• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.29 no.1
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• pp.56-59
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• 2003

The incident of false aneurysm of internal maxillary artery in the oral and maxillofacial region is known to be very rare. One case of false aneurysm in the internal maxillary artery is presented, which was experienced in our department. The etiology of this case is regarded as the mandibular condyle fracture, and/or iatrogenic trauma during open reduction. Clinically, there were systolic bruit on auscultation, pulsation and massive bleeding during operation. The lesion was finally diagnosed with angiography and treated by embolization procedure. False aneurysm can cause so massive bleeding as to threat the life of the patients. Therefore accurate diagnosis and treatment is very important. Angiography enables the solid diagnosis for the clinical one. And as the embolization has many advantages over the ligation, it can be a good treatment method.

• Journal of Radiation Protection and Research
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• v.44 no.2
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• pp.64-71
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• 2019

Background: It is very difficult to distinguish between a radioactive contamination source and background radiation from natural radionuclides in the marine environment by means of online monitoring system. The objective of this study was to investigate a statistical process for triggering abnormal level of count rate data measured from our on-line seawater radioactivity monitoring. Materials and Methods: Count rate data sets in time series were collected from 9 monitoring posts. All of the count rate data were measured every 15 minutes from the region of interest (ROI) for $^{137}Cs$ ($E_{\gamma}=661.6keV$) on the gamma-ray energy spectrum. The Shewhart ($3{\sigma}$), CUSUM, and Bayesian S-R control chart methods were evaluated and the comparative analysis of determination methods for count rate data was carried out in terms of the false positive incidence rate. All statistical algorithms were developed using R Programming by the authors. Results and Discussion: The $3{\sigma}$, CUSUM, and S-R analyses resulted in the average false positive incidence rate of $0.164{\pm}0.047%$, $0.064{\pm}0.0367%$, and $0.030{\pm}0.018%$, respectively. The S-R method has a lower value than that of the $3{\sigma}$ and CUSUM method, because the Bayesian S-R method use the information to evaluate a posterior distribution, even though the CUSUM control chart accumulate information from recent data points. As the result of comparison between net count rate and gross count rate measured in time series all the year at a monitoring post using the $3{\sigma}$ control charts, the two methods resulted in the false positive incidence rate of 0.142% and 0.219%, respectively. Conclusion: Bayesian S-R and CUSUM control charts are better suited for on-line seawater radioactivity monitoring with an count rate data in time series than $3{\sigma}$ control chart. However, it requires a continuous increasing trend to differentiate between a false positive and actual radioactive contamination. For the determination of count rate, the net count method is better than the gross count method because of relatively a small variation in the data points.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.1-11
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• 2009

To classifying and filtering of adult images, in recent the computer vision techniques are actively investigated because rapidly increase for the amount of adult images accessible on the Internet. In this paper, we investigate and develop the tool filtering of adult images using skin color model. The tool is consisting of two steps. In the first step, we use a skin color classifier to extract skin color regions from an image. In the nest step, we use a region feature classifier to determine whether an image is an adult image or not an adult image depending on extracted skin color regions. Using histogram color model, a skin color classifier is trained for RGB color values of adult images and not adult images. Using SVM, a region feature classifier is trained for skin color ratio on 29 regions of adult images. Experimental results show that suggested classifier achieve a detection rate of 92.80% with 6.73% false positives.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.511-520
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• 2016

Automatic License Plate Detection (ALPD) is a key technology for a efficient traffic control. It is used to improve work efficiency in many applications such as toll payment systems and parking and traffic management. Until recently, the hand-crafted features made for image processing are used to detect license plates in most studies. It has the advantage in speed. but can degrade the detection rate with respect to various environmental changes. In this paper, we propose a way to utilize a Faster Region based Convolutional Neural Networks (Faster R-CNN) and a Conventional Convolutional Neural Networks (CNN), which improves the computational speed and is robust against changed environments. The module based on Faster R-CNN is used to detect license plate candidate regions from images and is followed by the module based on CNN to remove False Positives from the candidates. As a result, we achieved a detection rate of 99.94% from images captured under various environments. In addition, the average operating speed is 80ms/image. We implemented a fast and robust Real-Time License Plate Detection System.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.83-92
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• 2006

This paper describes an image disparity estimation method using region-based stereo matching. Region-based disparity estimation yields a disparity map as the unit of segmented region. However it estimates disparity imprecisely because it not only has matching errors but also applies an identical way to disparity estimation, which does not consider each type of matched regions. To solve this problem, we proposes a disparity estimation method which considers the type of matched regions. That is, the proposed method classifies whole matched regions into a similar-matched region, a dissimilar-matched region, a false-matched region and a miss-matched region. We then performs proper disparity estimation for each type of matched regions. This method minimizes the error in estimating disparity which is caused by inaccurate matching and also improves the accuracy of disparity of the well-matched regions. The experimental results show the improved accuracy of the proposed method.

