• The Journal of Korean Academy of Prosthodontics
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• v.59 no.1
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• pp.79-87
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• 2021

The digital workflow of optical impressions by the intraoral scanner and CADCAM manufacture of dental prostheses is actively developing. The complex process of traditional impression taking, definite cast fabrication, wax pattern making, and casting has been shortened, and the number of patient's visits can also be reduced. Advances in intraoral scanner technology have increased the precision and accuracy of optical impression, and its indication is progressively widened toward the long span fixed dental prosthesis. This case report describes the long span implant case, and the operator fully utilized digital workflow such as computer-guided implant surgical template and CAD-CAM produced restoration after the digital impression. The provisional restoration and customized abutments were prepared with the optical impression taken on the same day of implant surgery. Moreover, the final prosthesis was fabricated with the digital scan while utilizing the same customized abutment from the provisional restoration. During the data acquisition step, stl data of customized abutments, previously scanned at the time of provisional restoration delivery, were imported and automatically aligned with digital impression data using an 'A.I. abutment matching algorithm' the intraoral scanner software. By using this algorithm, it was possible to obtain the subgingival margin without the gingival retraction or abutment removal. Using the digital intraoral scanner's advanced functions, the operator could shorten the total treatment time. So that both the patient and the clinician could experience convenient and effective treatment, and it was possible to manufacture a prosthesis with predictability.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.225-232
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• 2009

In this paper, a new face detection method based on pupil color distribution maps with the frequency under the illumination variance is proposed. Face-like regions are first extracted by applying skin color distribution maps to a color image and then, they are reduced by using the standard deviation of chrominance components. In order to search for eye candidates effectively, the proposed method extracts eye-like regions from face-like regions by using pupil color distribution maps. Furthermore, the proposed method is able to detect eyes very well by segmenting the eye-like regions, based on a lighting compensation technique and a segmentation algorithm even though face regions are changed into dark-tone due to varying illumination conditions. Eye candidates are then detected by means of template matching method. Finally, face regions are detected by using the evaluation values of two eye candidates and a mouth. Experimental results show that the proposed method can achieve a high performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1162-1170
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• 2014

In this paper, an accurate remote gaze tracking method with two cameras is presented using a modified Starburst algorithm and honography normalization. Starburst algorithm, which was originally developed for head-mounted systems, often fails in detecting accurate pupil centers in remote tracking systems with a larger field of view due to lots of noises. A region of interest area for pupil is found using template matching, and then only within this area Starburst algorithm is applied to yield pupil boundary candidate points. These are used in improved RANSAC ellipse fitting to produce the pupil center. For gaze estimation robust to head movement, an improved homography normalization using four LEDs and calibration based on high order polynomials is proposed. Finally, it is shown that accuracy and robustness of the system is improved using two cameras rather than one camera.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.17-24
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• 2018

Military camera equipment has a problem that observability is inferior due to various shaking factors. In this paper, we propose an image stabilization algorithm considering performance and execution time to solve this problem and implemented it in Zynq SoC. We stabilized both the simple shaking in the fixed observation position and the sudden shaking in the moving observation position. The feature of the input image is extracted by the Sobel edge algorithm, the subblock with the large edge data is selected, and the motion vector, which is the compensation reference, is calculated through template matching using the 3-step search algorithm of the region of interest. In addition, the proposed algorithm can distinguish the shaking caused by the simple shaking and the movement by using the Kalman filter, and the stabilized image can be obtained by minimizing the loss of image information. To demonstrate the effectiveness of the proposed algorithm, experiments on various images were performed. In comparison, PSNR is improved in the range of 2.6725~3.1629 (dB) and image loss is reduced from 41% to 15%. On the other hand, we implemented the hardware-software integrated design using HLS of Xilinx SDSoC tool and confirmed that it operates at 32 fps on the Zynq board, and realized SoC that operates with real-time processing.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.70-79
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• 2017

This study proposes a method to quickly and accurately acquire distance information on direction signs. The proposed method is composed of the recognition of the sign, pre-processing to facilitate the acquisition of the road sign distance, and the acquisition of the distance data. The road sign recognition uses color detection including gamma correction in order to mitigate various noise issues. In order to facilitate the acquisition of distance data, this study applied tilt correction using linear factors, and resolution correction using Fourier transform. To acquire the distance data, morphological operation was used to highlight the area, along with labeling and template matching. By acquiring the distance information on the direction sign through such a processes, the proposed system can be output the distance remaining to the next junction. As a result, when the proposed method is applied to system it can process the data in real-time using the fast calculation speed, average speed was shown to be 0.46 second per frame, with accuracy of 0.65 in similarity value.

