• The Korean Journal of Nuclear Medicine
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• v.21 no.2
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• pp.167-174
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• 1987

Among noninvasive approaches for the evaluation of left ventricular performance, radionuclide ventriculography (RVG) has been shown to be of particular values. Phase analysis, recently introduced as more objective means for evaluating the temporal sequence of systolic ventricular wall motion than cine image of RVG comprises a pixel by pixel Fourier transformation of the time activity curve of a multiple gated acquisition equilibrium blood pool study. To examine the regional wall motion of ventricles in myocardial infarctions, we evaluated the phase image and histogram constructed for each ventricle by total phase angle range and full width of half maximum (FWHM). This study consisted of 7 normal subjects and 23 subjects with acute myocardial infarction. Contrast ventriculography and coronary angiography was performed in all partients with myocardial infarction. And we compared the result of phase analysis with cine image of RVG and examined the interrelationship between phase analysis and contrast ventriculography with coronary angiography. The results were as follows; 1) The total phase angle range and FWHM of LV phase histogram in myocardial infarction ($86^{\circ}\;and\;32^{\circ}$, repectively) were wider than those in normal control ($38^{\circ}\;and\;18^{\circ}$, respectively p<0.01). 2) RV phase angle range and FWHM in patients with right coronary artery (RCA) occlusion ($79^{\circ}\;and\;37^{\circ}$, respectively) were wider than those in normal control ($39^{\circ}\;and\;18^{\circ}$, respectively p<0.001) and the patients without RCA occlusion ($52^{\circ}\;and\;19^{\circ}$, respectively p<0.01). 3) Phase analysis was more sensitive (95%) than cine image of RVG (70%) for the detection of regional wall motion abnormality of LV.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.171-180
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• 2013

Data security is always an important issue. In particular, the current emerging cloud computing system inevitably raises the issue of data security. However, data security is no longer safe with a simple way, but requires rather advanced method to secure the data. In this paper, instead of exploiting the existing text-based cryptography approach an image-based access control of data content is studied to present a higher level of data security. Color key chain is generated both using histogram value of the original image, and the location information and featured color information extracted by geometric transformation to form the security key to access secure data content. Finally, the paper addresses design interface and implementation for data content access control for evaluation of the proposed scheme.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.1
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• pp.67-78
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• 2005

We proposed a blind watermarking for 3D mesh model using the patch CEGIs. The CEGI is the 3D orientation histogram with complex weight whose magnitude is the mesh area and phase is the normal distance of the mesh from the designated origin. In the proposed algorithm we divide the 3D mesh model into the number of patch that determined adaptively to the shape of model and calculate the patch CEGIs. Some cells for embedding the watermark are selected according to the rank of their magnitudes in each of patches after calculating the respective magnitude distributions of CEGI for each patches of a mesh model. Each of the watermark bit is embedded into cells with the same rank in these patch CEGI. Based on the patch center point and the rank table as watermark key, watermark extraction and realignment process are performed without the original mesh. In the rotated model, we perform the realignment process using Euler angle before the watermark extracting. The results of experiment verify that the proposed algorithm is imperceptible and robust against geometrical attacks of cropping, affine transformation and vertex randomization as well as topological attacks of remeshing and mesh simplification.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.1
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• pp.73-80
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• 2016

The Car License Plate Recognition(: CLPR) is required in searching the hit-and-run car, measuring the traffic density, investigating the traffic accidents as well as in pursuing vehicle crimes according to the increasing in number of vehicles. The captured images on the real environment of the CLPR is contaminated not only by snow and rain, illumination changes, but also by the geometrical distortion due to the pose changes between camera and car at the moment of image capturing. We propose homographic transformation and intensity histogram of vertical image projection so as to transform the distorted input to the original image and cluster the character and number, respectively. Especially, in this paper, the Multilayer Perceptron Algorithm(: MLP) in the CLPR is used to not only recognize the charcters and car license plate, but also determine the optimized ratio among the number of input, hidden and output layers by the real experimental result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1469-1475
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• 2010

This paper presents a problem of existing encryption methods using pseudo-random numbers based on MLCA or complemented MLCA and proposes a method to resolve this problem. The existing encryption methods have a problem which the edge of original image appear on encrypted image because the image have color similarity of adjacent pixels. In this proposed method, we transform the value and spatial coordinates of all pixels by using pseudo-random numbers based on MLCA. This method can resolve the problem of existing methods and improve the level of encryption by encrypting pixel coordinates and pixel values of original image. The effectiveness of the proposed method is proved by conducting histogram and key space analysis.

