• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.208-215
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• 2021

Cosmic-ray muon scattering tomography (MST) technology is a new radiation imaging technology with unique advantages. As the performance of its image reconstruction algorithm has a crucial influence on the imaging quality, researches on this algorithm are of great significance to the development and application of this technology. In this paper, a fast inspection algorithm based on clustering analysis for the identification of the existence of nuclear materials is studied and optimized. Firstly, the principles of MST technology and a binned clustering algorithm were introduced, and then several simulation experiments were carried out using Geant4 toolkit to test the effects of exposure time, algorithm parameter, the size and structure of object on the performance of the algorithm. Based on these, we proposed two optimization methods for the clustering algorithm: the optimization of vertical distance coefficient and the displacement of sub-volumes. Finally, several sets of experiments were designed to validate the optimization effect, and the results showed that these two optimization methods could significantly enhance the distinguishing ability of the algorithm for different materials, help to obtain more details in practical applications, and was therefore of great importance to the development and application of the MST technology.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.240-251
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• 2016

This paper presents a real-time indoor location and pose estimation method that utilizes simple artificial markers and image analysis techniques for the purpose of warehouse automation. The conventional indoor localization methods cannot work robustly in warehouses where severe environmental changes usually occur due to the movement of stocked goods. To overcome this problem, the proposed framework places artificial markers having different interior pattern on the predefined position of the warehouse floor. The proposed algorithm obtains marker candidate regions from a captured image by a simple binarization and labeling procedure. Then it extracts maker interior pattern information from each candidate region in order to decide whether the candidate region is a true marker or not. The extracted interior pattern information and the outer boundary of the marker are used to estimate location and heading angle of the localization system. Experimental results show that the proposed localization method can provide high performance which is almost equivalent to that of the conventional method using an expensive LIDAR sensor and AMCL algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12C
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• pp.1162-1166
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• 2005

A new low dimensional feature representation technique is presented in this paper. Linear discriminant analysis is a popular feature extraction method. However, in the case of high dimensional data, the computational difficulty and the small sample size problem are often encountered. In order to solve these problems, we propose two dimensional direct LDA algorithm, which directly extracts the image scatter matrix from 2D image and uses Direct LDA algorithm for face recognition. The ORL face database is used to evaluate the performance of the proposed method. The experimental results indicate that the performance of the proposed method is superior to DLDA.

• Journal of Auto-vehicle Safety Association
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• v.13 no.1
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• pp.51-56
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• 2021

As hydrogen is classified as an eco-friendly fuel, vehicles using hydrogen fuel are being developed worldwide. Vehicle fuel hydrogen is stored in cylinders at 70 MPa, so there is a high risk of explosion. Therefore, it is important to inspect hydrogen cylinders in used-vehicles. This study was conducted to improve the inspection method of the cylinders currently mounted on used-hydrogen buses. The inspection method is an image analysis method using a camera. Calcaulation algorithm was developed to quantitatively chech the amount of hydrogen leakage by the image method. As a result of adding a contact angle element to the calculation algorithm suggested by the GTR regulation and comparing it with the experimental data of the GTR regulation, the algorithm reliability was 94%, which secured similarity.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.691-702
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• 2011

Recently, several researchers have attempted to combine human visual perception and computer graphics. Cole et. al. suggest the study results in which line drawing algorithm in computer graphics characterize the properties of line drawing made by artists. The paper also evaluates CG line drawing algorithms depending on whether people recognize effectively specific 3D shape from the image made by those CG line drawing algorithms. However, human recognizes the shape of objects more effectively in image made by BRDF shading model than line drawing algorithm. It means that the shading factor is important to recognize shape with human perception. In this paper, we analyze the correlation between shading made by human artists and that made by CG shading algorithms. The study is to characterize the mathematical properties of artists' shading and CG shading. This type of analysis can guide the future development of new CG shading algorithm in computer graphics for the purpose of shape perception.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.312-321
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• 2003

