• Physical Therapy Rehabilitation Science
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• v.6 no.4
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• pp.164-169
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• 2017

Objective: This research investigated the effects of simple visual imagery and mental rotation imagery on neural activity of adults who are at high risk of smart phone addiction by measuring their electroencephalography (EEG). Design: Cross-sectional study. Methods: Thirty people with a high risk of smart phone addiction was selected and then were evaluated for their neural activation patterns using EEG after reminding them about simple visual imagery and mental rotation imagery. A simple visual image was applied for 20 seconds using a smartphone. This was followed by a resting period of 20 seconds. Mental rotation imagery was applied for 20 seconds. During mental rotation imagery, the rotational angle was selected at random. We compared activation patterns according to the analyzed EEG with hemisphere reminding them about imagery. Results: On the EEG, theta rhythm from the left hemisphere parietal area increased when the subjects were reminded of mental rotation imagery, and sensorimotor rhythm from close to the left hemisphere area increased when the subjects were reminded of simple visual imagery. Conclusions: Neural activation from the left hemisphere occurs for motor imagery in adults who are at high risk of smart phone addiction. These results identify a neural mechanism of adults who a have high risk of smart phone addiction, which may provide contribute to the development of motor rehabilitation for smartphone users.

• The Academic Congress of Korean Shoulder and Elbow Society
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• 2009.03a
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• pp.175-175
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• 2009

Despite its importance for the understanding of joint kinematics in vivo, there has been few studies about shoulder joints. The purpose of this study is to analyze the glenohumeral joint during internal and external rotation at 90 degrees of abduction using in vivo noninvasive motion analysis system. MRI was performed for the following seven positions from maximum internal rotation to maximum external rotation at intervals of 30 degrees. We used 3D-gradient echo sequencing (TR: 12 ms, TE: 5.8 ms, 0.8 mm-slice thickness). Our method is based on matching three-dimensional MR images by the similarity of the image intensity. We analyzed the in vivo three-dimensional motions of the glenohumeral and scapulothoracic joint during this motion. In scapla plane, the mean rotation angle of the glenohumeral join was 105.5 degrees ($SD{\pm}39.0^{\circ}$). The mean rotation angle of the scapulothracic joint was 27.5 degrees ($SD\;{\pm}\;7.7^{\circ}$). The contribution ratio is almost 3.8:1 of glenohumeral and scapulothracic joint respectively.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1341-1348
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• 2012

In this paper, an efficient scheme for correcting rotated objects in medical images using the Mojette transform is presented. The Mojette transform is a kind of discrete Radon transform, where the transform domain is represented by a set of projections. The Mojette transform currently studied in the image compression area is modified for detecting the rotation angle of objects in medical images. First, in order to find accurate rotation angle, the projection value in the Mojette transform is determined by using pixels on the projection line and in addition the linear interpolation of pixels adjacent to the line. Second, at each projection angle, only one projection is implemented for reducing the amount of the calculation in the process of the Mojette transform. Finally, the projection in the Mojette transform is carried out at the predetermined ROI(Region Of Interest) at which the objects are not cropped or added by rotating the image. The simulation results show that the proposed method has good performance for correcting the rotation angle in medical images.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.4
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• pp.397-403
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• 2015

In this paper, a method of ISAR geometric calibration is represented by using impulse-radio UWB radar. The ir-UWB is good for using a signal processing in time domain, so, it does not occur a multi-path or coupling problem. If a signal that between antennas and target is assumed a plane wave, a center of rotation in ISAR geometry model can be estimated by using point target. Before image is reconstructed with sinogram, the center of rotation can be calculated by using least square fitting. This method can be obtained a more contrast image, and a maximum value of entropy of image. The method, that estimates a center of rotation in received data, will be used a initial setup of instruments or a periodic compensation to reconstruct image. It would be useful in medical, security and surveillance imaging equipments that have a fixed geometry.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.34-40
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• 2023

