• Agricultural and Biosystems Engineering
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• v.1 no.2
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• pp.95-99
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• 2000

Nondestructive methods such as ultrasonic and magnetic resonance imaging systems have many advantages but still much expensive. And they do not give exact color information and may miss some details. If it is allowed to destruct some biological objects to get interior and exterior informations, constructing 3D image form a series of slices sectional images gives more useful information with relatively low cost. In this paper, a PC based automatic 3D model generator was developed. The system was composed of three modules. The first module was the object handling and image acquisition module, which fed and sliced the object sequentially and maintains the paraffine cool to be in solid state and captures the sectional image consecutively. The second one was the system control and interface module, which controls actuators for feeding, slicing, and image capturing. And the last was the image processing and visualization module, which processed a series of acquired sectional images and generated 3D volumetric model. Handling module was composed of the gripper, which grasped and fed the object and the cutting device, which cuts the object by moving cutting edge forward and backward. sliced sectional images were acquired and saved in a form of bitmap file. 2D sectional image files were segmented from the background paraffine and utilized to generate the 3D model. Once 3-D model was constructed on the computer, user could manipulated it with various transformation methods such as translation, rotation, scaling including arbitrary sectional view.

• Journal of Digital Convergence
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• v.9 no.3
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• pp.47-58
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• 2011

As China's international status is more and more uplifted, the active shaping and effective propagation of China's national image has been regarded as an important means to demonstrate China's soft power, demolish the so-called "China Threat Theory", and compete for China's share in international discourse power. This article first makes a discussion on the fundamental concepts and related theories of national image, and then explores the precise positioning of China's image as "a responsible power" and the connotation that should be contained in this image. Finally, this article presents a tactic of "complex propagation" for the shaping of China's national image, which includes the propagation by new media and advertisement, the marketing of international sport games and other international events, public diplomacy and public relations tactics.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.17-25
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• 2012

In this paper, we propose a method of producing a stereoscopic image from multiple images captured from a monoscopic camera. By translating a camera in the horizontal direction, left and right images are chosen among N captured images. For this, image edges are extracted and a rotational angle is estimated from edge orientation. Also, a translational vector is also estimated from the correlation of projected image data. Then, two optimal images are chosen and subsequently compensated using the rotational angle as well as the translational vector in order to make a satisfactory stereoscopic image. The proposed method was performed on thirty-two test image set. The subjective visual fatigue test was carried out to validate the 3D quality of stereoscopic images. In terms of visual fatigue, the 3D satisfaction ratio reached approximately 84%.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.5
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• pp.93-103
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• 2005

In this paper, we propose a RST resistant robust logo embedding technique for multimedia copyright protection Geometric manipulations are challenging attacks in that they do not introduce the quality degradation very much but make the detection process very complex and difficult. Watermark embedding in the normalized image directly suffers from smoothing effect due to the interpolation during the image normalization. This can be avoided by estimating the transform parameters using an image normalization technique, instead of embedding in the normalized image. Conventional RST resistant schemes that use full frame transform suffer from the absence of effective perceptual masking methods. Thus, we adopt $8\times8$ block DCT and calculate masking using a spatio-frequency localization of the $8\times8$ block DCT coefficients. Simulation results show that the proposed algorithm is robust against various signal processing techniques, compression and geometrical manipulations.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.575-578
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• 2005

Topographical images, in case of aerial or satellite images, are usually similar in colors and textures, and complex in shapes. Thus we have to use shape features of images for efficiently retrieving a query image from topographical image databases. In this paper, we propose a shape feature extraction method which is suitable for topographical images. This method, which improves the existing projection in the Cartesian coordinates, performs the projection operation in the polar coordinates. This method extracts three attributes, namely the number of region pixels, the boundary pixel length of the region from the centroid, the number of alternations between region and background, along each angular direction of the polar coordinates. It extracts the features of complex shape objects which may have holes and disconnected regions. An advantage of our method is that it is invariant to rotation/scale/translation of images. Finally we show the advantages of our method through experiments by comparing it with CSS which is one of the most successful methods in the area of shape feature extraction

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.876-883
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• 2003

In this paper, we propose an algorithm for organ recognition in ultrasound images using log power spectrum. The main procedure of the algorithm consists of feature extraction and feature classification. In the feature extraction, as a translation invariant feature, log power spectrum is used for extracting the information on echo of the organs tissue from a preprocessed input image. In the feature classification, Mahalanobis distance is used as a measure of the similarity between the feature of an input image and the representative feature of each class. Experimental results for real ultrasound images show that the proposed algorithm yields the improvement of maximum 30% recognition rate than the recognition algorithm using power spectrum and Euclidean distance, and results in better recognition rate of 10-40% than the recognition algorithm using weighted quefrency complex cepstrum.