• Journal of Korea Multimedia Society
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• v.12 no.5
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• pp.633-643
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• 2009

We propose a color transfer method that used color contrast based templates to express the visual difference clearly between objects, while remaining the quality of the input image. Our algorithm employs colors of both the input image and template distributed on the $a^{\ast}b^{\ast}$chrominance plane of CIE $L^{\ast}a^{\ast}b^{\ast}$color space. The templates are made by considering the effect of color contrast and have the shape of either a line or a curve represented color distribution of the basic colors based gradation image. These tempates can be modeled on spline curves. We also generate simply new templates with the different basic colors by moving the control points of that curve. The color transfer method using the templates is done through a regressive analysis and color matching. We maintained color coherence of the input image by transforming similarly the color distribution of an input image to the one of templates.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.773-779
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• 2003

Locating exact position of facial components is a key preprocessing for realizing highly accurate and reliable face recognition schemes. In this paper, we propose a simple but powerful method for detecting isolated facial components such as eyebrows, eyes, and a mouth, which are horizontally oriented and have relatively dark gray levels. The method is based on the shape-resolving locally optimum thresholding that may guarantee isolated detection of each component. We show that pure facial regions can be determined by grouping facial features satisfying simple geometric constraints on unique facial structure. In the test for over 1000 images in the AR -face database, pure facial regions were detected correctly for each face image without wearing glasses. Very few errors occurred in the face images wearing glasses with a thick frame because of the occluded eyebrow -pairs. The proposed scheme may be best suited for the later stage of classification using either the mappings or a template matching, because of its capability of handling rotational and translational variations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.5169-5175
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• 2013

We present a framework for 3D hand gesture design and modeling. We adapted two different pattern matching techniques, Dynamic Time Warping (DTW) and Hidden Markov Models (HMMs), to support the registration and evaluation of 3D hand gestures as well as their recognition. One key ingredient of our framework is a concept for the convenient gesture design and registration using HMMs. DTW is used to recognize hand gestures with a limited training data, and evaluate how the performed gesture is similar to its template gesture. We facilitate the use of visual sensors and body sensors for capturing both locative and inertial gesture information. In our experimental evaluation, we designed 18 example hand gestures and analyzed the performance of recognition methods and gesture features under various conditions. We discuss the variability between users in gesture performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.367-370
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• 2015

This paper proposes an improve method of the detection performance of traffic lights for autonomous driving cars. Earlier detection methods used to adopt color thresholding, template matching and based learning maching methods, but its have some problems such as recognition rate decreasing, slow processing time. The proposed method uses both detection mask and morphological preprocessing. Firstly, input color images are converted to YCbCr image in order to strengthen its illumination, and horizontal edge components are extracted in the Y Channel. Secondly, the region of interest is detected according to morphological characteristics of the traffic lights. Finally, the traffic signal is detected based on color distributions. The proposed method showed that the detection rate and processing time improved rather than the conventional algorithm about some surrounding environments.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.24-30
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• 2001

This article is concerned with automatic segmentation for Korean speech signals. All kinds of transition cases of phonetic units are classified into 3 types and different strategies for each type are applied. The type 1 is the discrimination of silence, voiced-speech and unvoiced-speech. The histogram analysis of each indicators which consists of wavelet coefficients and SVF (Spectral Variation Function) in wavelet coefficients are used for type 1 segmentation. The type 2 is the discrimination of adjacent vowels. The vowel transition cases can be characterized by spectrogram. Given phonetic transcription and transition pattern spectrogram, the speech signal, having consecutive vowels, are automatically segmented by the template matching. The type 3 is the discrimination of vowel and voiced-consonants. The smoothed short-time RMS energy of Wavelet low pass component and SVF in cepstral coefficients are adopted for type 3 segmentation. The experiment is performed for 342 words utterance set. The speech data are gathered from 6 speakers. The result shows the validity of the method.