• Journal of Digital Contents Society
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• v.10 no.3
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• pp.423-431
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• 2009

There are various image retrieval methods using shape, color and texture features. One of the most active area is using shape and color information. A number of shape representations have been suggested to recognize shapes even under affine transformation. There are many kinds of method for shape recognition, the well-known method is Fourier descriptors and moment invariant. The other method is CSS(Curvature Scale Space). The maxima of curvature scale space image have already been used to represent 2-D shapes in different applications. Because preexistence CSS exists several problems, in this paper we use improved CSS method for retrieval image. There are two kinds of method, One is using RGB color information feature and the other is using HSI color information feature. In this paper we used HSI color model to represent color histogram before, then use it as comparison measure. The similarity is measured by using Euclidean distance and for reduce search time and accuracy, We use DTW for measure similarity. Compare with the result of using Euclidean distance, we can find efficiency elevated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4C
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• pp.350-357
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• 2010

In this paper, we present an auto-range fast bilateral filter (FBF) for high-dynamic-range (HDR) images, which increases computation speed by using adaptive standard deviations for range filter (RF) of FBF in iCAM06. Many images that cover the entire dynamic range of the scene with different exposure times are fused into one High Dynamic Range (HDR) image. The representative algorithm for HDR image rendering is iCAM06, which is based on the iCAM framework, such as the local white point adaptation, chromatic adaptation, and the image processing transform (IPT) uniform color space. FBF in iCAM06 uses constant standard deviation in RF. So, it causes unnecessary FBF computation in high stimulus range with broad and low distribution. To solve this problem, the low stimulus image and high stimulus image of CIE tri-stimulus values (XYZ) divided by the threshold are respectively processed by adaptive standard deviation based on its histogram distribution. Experiment results show that the proposed method reduces computation time than the previous FBF.

• Journal of KIISE:Software and Applications
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• v.28 no.7
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• pp.501-510
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• 2001

Generally, it is essential to estimate exact disparity for the 3D modeling from stereo images. Because existing methods calculate disparities from a whole image, they require too much cimputational time and bring about the mismatching problem. In this article, using the characteristic that the disparity vectors in stereo images are distributed not equally in a whole image but only exist about the background and obhect, we do a wavelet transformation on stereo images and estimate coarse disparity fields from the reduced lowpass field using area-based method at first-step. From these coarse disparity vectors, we generate disparity histogram and then separate object from background area using it. Afterwards, we restore only object area to the original image and estimate dense and accurate disparity by our two-step pixel-based method which does not use pixel brightness but use second gradient. We also extract feature points from the separated object area and estimate depth information by applying disparity vectors and camera parameters. Finally, we generate 3D model using both feature points and their z coordinates. By using our proposed, we can considerably reduce the computation time and estimate the precise disparity through the additional pixel-based method using LOG filter. Furthermore, our proposed foreground/background method can solve the mismatching problem of existing Delaunay triangulation and generate accurate 3D model.

• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.51-56
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• 2011

Algorithms for intrinsic images reduce color differences in RGB images caused by the temperature of black-body radiators. Based on the reference light and detecting single invariant direction, these algorithms are weak in real images which can have multiple invariant directions when the scene illuminant is a colored illuminant. To solve these problems, this paper proposes a method of acquiring an intrinsic image by omnidirectional projection of an ROI and a translation of white patch in the ${\chi}$-chromaticity space. Because it is not easy to analyze an image in the three-dimensional RGB space, the ${\chi}$-chromaticity is also employed without the brightness factor in this paper. After the effect of the colored illuminant is decreased by a translation of white patch, an invariant direction is detected by omnidirectional projection of an ROI in this chromaticity space. In case the RGB image has multiple invariant directions, only one ROI is selected with the bin, which has the highest frequency in 3D histogram. And then the two operations, projection and inverse transformation, make intrinsic image acquired. In the experiments, test images were four datasets presented by Ebner and evaluation methods was the follows: standard deviation of the invariant direction, the constancy measure, the color space measure and the color constancy measure. The experimental results showed that the proposed method had lower standard deviation than the entropy, that its performance was two times higher than the compared algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.655-663
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• 2017

With the development of ICT technology, the indoor utilization of robots is increasing. Research on transportation, cleaning, guidance robots, etc., that can be used now or increase the scope of future use will be advanced. To facilitate the use of mobile robots in indoor spaces, the problem of self-location recognition is an important research area to be addressed. If an unexpected collision occurs during the motion of a mobile robot, the position of the mobile robot deviates from the initially planned navigation path. In this case, the mobile robot needs a robust controller that enables the mobile robot to accurately navigate toward the goal. This research tries to address the issues related to self-location of the mobile robot. A robust position recognition system was implemented; the system estimates the position of the mobile robot using a combination of encoder information of the mobile robot and the absolute space coordinate transformation information obtained from external video sources such as a large number of CCTVs installed in the room. Furthermore, vector field histogram method of the pass traveling algorithm of the mobile robot system was applied, and the results of the research were confirmed after conducting experiments.