• ETRI Journal
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• v.43 no.4
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• pp.603-616
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• 2021

Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1166-1186
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• 2022

Artistic font design has become an integral part of visual media. However, without prior knowledge of the font domain, it is difficult to create distinct font styles. When the number of characters is limited, this task becomes easier (e.g., only Latin characters). However, designing CJK (Chinese, Japanese, and Korean) characters presents a challenge due to the large number of character sets and complexity of the glyph components in these languages. Numerous studies have been conducted on automating the font design process using generative adversarial networks (GANs). Existing methods rely heavily on reference fonts and perform font style conversions between different fonts. Additionally, rather than capturing style information for a target font via multiple style images, most methods do so via a single font image. In this paper, we propose a network architecture for generating multilingual font sets that makes use of geometric structures as content. Additionally, to acquire sufficient style information, we employ multiple style images belonging to a single font style simultaneously to extract global font style-specific information. By utilizing the geometric structural information of content and a few stylized images, our model can generate an entire font set while maintaining the style. Extensive experiments were conducted to demonstrate the proposed model's superiority over several baseline methods. Additionally, we conducted ablation studies to validate our proposed network architecture.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.42.3-42.3
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• 2019

We translate Solar Dynamics Observatory/Atmospheric Imaging Assembly (AIA) ultraviolet (UV) multi-channel images into another UV single-channel image using a deep learning algorithm based on conditional generative adversarial networks (cGANs). The base input channel, which has the highest correlation coefficient (CC) between UV channels of AIA, is 193 Å. To complement this channel, we choose two channels, 1600 and 304 Å, which represent upper photosphere and chromosphere, respectively. Input channels for three models are single (193 Å), dual (193+1600 Å), and triple (193+1600+304 Å), respectively. Quantitative comparisons are made for test data sets. Main results from this study are as follows. First, the single model successfully produce other coronal channel images but less successful for chromospheric channel (304 Å) and much less successful for two photospheric channels (1600 and 1700 Å). Second, the dual model shows a noticeable improvement of the CC between the model outputs and Ground truths for 1700 Å. Third, the triple model can generate all other channel images with relatively high CCs larger than 0.89. Our results show a possibility that if three channels from photosphere, chromosphere, and corona are selected, other multi-channel images could be generated by deep learning. We expect that this investigation will be a complementary tool to choose a few UV channels for future solar small and/or deep space missions.

• Journal of Biomedical Engineering Research
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• v.27 no.6
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• pp.392-401
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• 2006

Image Guided Surgery (IGS) system which has variously tried in medical engineering fields is able to give a surgeon objective information of operation process like decision making and surgical planning. This information is displayed through 3D images which are acquired from image modalities like CT and MRI for pre-operation. The technique of image registration is necessary to construct IGS system. Image registration means that 3D model and the object operated by a surgeon are matched on the common frame. Major techniques of registration in IGS system have been used by recognizing fiducial markers placed on the object. However, this method has been criticized due to additional trauma, its invasive protocol inserting fiducial markers in patient's bone and generating noise data when 2D slice images are acquired by image modality because many markers are made of metal. Therefore, this paper developed shape-based registration technique to improve the limitation of fiducial marker based IGS system. Iterative Closest Points (ICP) algorithm was used to match corresponding points and quaternion based rotation and translation transformation using closed form solution applied to find the optimized cost function of transformation. we assumed that this algorithm were used in Total Knee replacement (TKR) operation. Accordingly, we have developed region-based 3D registration technique based on anatomical landmarks and this registration algorithm was evaluated in a femur model. It was found that region-based algorithm can improve the accuracy in 3D registration.