A smart business card printing system that automatically prints business cards requested by customers online is being activated. What matters is that the business card submitted by the customer to the system may be abnormal. This paper deals with the problem of determining whether the image of a business card has been abnormally rotated by adopting artificial intelligence technology. It is assumed that the business card rotates 0 degrees, 90 degrees, 180 degrees, and 270 degrees. Experiments were conducted by applying existing VGG, ResNet, and DenseNet artificial neural networks without designing special artificial neural networks, and they were able to distinguish image rotation with an accuracy of about 97%. DenseNet161 showed 97.9% accuracy and ResNet34 also showed 97.2% precision. This illustrates that if the problem is simple, it can produce sufficiently good results even if the neural network is not a complex one.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1834-1843
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• 2000

In this paper, we propose a modular neural network based classification method for handwritten numerals utilizing rotated and translated images of an input image. The whole numeral pattern space is divided into smaller spaces which overlap each other and form multiple clusters. On these multiple clusters, multiple multilayer perceptrons (MLP) neural networks, specialized in those clusters, are constructed. Thus, each MLP acts as an expert network on the corresponding cluster. An MLP is also used as a gating network functioning as a mediator among the multiple MLPs. In the learning phase, an input numeral image is dithered by tow geometric operations of translation and rotation so that new numeral images similar to original one are generated. In the recognition phase, we utilize not only input numeral image, but also nearly generated images through the rotation and the translation of the original image. Thus, multiple output values for those generated images were combined to make class decision by various combination methods. The experimental results confirm the validity of the proposed method.

• Journal of Korea Multimedia Society
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• v.8 no.9
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• pp.1195-1207
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• 2005

In this paper, we describe image matching techniques which is automatically retrieving the exact matching area using geometry-phase information. We proposed a Matching Method which is rapidly estimating the correspondent points between adjacent images that included big-rotation and top-bottom movement element. It is a method that reduce computation quantity to be required to find an exact correspondent position using geometry-phase information of extracted points in images and DT map which set the distance value among feature points and other points on the basis of each feature point of a image. The proposed method shows good performance especially in the part to search a exact correspondent position between adjacent images that included big-rotation and top-bottom movement element.

• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.94-99
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• 2003

In this paper, a rotation invariant fingerprint identification system is implemented using the circular harmonic filter and phase only correlator. We extracted the phase component from input fingerprint image and correlate it with the circular harmonic filter of the reference fingerprint image by POC. The input image is obtained using a prism operating in the internal full reflection mode. Then the input image is transformed to two dimensional Fourier spectrum in optical way and the phase component is extracted using a digital system from the spectrum. Because composed of the optical system and digital algorithm, the proposed system has the advantages of the two technologies such as realtime parallel processing property of the optics and the flexibility of the digital system.

• Journal of KIISE
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• v.42 no.10
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• pp.1185-1194
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• 2015

A spherical panoramic image does not conform to the pin-hole camera model, and, hence, it is not possible to utilize previous techniques consisting of plane-to-plane transformation. In this paper, we propose a new method to estimate the planar geometric transformation between the planar image and a spherical panoramic image. Our proposed method estimates the transformation parameters for latitude, longitude, rotation and scaling factors when the matching pairs between a spherical panoramic image and a planar image are given. A planar image is projected into a spherical panoramic image through two steps of nonlinear coordinate transformations, which makes it difficult to compute the geometric transformation. The advantage of using our method is that we can uncover each of the implicit factors as well as the overall transformation. The experiment results show that our proposed method can achieve estimation errors of around 1% and is not affected by deformation factors, such as the latitude and rotation.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1351-1367
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• 2018

Image registration is an essential process for image fusion, change detection and time series analysis using multi-sensor images. For this purpose, we need to detect accurately the difference of scale and rotation between the multi-sensor images with difference spatial resolution. In this paper, we propose a new feature matching method using variable circular template for image registration between multi-resolution images. The proposed method creates a circular template at the center of a feature point in a coarse scale image and also a variable circular template in a fine scale image, respectively. After changing the scale of the variable circular template, we rotate the variable circular template by each predefined angle and compute the mutual information between the two circular templates and then find the scale, the angle of rotation and the center location of the variable circular template, respectively, in fine scale image when the mutual information between the two circular templates is maximum. The proposed method was tested using Kompsat-2, Kompsat-3 and Kompsat-3A images with different spatial resolution. The experimental results showed that the error of scale factor, the error of rotation angle and the localization error of the control point were less than 0.004, $0.3^{\circ}$ and one pixel, respectively.