In this paper, we implement robot which are ability to recognize obstacles and moving automatically to destination. we present two results in this paper; hardware implementation of image processing board and software implementation of visual feedback algorithm for a self-controlled robot. In the first part, the mobile robot depends on commands from a control board which is doing image processing part. We have studied the self controlled mobile robot system equipped with a CCD camera for a long time. This robot system consists of a image processing board implemented with DSPs, a stepping motor, a CCD camera. We will propose an algorithm in which commands are delivered for the robot to move in the planned path. The distance that the robot is supposed to move is calculated on the basis of the absolute coordinate and the coordinate of the target spot. And the image signal acquired by the CCD camera mounted on the robot is captured at every sampling time in order for the robot to automatically avoid the obstacle and finally to reach the destination. The image processing board consists of DSP (TMS320VC33), ADV611, SAA7111, ADV7l76A, CPLD(EPM7256ATC144), and SRAM memories. In the second part, the visual feedback control has two types of vision algorithms: obstacle avoidance and path planning. The first algorithm is cell, part of the image divided by blob analysis. We will do image preprocessing to improve the input image. This image preprocessing consists of filtering, edge detection, NOR converting, and threshold-ing. This major image processing includes labeling, segmentation, and pixel density calculation. In the second algorithm, after an image frame went through preprocessing (edge detection, converting, thresholding), the histogram is measured vertically (the y-axis direction). Then, the binary histogram of the image shows waveforms with only black and white variations. Here we use the fact that since obstacles appear as sectional diagrams as if they were walls, there is no variation in the histogram. The intensities of the line histogram are measured as vertically at intervals of 20 pixels. So, we can find uniform and nonuniform regions of the waveforms and define the period of uniform waveforms as an obstacle region. We can see that the algorithm is very useful for the robot to move avoiding obstacles.

• The Journal of Korean Society for Radiation Therapy
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• v.35
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• pp.15-21
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• 2023

Purpose: The purpose of this study is to compare the performance of the anisotropic analytical algorithm (AAA) and portal dose image prediction (PDIP) for patient-specific quality assurance based on electronic portal imaging device, and to evaluate the clinical feasibility of portal dosimetry using AAA. Subjects and methods: We retrospectively selected a total of 32 patients, including 15 lung cancer patients and 17 liver cancer patients. Verification plans were generated using PDIP and AAA. We obtained gamma passing rates by comparing the calculated distribution with the measured distribution and obtained MLC positional difference values. Results: The mean gamma passing rate for lung cancer patients was 99.5% ± 1.1% for 3%/3 mm using PDIP and 90.6% ± 5.8% for 1%/1 mm. Using AAA, the mean gamma passing rate was 98.9% ± 1.7% for 3%/3 mm and 87.8% ± 5.2% for 1%/1 mm. The mean gamma passing rate for liver cancer patients was 99.9% ± 0.3% for 3%/3 mm using PDIP and 96.6% ± 4.6% for 1%/1 mm. Using AAA, the mean gamma passing rate was 99.6% ± 0.5% for 3%/3 mm and 89.5% ± 6.4% for 1%/1 mm. The MLC positional difference was small at 0.013 mm ± 0.002 mm and showed no correlation with the gamma passing rate. Conclusion: The AAA algorithm can be clinically used as a portal dosimetry calculation algorithm for patientspecific quality assurance based on electronic portal imaging device.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.147-153
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• 2018

In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.11a
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• pp.229-232
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• 2005

More than effectively judging the existence of voids behind concrete tunnel linings or under concrete pavements, this research aims to develop the analysis algorithm of radar capable of estimation of the shape of specific voids. To detect or estimate void shapes in non-reinforced concrete, the simulation analysis model of transmission and reflection wave of electromagnetic radar is used. This radar simulation model is carried out with various void shapes. As the results, a proposed method in this study has a possibility of detecting or estimating void shapes with good accuracy.

• The KIPS Transactions:PartB
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• v.13B no.6 s.109
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• pp.591-600
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• 2006

This paper describes the development and implementation of a algorithm to decompose word images from image regions mixed text/graphics in document images using statistical analyses. To decompose word images from image regions, the character components need to be separated from graphic components. For this process, we propose a method to separate them with an analysis of box-plot using a statistics of structural components. An accuracy of this method is not sensitive to the changes of images because the criterion of separation is defined by the statistics of components. And then the character regions are determined by analyzing a local crowdedness of the separated character components. finally, we devide the character regions into text lines and word images using projection profile analysis, gap clustering, special symbol detection, etc. The proposed system could reduce the influence resulted from the changes of images because it uses the criterion based on the statistics of image regions. Also, we made an experiment with the proposed method in document image processing system for keyword spotting and showed the necessity of studying for the proposed method.