• Journal of Yeungnam Medical Science
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• v.20 no.2
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• pp.117-128
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• 2003

Thallium-201 scintigraphy is used to discriminate the malignant bone tumor from the benign by qualitatively and quantitatively, and to predict the response of preoperative chemotherapy in osteosarcoma, by comparing the changes of thallium uptake ratio after chemotherapy to the tumor necrosis ratio. Thallium-201 scintigraphy scan should be done prior to surgical biopsy. PICKER Prism 2000 gamma camera with high resolution parallel hole collimator is usually used for scanning. The patient is injected with 2-3mCi of Tl-201 and the early phase is checked in 30 minutes and delayed phase in 3 hours. The scan images are visually evaluated by a blinded nuclear medicine physician. We could evaluate true positive, true negative, false positive and false negative by the comparison of results with those of biopsy, and calculate positive and negative predictive value(%), sensitivity(%), specificity(%) and diagnostic accuracy(%). For the quantitative analysis of thallium uptake, we drew the region of interest on the tumor side and contralateral normal side as mirror image, and calculated the uptake ratio with dividing the amount of gamma count in tumor side by normal side. We could calculate the percent changes of thallium uptake ratio in early and delayed phase, and compare them to the ratio of tumor necrosis. Thallium-201 scintigraphy proved as useful imaging study to discriminate malignant bone tumor from benign, but had exception in giant cell tumor and low grade malignant bone tumors. We can use T1-201 scan to differentiate the benign from the malignant tumor, and to evaluate the response of preoperative chemotherapy or radiotherapy, and to determine the residual tumor or local recurrence. For the better result, we need to have a more detail information about false positive cases and a more objective and quantitative reading technique.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.958-966
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• 2003

Change detection algorithms based on frame difference are frequently used for finding moving objects in image sequences. These algorithms detect the change of frames using estimated statistical background model. But, if this estimated background model is different from the actual statistical distribution, false detections are generated. In this paper, we propose an improved change detection algorithm using euler number and structure tensor. The proposed mapping method which is based on the euler number can be used for reducing the false detections that generated by nonparametric change detection algorithm. In this paper, the change in the region of moving object also can be detected by the proposed method using structure tensor. Experimental result shows that the proposed method reduces the false detections effectively by 90% on "Weather", by 34% on "Mother & daughter" and by 43% on "Aisle" than an existing method does.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.192-198
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• 2018

Recently, the use of drone has been increasing rapidly in many ways. A drone can capture remote objects efficiently so it is suitable for surveillance and security systems. This paper discusses three methods for detecting moving vehicles using a drone. We compare three target detection methods using a background frame, preceding frames, or moving average frames. They are subtracted from a current frame. After the frame subtraction, morphological filters are applied to increase the detection rate and reduce the false alarm rate. In addition, the false alarm region is removed based on the true size of targets. In the experiments, three moving vehicles were captured by a drone, and the detection rate and the false alarm rate were obtained by three different methods and the results are compared.

• Journal of Space Technology and Applications
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• v.3 no.2
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• pp.154-164
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• 2023

In space exploration, spectroscopic observation is useful for understanding objects' composition and physical properties. There are various methods for analyzing spectral data, and there are differences depending on the object and the wavelength. This paper introduces a method for analyzing visible & nearinfrared (VNIR) spectral data, which is mainly applied in lunar exploration. The main analysis methods include false color ratio image processing, reflectance pattern analysis, integrated band depth (IBD) processing, and continuum removal as preprocessing before analysis. These spectroscopic analysis methods help to understand the mineral properties of the lunar surface in the VNIR region and can be applied to other celestial bodies such as Mars.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.17 no.2
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• pp.180-185
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• 1995

TMJ ankylosis is classified with true and false type. A true ankylosis is defined as any condition that produces fibrous or bony adhesions between the articular surfaces of the temporomandibular joint. The main causes of true ankylosis are trauma or infection. A false ankylosis results from pathologic conditions outside the joint that limit mobility of the mandible such as myogenic disorders, coronoid impingement or rare direct bony fusion between maxilla and mandible. The treatment of choice of TMJ ankylosis is surgical intervention. We experienced the male patient with complete mouth opening limitation since 45 years before. This patient has true TMJ ankylosis and rare bony synostosis between maxilla and mandible in the right posterior region. We performed surgical intervention and had a favorable result.