• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.3
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• pp.397-405
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• 2024

In order to improve the visibility of nighttime thermal infrared images, a simulation method with daytime color images was proposed. As a simulation method consisting of two steps, the daytime thermal infrared image was simulated by learning the unpaired nighttime thermal infrared image and daytime thermal infrared image, then the result was translated into a daytime color image. A temperature change regression equation was constructed and applied to reflect the systematic characteristics of temperature changes in daytime and nighttime images, and day and night simulation and colorization were trained and modeled by CycleGAN. For the experimental area, 100 images were captured and used for training. As a result, the simulation showed an average SSIM of 0.2449 and a PSNR of 51.2254. It was confirmed that the method could simulate complex and detailed features such as vegetation.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.40 no.3
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• pp.103-110
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• 2014

Objectives: In this study, we assessed soft tissue asymmetry that occurred after open reduction of unilateral zygomaticomaxillary complex (ZMC) fractures. We proposed a simple method to assess soft tissue asymmetry after reduction surgery by evaluating the symmetry between the affected and the unaffected sides. The factors affecting soft tissue contour after surgery were also analyzed. Materials and Methods: Subjects included patients admitted to Wonkwang University Dental Hospital from 2008 to 2013. Cone-beam computed tomography (CBCT) images of asymmetric patients who underwent open reduction at least 3 months prior were compared with healthy patients. Results: The degree of asymmetry was measured in both the open reduction and control groups. Landmarks that showed a statistically significant difference between the two groups were zygion ($1.73{\pm}0.24mm$), bucclae ($1.08{\pm}0.26mm$), point of cheek ($2.05{\pm}0.33mm$) and frontozygomatic point ($1.30{\pm}0.31mm$). Conclusion: When compared with the normal group, asymmetry can occur in the affected side, which usually shows depression of overlying soft tissue and is statistically significantly different. Evaluation of soft tissue asymmetry with CBCT images after open reduction of ZMC fracture is useful.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.5
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• pp.29-37
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• 2009

This paper describes a vision-based and real-time system for detecting road signs from within a moving vehicle. The proposed system has the standard architecture with adaboost algorithm to detect road signs in real time. And it uses the value of vortical plane in the process of extracting candidate areas in view of fact that there are vertically most of signs on roads. Although being useful for detecting objects in real time, the conventional adaboost algorithm deteriorates the performance of detection rate in complex circumstance by reason of using only integral images as features. To overcome this problem, this paper proposes the method that improves the reliability of candidates as using the value of vertical plane for extracting candidate area and improves the performance of the detection rate as using integral images to which we add the kind of feature prototype. The experiments of this paper show that the detection rate of the proposed method has higher than that of the conventional adaboost algorithm under the real complex circumstance of roads.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.140-148
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• 2004

Natural images can be classified into edge or flat region. Edges have also various shapes such as long edge, texture and so on. Because the conventional deinterlacing methods commonly use one specific algorithm, they are faced with the difficulty that does not adapt various shapes of images. In this paper, a selective deinterlacing method based on the characteristics of local region of image is proposed. An input image is classified into three regions; flat region, complex edge, long edge. And then for each region, the proper method is assigned according to the characteristic of the local feature. For long edge region, the modified $NEDI(New Edge Directed Interpolation)^{[1]}$ method that interpolates long edge very well is used. The linear $filter^{[2]}$ that enhances high frequency components is used for complex edge, and the bilinear interpolation method is applied to flat region. The proposed method shows improved performance in PSNR and subjective evaluation compared with previous algorithms.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.42 no.5
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• pp.278-283
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• 2016

Objectives: The maxillary sinus mucosa is reported to recover to preoperative sterility after sinus floor elevation. However, when drainage of maxillary sinus is impaired, recovery can be delayed and maxillary sinusitis can occur. Therefore, in this study, we investigated the correlations between anatomic variants that can interrupt the ostium of the maxillary sinus and incidence of complication after sinus lifting. Materials and Methods: The subjects are 81 patients who underwent sinus lifting in Wonkwang University Dental Hospital (Iksan, Korea). Computed tomography (CT) images of the subjects were reviewed for presence of nasal septum deviation, anatomic variants of the middle turbinate, and Haller cells. Correlations between anatomic variations and occurrence of maxillary sinusitis were statistically analyzed. Results: Patients with anatomic variants of ostio-meatal units, such as deviated nasal septum, concha bullosa or paradoxical curvature of the middle turbinate, or Haller cells, showed a higher rate of complication. However, only presence of Haller cell showed statistically significant. Conclusion: Before sinus lifting, CT images are recommended to detect anatomic variants of the ostio-meatal complex. If disadvantageous anatomic variants are detected, the use of nasal decongestants should be considered to reduce the risk of postoperative sinusitis.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.357-365
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• 2005

