• The Journal of Advanced Prosthodontics
• /
• v.7 no.6
• /
• pp.460-467
• /
• 2015

PURPOSE. The aim of this study is to evaluate the appropriate impression technique by analyzing the superimposition of 3D digital model for evaluating accuracy of conventional impression technique and digital impression. MATERIALS AND METHODS. Twenty-four patients who had no periodontitis or temporomandibular joint disease were selected for analysis. As a reference model, digital impressions with a digital impression system were performed. As a test models, for conventional impression dual-arch and full-arch, impression techniques utilizing addition type polyvinylsiloxane for fabrication of cast were applied. 3D laser scanner is used for scanning the cast. Each 3 pairs for 25 STL datasets were imported into the inspection software. The three-dimensional differences were illustrated in a color-coded map. For three-dimensional quantitative analysis, 4 specified contact locations(buccal and lingual cusps of second premolar and molar) were established. For two-dimensional quantitative analysis, the sectioning from buccal cusp to lingual cusp of second premolar and molar were acquired depending on the tooth axis. RESULTS. In color-coded map, the biggest difference between intraoral scanning and dual-arch impression was seen (P<.05). In three-dimensional analysis, the biggest difference was seen between intraoral scanning and dual-arch impression and the smallest difference was seen between dual-arch and full-arch impression. CONCLUSION. The two- and three-dimensional deviations between intraoral scanner and dual-arch impression was bigger than full-arch and dual-arch impression (P<.05). The second premolar showed significantly bigger three-dimensional deviations than the second molar in the three-dimensional deviations (P>.05).

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.12
• /
• pp.219-228
• /
• 2012

In this paper, we propose a paper keyboard piano implementation using the finger movement detection with the 3D image data from a kinect. Keyboard pattern and keyboard depth information are extracted from the color image and depth image to detect the touch event on the paper keyboard and to identify the touched key. Hand region detection error is unavoidable when using the simple comparison method between input depth image and background depth image, and this error is critical in key touch detection. Skin color is used to minimize the error. And finger tips are detected using contour detection with area limit and convex hull. Finally decision of key touch is carried out with the keyboard pattern information at the finger tip position. The experimental results showed that the proposed method can detect key touch with high accuracy. Paper keyboard piano can be utilized for the easy and convenient interface for the beginner to learn playing piano with the PC-based learning software.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.11
• /
• pp.529-536
• /
• 2015

When rendering both three-dimensional objects and photo images together, the non-photorealistic rendering results are in visual discord since the two contents have their own independent color distributions. This paper proposes a non-photorealistic rendering technique which renders both three-dimensional objects and photo images such as cartoons and sketches. The proposed technique computes the color distribution property of the photo images and reduces the number of colors of both photo images and 3D objects. NPR is performed based on the reduced colormaps and edge features. To enhance the natural scene presentation, the image region segmentation process is preferred when extracting and applying colormaps. However, the image segmentation technique needs a lot of computational operations. It takes a long time for non-photorealistic rendering for large size frames. To speed up the time-consuming segmentation procedure, we use GPGPU for the parallel computing using the GPU. As a result, we significantly improve the execution speed of the algorithm.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.8
• /
• pp.301-310
• /
• 2021

The TATI model is a Traffic Accident Text to RGB Image model, which is a methodology proposed in this paper for predicting the severity of traffic accidents. Traffic fatalities are decreasing every year, but they are among the low in the OECD members. Many studies have been conducted to reduce the death rate of traffic accidents, and among them, studies have been steadily conducted to reduce the incidence and mortality rate by predicting the severity of traffic accidents. In this regard, research has recently been active to predict the severity of traffic accidents by utilizing statistical models and deep learning models. In this paper, traffic accident dataset is converted to color images to predict the severity of traffic accidents, and this is done via CNN models. For performance comparison, we experiment that train the same data and compare the prediction results with the proposed model and other models. Through 10 experiments, we compare the accuracy and error range of four deep learning models. Experimental results show that the accuracy of the proposed model was the highest at 0.85, and the second lowest error range at 0.03 was shown to confirm the superiority of the performance.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.19 no.6
• /
• pp.105-112
• /
• 2009

Nowadays, completely automated public turing tests to tell computers and humans apart(CAPTCHAs) are widely used to prevent various attacks by automated software agents such as creating accounts, advertising, sending spam mails, and so on. In early CAPTCHAs, the characters were simply distorted, so that users could easily recognize the characters. From that reason, using various techniques such as image processing, artificial intelligence, etc., one could easily break many CAPTCHAs, either. As an alternative, By adding noise to CAPTCHAs and distorting the characters in CAPTCHAs, it made the attacks to CAPTCHA more difficult. Naturally, it also made users more difficult to read the characters in CAPTCHAs. To improve the readability of CAPTCHAs, some CAPTCHAs used different colors for the characters. However, the usage of the different colors gives advantages to the adversary who wants to break CAPTCHAs. In this paper, we suggest a method of increasing the recognition ratio of CAPTCHAs based on colors.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.2
• /
• pp.83-90
• /
• 2023

