• The Transactions of the Korea Information Processing Society
• /
• v.6 no.7
• /
• pp.1970-1979
• /
• 1999

This paper proposes an AVI system which recognizes the license plate and the driver's face simultaneously using passive AVI techniques. For this, firstly, the pro-processing algorithm independent of the environment is proposed and region extraction of the car number plate and the driver's face is described. Secondly, characters are separated and recognition parameters are extracted from target regions. Thirdly, template matching of car number plate is performed and the fuzzy relation matrix of driver face is made for the final recognition processes. The merits of the proposed system are following : Pre-processing is accomplished regardless of the environment. The application areas of conventional AVI system can be expanded in the content that the driver's face is also recognized in the proposed system compared with only the number plast is recognized in the existing systems.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.2
• /
• pp.218-226
• /
• 2001

The MPEG-2 Test Model 5 (TM5) algorithm is widely used for bit rate control. In TM5, however, the target number of bits and the number of actual coding bits for each picture do not match well. Therefore, buffer overflow and picture quality degradation may occur at the end of the GOP. In this paper, we propose a new bit rate control algorithm for matching the target and the actual coding bits based on accurate bit allocation. The key idea of the proposed algorithm is to determine quantization Parameters which enable us to generate the number of actual coding bits close to the target number of bits for each picture, while maintaining uniform picture quality and supporting real-time processing. The proposed algorithm exploits the relationship between the number of actual coding bits and the number of estimated bits of the previous macroblock.

• Tuberculosis and Respiratory Diseases
• /
• v.83 no.1
• /
• pp.61-70
• /
• 2020

Background: Circulating tumor cells (CTCs) are frequently detected in patients with advanced-stage malignant tumors and could act as a predictor of poor prognosis. However, there is a paucity of data on the relationship between CTC number and primary tumor volume in patients with lung cancer. Therefore, our study aimed to evaluate the relationship between CTC number and primary tumor volume in patients with lung adenocarcinoma. Methods: We collected blood samples from 21 patients with treatment-naive lung adenocarcinoma and 73 healthy individuals. To count CTCs, we used a CTC enrichment method based on fluid-assisted separation technology. We compared CTC numbers between lung adenocarcinoma patients and healthy individuals using propensity score matching, and performed linear regression analysis to analyze the relationship between CTC number and primary tumor volume in lung adenocarcinoma patients. Results: CTC positivity was significantly more common in lung adenocarcinoma patients than in healthy individuals (p<0.001). The median primary tumor volume in CTC-negative and CTC-positive patients was 10.0 ㎤ and 64.8 ㎤, respectively. Multiple linear regression analysis showed that the number of CTCs correlated with primary tumor volume in lung adenocarcinoma patients (β=0.903, p=0.002). Further subgroup analysis showed a correlation between CTC number and primary tumor volume in patients with distant (p=0.024) and extra-thoracic (p=0.033) metastasis (not in patients with distant metastasis). Conclusion: Our study showed that CTC numbers may be associated with primary tumor volume in lung adenocarcinomas patients, especially in those with distant metastasis.

• Journal of dental hygiene science
• /
• v.24 no.1
• /
• pp.22-28
• /
• 2024

Background: Particulate matter (PM) has been extensively observed due to its negative association with human health. Previous research revealed the possible negative effect of air pollutant exposure on oral health. However, the predictive model between air pollutant exposure and the prevalence of periodontitis has not been observed yet. Therefore, this study aims to propose a predictive model for the number of patients with periodontitis exposed to PM and atmospheric factors in South Korea using deep learning. Methods: This study is a retrospective cohort study utilizing secondary data from the Korean Statistical Information Service and the Health Insurance Review and Assessment database for air pollution and the number of patients with periodontitis, respectively. Data from 2015 to 2022 were collected and consolidated every month, organized by region. Following data matching and management, the deep neural networks (DNN) model was applied, and the mean absolute percentage error (MAPE) value was calculated to ensure the accuracy of the model. Results: As we evaluated the DNN model with MAPE, the multivariate model of air pollution including exposure to PM_2.5, PM₁₀, and other atmospheric factors predict approximately 85% of the number of patients with periodontitis. The MAPE value ranged from 12.85 to 17.10 (mean±standard deviation=14.12±1.30), indicating a commendable level of accuracy. Conclusion: In this study, the predictive model for the number of patients with periodontitis is developed based on air pollution, including exposure to PM_2.5, PM₁₀, and other atmospheric factors. Additionally, various relevant factors are incorporated into the developed predictive model to elucidate specific causal relationships. It is anticipated that future research will lead to the development of a more accurate model for predicting the number of patients with periodontitis.

• Korean Journal of Remote Sensing
• /
• v.30 no.4
• /
• pp.431-444
• /
• 2014

As applications of spaceborne SAR imagery are extended, there are increased demands for accurate registrations for better understanding and fusion of radar images. It becomes common to adopt multi-resolution SAR images to apply for wide area reconnaissance. Geometric correction of the SAR images can be performed by using satellite orbit and attitude information. However, the inherent errors of the SAR sensor's attitude and ground geographical data tend to cause geometric errors in the produced SAR image. These errors should be corrected when the SAR images are applied for multi-temporal analysis, change detection applications and image fusion with other sensor images. The undesirable ground registration errors can be corrected with respect to the true ground control points in order to produce complete SAR products. Speeded Up Robust Feature (SURF) technique is an efficient algorithm to extract ground control points from images but is considered to be inappropriate to apply to SAR images due to high speckle noises. In this paper, an attempt is made to apply SURF algorithm to SAR images for image registration and fusion. Matched points are extracted with respect to the varying parameters of Hessian and SURF matching thresholds, and the performance is analyzed by measuring the imaging matching accuracies. A number of performance measures concerning image registration are suggested to validate the use of SURF for spaceborne SAR images. Various simulations methodologies are suggested the validate the use of SURF for the geometric correction and image registrations and it is shown that a good choice of input parameters to the SURF algorithm should be made to apply for the spaceborne SAR images of moderate resolutions.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.26 no.1
• /
• pp.44-49
• /
• 2016