We present a B-spline fitting method based on genetic algorithm for the extraction of object contours from the complex image sequence, where objects with similar shape and intensity are adjacent each other. The proposed algorithm solves common malfitting problem of the existing B-spline fitting methods including snakes. Classical snake algorithms have not been successful in such an image sequence due to the difficulty in initialization and existence of multiple extrema. We propose a B-spline fitting method using a genetic algorithm with a new initial population generation and fitting function, that are designed to take advantage of the contour of the previous slice. The test results show that the proposed method extracts contour of individual object successfully from the complex image sequence. We validate the algorithm by false-positive/negative errors and relative amounts of agreements.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.1149-1152
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• 2005

Detecting faces in images with complex backgrounds is a difficult task. Our approach, which obtains state of the art results, is based on a generative neural network model: the Constrained Generative Model (CGM). To detect side view faces and to decrease the number of false alarms, a conditional mixture of networks is used. To decrease the computational time cost, a fast search algorithm is proposed. The level of performance reached, in terms of detection accuracy and processing time, allows to apply this detector to a real word application: the indexation of face images on the Web.

• Restorative Dentistry and Endodontics
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• v.43 no.2
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• pp.16.1-16.9
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• 2018

Objectives: Understanding the reason for an unsuccessful non-surgical endodontic treatment outcome, as well as the complex anatomy of the root canal system, is very important. This study examined the cross-sectional root canal structure of mandibular first molars confirmed to have failed non-surgical root canal treatment using digital images obtained during intentional replantation surgery, as well as the causative factors of the failed conventional endodontic treatments. Materials and Methods: This study evaluated 115 mandibular first molars. Digital photographic images of the resected surface were taken at the apical 3 mm level and examined. The discolored dentin area around the root canal was investigated by measuring the total surface area, the treated areas as determined by the endodontic filling material, and the discolored dentin area. Results: Forty 2-rooted teeth showed discolored root dentin in both the mesial and distal roots. Compared to the original filled area, significant expansion of root dentin discoloration was observed. Moreover, the mesial roots were significantly more discolored than the distal roots. Of the 115 molars, 92 had 2 roots. Among the mesial roots of the 2-rooted teeth, 95.7% of the roots had 2 canals and 79.4% had partial/complete isthmuses and/or accessory canals. Conclusions: Dentin discoloration that was not visible on periapical radiographs and cone-beam computed tomography was frequently found in mandibular first molars that failed endodontic treatment. The complex anatomy of the mesial roots of the mandibular first molars is another reason for the failure of conventional endodontic treatment.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.735-740
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• 2022

The construction is the industry with the highest fatalities, and the fatalities has not decreased despite various institutional improvements. Accordingly, real-time safety management by applying artificial intelligence (AI) to CCTV images is emerging. Although some research on worker detection by applying AI to images of construction sites is being conducted, there are limitations in performance expression due to problems such as complex background due to the nature of the construction industry. In this study, the YOLO model and the OpenPose model were fused to improve the performance of worker detection and posture estimation to improve the detection performance of workers in various complex conditions. This is expected to be highly useful in terms of unsafe behavior and health management of workers in the future.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.83-92
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• 2009

In this paper, an extended snake algorithm using color variance energy is proposed for segmenting an interest object in color image. General snake algorithm makes use of energy in image to segment images into a interesting area and background. There are many kinds of energy that can be used by the snake algorithm. The efficiency of the snake algorithm is depend on what kind of energy is used. A general snake algorithm based on active contour model uses the intensity value as an image energy that can be implemented and analyzed easily. But it is sensitive to noises because the image gradient uses a differential operator to get its image energy. And it is difficult for the general snake algorithm to be applied on the complex image background. Therefore, the proposed snake algorithm efficiently segment an interest object on the color image by adding a color variance of the segmented area to the image energy. This paper executed various experiments to segment an interest object on color images with simple or complex background for verifying the performance of the proposed extended snake algorithm. It shows improved accuracy performance about 12.42 %.