detectors such as Scale Invariant Feature Transform (SIFT) yields high quality features but computationally intensive for use in real-time applications. The Features from Accelerated Segment Test (FAST) detector provides faster feature computation by extracting only corner information in recognising an object. In this paper we have analyzed the efficient object detection algorithms with respect to efficiency, quality and robustness by comparing characteristics of image detectors for corner detector and feature extractors. The simulated result shows that compared to conventional SIFT algorithm, the object recognition system based on the FAST corner detector yields increased speed and low performance degradation. The average time to find keypoints in SIFT method is about 0.116 seconds for extracting 2169 keypoints. Similarly the average time to find corner points was 0.651 seconds for detecting 1714 keypoints in FAST methods at threshold 30. Thus the FAST method detects corner points faster with better quality images for object recognition.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.324-327
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• 2002

For a next generation PET that realizes high sensitivity and high resolution, we proposed a design of a depth of interaction detector. A unit of the detector is constructed of four stages rectangular blocks of 2 by 2 Gd$_2$SiO$\sub$5/: Ce (GSO) crystal array optically coupled to position sensitive photomultiplier tube (PS-PMT). The 256ch flat panel PS-PMT is under development by Hamamatsu Photonics K.K., JAPAN. It has large cathode area, 51.7 by 51.7 mm$^2$, and the ratio of the effective area to external size is about 90%. The feature will contribute high packing fraction, accordingly high sensitivity. The 256 anodes are arranged in 16 by 16 at intervals of 3.0 mm. So as to evaluate the detector capability for identifying crystal of interaction, we got positioning image histograms with coupling a 16 by 5 array of GSO crystals, 2.9 by 2.9 by 7.5 mm$^3$, to the PS-PMT by irradiating a gamma ray uniformly from a point source. Flat panel PS-PMT is a new promising device for PET. We need to evaluate it if its performance is sufficiency. The performance was compared to the one with a 16ch PS-PMT.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.418-421
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• 2003

Today, much terminologies such as noise spectrum, Sharpness, contrast, MTF had been defined for Image quality revaluation of radiation Image. Since development of Xeroradiography In the 1970s, Digital radiation detector that use amorphous selenium was developed. The aim of this research is to analyze physical phenomenon of digital radiation detector that use amorphous selenium. Result of Monte Carlo simulations on amorphous selenium based on physical properties(creation of electron-hole pairs) by induced x-ray are described. From the simulation, intrinsic point spread function(PSF) was found and used to observe modulation transfer function(MTF). We investigated how PSF and MTF changed with various x-ray energy. This result can be used to design digital x-ray detector based on a-Se.

• Nuclear Engineering and Technology
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• v.53 no.6
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• pp.1947-1954
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• 2021

In the nuclear medicine imaging, quality control (QC) process using quadrant bar phantom is fundamental aspect of evaluating the spatial resolution. In addition, QC process of gamma camera is performed by daily or weekly. Recently, Monte Carlo simulation using the Geant4 application for tomographic emission (GATE) is widely applied in the pre-clinical nuclear medicine field for modeling gamma cameras with pixelated cadmium telluride (CdTe) semiconductor detector. In this study, we modeled a pixelated CdTe semiconductor detector and quadrant bar phantom (0.5, 1.0, 1.5, and 2.0 mm bar thicknesses) using the GATE tool. Similarity analysis based on correlation coefficients and peak signal-to-noise ratios was performed to compare image qualities for various source to collimator distances (0, 2, 4, 6, and 8 cm) and collimator lengths (0.2, 0.4, 0.6, 0.8, and 1.0 cm). To this end, we selected reference images based on collimator length and source to collimator distance settings. The results demonstrate that as the collimator length increases and the source to collimator distance decreases, the similarity to reference images improves. Therefore, our simulation results represent valuable information for the modeling of CdTe-based semiconductor gamma imaging systems and QC phantoms in the field of nuclear medicine.

• Smart Structures and Systems
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• v.28 no.6
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• pp.811-825
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• 2021

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.44-44
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• 2003

As a basic measurement tool in the areas of animal models of human disease, gene expression and therapy, and drug discovery and development, small animal PET imaging is being used increasingly. An ideal small animal PET should have high sensitivity and high and uniform resolution across the field of view to achieve high image quality. However, the combination of long narrow pixellated crystal array and small ring diameter of small animal PET leads to the degradation of spatial resolution for the source located at off center. This degradation of resolution can be improved by determining the depth of interaction (DOI) in the crystal and by taking into account the information in sorting the coincident events. Among a number of 001 identification schemes, dual layer phsowich detector has been widely investigated by many research groups due to its practicability and effectiveness on extracting DOI information. However, the effects of each crystal length composing dual layer phoswich detector on DOI measurements and image qualities were not fully characterized. In order to minimize the DOI effect, the length of each layer of phoswich detector should be optimized. The aim of this study was to perform simulations using a simulation tool, GATE to design the optimum lengths of crystals composing a dual layer phoswich detector. The simulated small PET system employed LSO front layer LuYAP back layer phoswich detector modules and the module consisted of 8${\times}$8 arrays of dual layer crystals with 2 mm ${\times}$ 2 mm sensitive area coupled to a Hamamatsu R7600 00 M64 PSPMT. Sensitivities and variation of radial resolutions were simulated by varying the length of LSO front layer from 0 to 10 mm while the total length (LSO + LuYAP) was fixed to 20 mm for 10 cm diameter ring scanner. The radial resolution uniformity was markedly improved by using DOI information. There existed the optimal lengths of crystal layers to minimize the variation of radial resolutions. In 10 cm ring scanner configuration, the radial resolution was kept below 3.4 mm over 8 cm FOV while the sensitivity was higher than 7.4% for LSO 5 mm : LuYAP 15 mm phoswich detector. In this study, the optimal length of dual layer phoswich detector was derived to achieve high and uniform radial resolution.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.814-821
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• 2011

The purpose of this study was to evaluate of resolution parameter and reconstitution filter in the 256 multi detector computed tomography(MDCT) by using the head phantom. We used 256 MDCT, and head phantom of philips system. We evaluated to image quality by using Extended Brilliance Workspace. The protocol were axial scan method with 120 kVp, 0.5 sec of rotation time, 5 mm of slice thickness and increment, 250 mm of field of view(FOV), $512{\times}512$ of matrix size, 1.0 of pitch, $128{\times}0.625$ mm of collimations. The resolution parameter was applied for 'Standard', 'High' and 'Ultrahigh'. The reconstitution filters were changed to seven type of 'A', 'B', 'C', 'D', 'UA', 'UB', 'UC'. The assesment factors of image quality were the uniformity, the noise, the linearity and 50% and 10% of the modulation transfer function(MTF). Finally The good image quality in 'High' resolution parameter showed at the uniformity, the linearity and 50% and 10% of MTF. The 'UA', 'UB' reconstitution filter showed at the good image quality of the uniformity and the noise and 'C' reconstitution filter showed at the same result of the linearity and 50% and 10% of MTF.