• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.360-362
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• 2009

In this paper, we studied for the real-time azimuthal measurement of HMD(Head Mounted Display) using the feature points detection to control the tele-operated vision system on the mobile robot. To give the sense of presence to the tele-operator, we used a HMD to display the remote scene, measured the rotation angle of the HMD on a real time basis, and transmitted the measured rotation angles to the mobile robot controller to synchronize the pan-tilt angles of remote camera with the HMD. In this paper, we suggest an algorithm for the real-time estimation of the HMD rotation angles using feature points extraction from pc-camera image.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.199-205
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• 2011

This paper presents a QR decomposition processor by exploiting Givens rotation for the GDFE (Generalized Decision Feedback Equalizer). A Givens rotation consists of phase extraction, sine/cosine generation and angle rotation parts. Combining two-stage method (coarse and fine stage) and the fixed-width modified-Booth multiplier, we design an efficient QR decomposition processor. By simulations, it is shown that the proposed QR decomposition processor can be a feasible solution for GDFE.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.509-516
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• 2002

This paper proposes an efficient algorithm which recognizes the mixed document image consisting of the images, texts, tables, and straight lines. This system is composed of three steps. The first step is the detection of rotation angle for complementing skewed images, the second is detection of erasing an unnecessary background region and last is the classification of each component included in document images. This algorithm performs preprocessing of detecting rotation angles and correcting documents based on the detected rotation angles in order to minimize the error rate by skewness of the documentation. We detected the rotation angie using only horizontal and vertical components in document images and minimized calculation time by erasing unnecessary background region in the detecting process of component of document. In the next step, we classify various components such as image, text, table and line area included in document images. we applied this method to various document images in order to evaluate the performance of document recognition system and show the successful experimental results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.605-613
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• 2009

In this paper, we studied for the real-time azimuthal measurement of HMD (Head Mounted Display) to control the tele-operated vision system on the mobile robot. In the preexistence tele-operated vision system, a joystick was used to control the pan-tilt unit of the remote camera system. To give the sense of presence to the tele-operator, we used a HMD to display the remote scene, measured the rotation angle of the HMD on a real time basis, and transmitted the measured rotation angles to the mobile robot controller to synchronize the pan-tilt angles of remote camera with the HMD. In this paper, we suggest an algorithm for the real-time estimation of the HMD rotation angles using feature points extraction from pc-camera image. The simple experiment is conducted to demonstrate the feasibility.

• Fisheries and Aquatic Sciences
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• v.4 no.1
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• pp.1-9
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• 2001

This paper describes a procedure extracting feature vector of a target cell more precisely in the case of identifying specified cell. The classification of object type is based on feature vector such as area, complexity, centroid, rotation angle, effective diameter, perimeter, width and height of the object So, the feature vector plays very important role in classifying objects. Because the feature vectors is affected by noises and holes, it is necessary to remove noises contaminated in original image to get feature vector extraction exactly. In this paper, we propose the following method to do to get feature vector extraction exactly. First, by Otsu's optimal threshold selection method and morphological filters such as cleaning, filling and opening filters, we separate objects from background an get rid of isolated particles. After the labeling step by 4-adjacent neighborhood, the labeled image is filtered by the area filter. From this area-filtered image, feature vector such as area, complexity, centroid, rotation angle, effective diameter, the perimeter based on chain code and the width and height based on rotation matrix are extracted. To prove the effectiveness, the proposed method is applied for yeast Zygosaccharomyces rouxn. It is also shown that the experimental results from the proposed method is more efficient in measuring feature vectors than from only Otsu's optimal threshold detection method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.3
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• pp.217-226
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• 2003

A novel fingerprint ridge feature extraction using sequential labeling of thinned fingerprint image is proposed, which is invariant to position translation, scaling, and rotation. the proposed algorithm labels ridges of thinned fingerprint image sequentially using vertical line that goes through fingerprint core point. Then, we extract a feature from each labeled ridge and the extraction process is based on the type fo the ridge and a minutiae ridge angle in the ridge. The feature extracted through this process enables us to find out the kind of various minutiae and minutiae angle. As a result of the experiment using two thinned fingerprint images, we finally confirm that proposed algorithm is not related to position translation, scaling, and rotation.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.73-77
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• 2012

This paper reports a combined depth- and model-based face detection and tracking approach. The proposed algorithm consists of four functional modules; i) color-based candidate region extraction, ii) generation of the depth histogram for handling occlusion, iii) rotation-invariant face region detection using ellipse fitting, and iv) face tracking based on motion prediction. This technique solved the occlusion problem under complicated environment by detecting the face candidate region based on the depth-based histogram and skin colors. The angle of rotation was estimated by the ellipse fitting method in the detected candidate regions. The face region was finally determined by inversely rotating the candidate regions by the estimated angle using Haar-like features that were robustly trained robustly by the frontal face.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.118-125
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• 2016

This study evaluates the performance of image to patient registration algorithm by using stereo vision and CT image for facial region surgical navigation. For the process of image to patient registration, feature extraction and 3D coordinate calculation are conducted, and then 3D CT image to 3D coordinate registration is conducted. Of the five combinations that can be generated by using three facial feature extraction methods and three registration methods on stereo vision image, this study evaluates the one with the highest registration accuracy. In addition, image to patient registration accuracy was compared by changing the facial rotation angle. As a result of the experiment, it turned out that when the facial rotation angle is within 20 degrees, registration using Active Appearance Model and Pseudo Inverse Matching has the highest accuracy, and when the facial rotation angle is over 20 degrees, registration using Speeded Up Robust Features and Iterative Closest Point has the highest accuracy. These results indicate that, Active Appearance Model and Pseudo Inverse Matching methods should be used in order to reduce registration error when the facial rotation angle is within 20 degrees, and Speeded Up Robust Features and Iterative Closest Point methods should be used when the facial rotation angle is over 20 degrees.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.17-24
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• 2015

In this paper, a novel scheme for correcting rotated region in medical images using SIFT(Scale Invariant Feature Transform) algorithm is presented. Using the feature extraction function of SIFT, the rotation angle of rotated object in medical images is calculated as follows. First, keypoints of both reference and rotated medical images are extracted by SIFT. Second, the matching process is performed to the keypoints located at the predetermined ROI(Region Of Interest) at which objects are not cropped or added by rotating the image. Finally, degrees of matched keypoints are calculated and the rotation angle of the rotated object is determined by averaging the difference of the degrees. The simulation results show that the proposed scheme has excellent performance for correcting the rotated region in medical images.

• The Journal of the Korean dental association
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• v.16 no.4 s.107
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• pp.273-278
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• 1978

A girl aged 16 years and I month, had a severe Angle's class III malocclusion, characterized by a retarded and constricted maxilla, anterior and posterior crossbite. This patient underwent extraction of two lower Ist premolar. After extraction, author placed multibanded system in lower dental arch to change the long axis of anterior teeth and delivered removable appliance with Coffin spring in the upper dental arch to expand dental arch. After 13 months, anterior & posterior crossbite was corrected and this patient's profile was improved. Superimposition of pretreatment and posttreatment cephalograms upon the SN line registered at S showed backward downward rotation of the mandible and retrusion of lower lip.