Blurred image is an important factor in lowering image recognition rates in Computer vision. This mainly occurs when the camera is unstablely out of focus or the object in the scene moves quickly during the exposure time. Blurred images greatly degrade visual quality, weakening visibility, and this phenomenon occurs frequently despite the continuous development digital camera technology. In this paper, it replace the modified building module based on the Deep multi-patch neural network designed with convolution neural networks to capture details of input images and Attention techniques to focus on objects in blurred images in many ways and strengthen the image. It measures and assigns each weight at different scales to differentiate the blurring of change and restores from rough to fine levels of the image to adjust both global and local region sequentially. Through this method, it show excellent results that recover degraded image quality, extract efficient object detection and features, and complement color constancy.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.19 no.1
• /
• pp.217-224
• /
• 2024

With the rapid growth of K-POP, the dance content industry is spreading. With the recent increase in the spread of SNS, they also shoot and share their dance videos. However, it is not easy for dance beginners who are new to dancing to learn dance moves because it is difficult to receive objective feedback when dancing alone while watching videos. This paper describes a system that uses MediaPipe to compare choreography videos and dance videos of users and detect whether they are following the movement correctly. This study proposes a method of giving feedback based on Color Map to users by calculating the similarity of dance movements between user images taken with webcam or camera and choreography images using cosine similarity and COCO OKS. Through this system, objective feedback on users' dance movements can be visually received, and beginners are expected to be able to learn accurate dance movements.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.7
• /
• pp.816-822
• /
• 2016

Content-Based image retrieval is a method to search by image features such as local color, texture, and other image content information, which is different from conventional tag or labeled text-based searching. In real life data, the number of images having tags or labels is relatively small, so it is hard to search the relevant images with text-based approach. Existing image search method only based on image feature similarity has limited performance and does not ensure that the results are what the user expected. In this study, we propose and validate a machine learning based approach to improve the performance of the image search engine. We note that when users search relevant images with a query image, they would expect the retrieved images belong to the same category as that of the query. Image classification method is combined with the traditional image feature similarity method. The proposed method is extensively validated on a public PASCAL VOC dataset consisting of 11,530 images from 20 categories.

• The Bulletin of The Korean Astronomical Society
• /
• v.41 no.2
• /
• pp.48.2-48.2
• /
• 2016

The wide-field and the round-the clock operation capabilities of the KMTNet enables the discovery, astrometry and follow-up physical characterization of asteroids and comets in a most efficient way. We collectively refer to the team members, partner organizations, the dedicated software subsystem, the computing facility and research activities as Deep Ecliptic Patrol of the Southern Sky (DEEP-South). Most of the telescope time for DEEP-South is devoted to targeted photometry of Near Earth Asteroids (NEAs) to push up the number of the population with known physical properties from several percent to several dozens of percent, in the long run. We primarily adopt Johnson R-band for lightcurve study, while we employ BVI filters for taxonomic classification and detection of any possible color variations of an object at the same time. In this presentation, the progress and new findings since the last KAS meeting will be outlined. We report DEEP-South preliminary lightcurves of several dozens of NEAs obtained at three KMTNet stations during the first year runs. We also present a physical model of asteroid (5247) Krylov, the very first Non principal Axis (NPA) rotator that has been confirmed in the main belt (MB). A new asteroid taxonomic classification scheme will be introduced with an emphasis on its utility in the LSST era. The progress on the current version of automated mover detection software will also be summarized.

• Journal of Broadcast Engineering
• /
• v.17 no.4
• /
• pp.676-683
• /
• 2012

Motion estimation in video coding greatly affects implementation complexity. In this paper, a reducing method of the complexity in motion estimation is proposed by using both the depth and color cameras. We obtain object information with video sequence from distance information calculated by depth camera, then perform labeling for grouping pixels within similar distances as the same object. Three search regions (background, inside-object, boundary) are determined adaptively for each of motion estimation blocks within current and reference pictures. If a current block is the inside-object region, then motion is searched within the inside-object region of reference picture. Also if a current block is the background region, then motion is searched within the background region of reference picture. From simulation results, we can see that the proposed method compared to the full search method remains the almost same as the motion estimated difference signal and significantly reduces the searching complexity.