This paper proposed the method to improve performance of a pixel, which has low accuracy, by applying image segmentation methods based on color and multi-threshold of brightness. Stereo matching is the process to find the corresponding point on the right image with the point on the left image. For this process, distance(depth) information in stereo images is calculated. However, in the case of a region which has textureless, stereo matching has low accuracy and bad pixels occur on the disparity map. In the proposed method, the relationship between adjacent pixels is considered for compensating bad pixels. Generally, the object has similar color and brightness. Therefore, by considering the relationship between regions based on segmented regions by means of color and multi-threshold of brightness respectively, the region which is considered as parts of same object is re-segmented. According to relationship information of segmented sets of pixels, bad pixels in the disparity map are compensated efficiently. By applying the proposed method, the results show a decrease of nearly 28% in the number of bad pixels of the image applied the method which is established.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.1
• /
• pp.9-18
• /
• 2018

Recently, the use of image stitching technology has been increasing as the number of contents based on virtual reality increases. Image Stitching is a method for matching multiple images to produce a high resolution image and a wide field of view image. The image stitching is used in various fields beyond the limitation of images generated from one camera. Image Stitching detects feature points and corresponding points to match multiple images, and calculates the homography among images using the RANSAC algorithm. Generally, corresponding points are needed for calculating conversion relation. However, the corresponding points include various types of noise that can be caused by false assumptions or errors about the conversion relationship. This noise is an obstacle to accurately predict the conversion relation. Therefore, RANSAC algorithm is used to construct an accurate conversion relationship from the outliers that interfere with the prediction of the model parameters because matching methods can usually occur incorrect correspondence points. In this paper, we propose an algorithm that extracts more accurate inliers and computes accurate transformation relations by using correspondence point relation information used in RANSAC algorithm. The correspondence point relation information uses distance ratio between corresponding points used in image matching. This paper aims to reduce the processing time while maintaining the same performance as RANSAC.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.7
• /
• pp.49-55
• /
• 2022

In this paper, we propose an obstacle detection method that can operate robustly even in external environmental factors such as weather. In particular, we propose an obstacle detection system that can accurately inform dangerous situations in AR through DB-based feature matching and RANSAC-based multiplane method. Since the approach to detecting obstacles based on images obtained by RGB cameras relies on images, the feature detection according to lighting is inaccurate, and it becomes difficult to detect obstacles because they are affected by lighting, natural light, or weather. In addition, it causes a large error in detecting obstacles on a number of planes generated due to complex terrain. To alleviate this problem, this paper efficiently and accurately detects obstacles regardless of lighting through DB-based feature matching. In addition, a criterion for classifying feature points is newly calculated by normalizing multiple planes to a single plane through RANSAC. As a result, the proposed method can efficiently detect obstacles regardless of lighting, natural light, and weather, and it is expected that it can be used to secure user safety because it can reliably detect surfaces in high and low or other terrains. In the proposed method, most of the experimental results on mobile devices reliably recognized indoor/outdoor obstacles.

• Journal of Preventive Medicine and Public Health
• /
• v.33 no.3
• /
• pp.313-322
• /
• 2000

Objectives : To estimate mumps incidence during the study period and to evaluate the completeness of case reporting. Methods : Capture-recapture methods, originally developed for counting wildlife animals, were used. The data sources were 1) the National Notifiable Communicable Disease Reporting System (NNCDRS; 848 cases), 2) the School Health Reporting System, temporarily administered by the Division of Education (SHRS; 1,026 cases), and 3) a survey of students (785 cases). We estimated the number of unobserved mumps cases by matching the three data sources and fitting loglinear models to the data. We then determined the estimated total number of mumps cases by adding this to the number of observed cases. Completeness was defined as the proportion of observed cases from each source to the total of estimated cases. Results : The total number of observed cases was 1,844 and the total number of estimated cases was 1,935 (95%, CI: $1,878\sim2,070$). The overall completeness was 43.8% of the NNCDRS, 53.0% of the SHRS, and 40.6% of the survey. However, completeness varied by area and age. Conclusion : Although the completeness of NNCDRS data appeared higher than in the past, it is difficult to generalize this result In Korea, it is possible to estimate the size of health hazards relatively cheaply and quickly, by applying capture-recapture methods to various data using a multiple data collection system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.5
• /
• pp.495-503
• /
• 2014

As the number of vehicles has been sharply increases, the significance of safety and effective operation issues in the parking lot is being emphasized, which takes a part of the transportation system. Recently, there have been several studies for the parking management by detecting moving object, however, recognizing numbers of fast-moving vehicles simultaneously in the picture is still a challenging problem. The parking lot in public area, or large-sized buildings has clear parking section, whereas the sensor system is configured to monitor a plurality of parking spaces. Therefore, by considering those parking lots, we suggested to develop the real-time parking availability information system by applying the real-time image processing techniques. with the help of template matching. Following the study, we wanted to provide the alternative method for parking management system through the reference template makers by recognizing movements of parked vehicles with the size and shape, regardless of direct detecting of driving movements. In addition, we evaluated the applicability and performances of the information system, presented in this study, and implemented a prototype system to simulate the parking statuses of each floor. In fat, it was possible to manage and analyze statistics about the total number of parking spaces and the number of vehicles parked through real-time video flames. We expected that the result of the study will be advanced, following the user-friendliness and cost reduction in operating parking management system and giving information by efficient analysis of parking situation.