• 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.

• (The)Study of the Eastern Classic
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• no.73
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• pp.445-473
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• 2018

This article deals with the reason for translating Korean Chinese written classics and the image of the person performing the translation. The scope of the research was restricted to South Korea and the translation value of translating the Korean classical texts from the 1960s to the 2018. In the 1960s and 1970s, the discourse of national culture and the Classical Sinology(漢學) discourse centered around the Minjokmunwhachujinhwe(民族文化推進會, National Culture Promotion Association). The discourse of the national culture was paired with the modernization, and the discourse of Classical Sinology(漢學) discourse was a certain antagonism to the discourse of modernization. The translator stereotype in this periods was close to a Classical Sinology(漢學) who could wright Korean letters. The discourse of the national culture led to the establishment of The Academy of Korean Studies by pairing with the discourse of the spiritual culture, and then changed into Korean study discourse in the 1980s. Since the mid 80s, the theory of translation has been introduced byo Kim Yong-ok. The translation of the Chosun dynasty annals, which started in the 70s, made the classical translation discourse in the classical translation field into the national project efficiency discourse. To the Early achievement of state-led gigantic project through group translation, they emphasized coherence and efficiency. On the contrary, the individuality of the translators and aspects of in-depth research have weakened. This discourse also influenced until the early 2000s. These large translation projects were produced by professional translator group. With the establishment of the Institute for the Translation of Korean Classics(Hankuk Kojon Bunyukwon) in 2007, he foundation for the stability of the classical translation business was established, and the classical translation discourse was shifted to the academic discourse centered on classical translation sudies. This discussion was expanded to the request of the establishment of an academic institution called the Classical Translation Graduate School, with a discussion on the academic identities of classical translation studies. The imagies of translators, paired with the academic discourse of this period, and that the classical translators must be classical scholars and translators, are begun to be requested. Thus, the classical translation value discourse changed with the passage of time, and the imagies of classical translators have been changed accordingly.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.386-393
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• 2010

A defect in an image is a set of pixels forming an irregular shape. Since a defect, in most cases, is not easy to be modeled mathematically, the defect detection problem still resides in a research area. If a given image, however, composed by certain patterns, a defect can be detected by the fact that a non-defect area should be explained by another patch in terms of a rotation, translation, and noise. In this paper, therefore, the defect detection method for a repeated multi-patterned image is proposed. The proposed defect detection method is composed of three steps. First step is the interest point detection step, second step is the selection step of a appropriate patch size, and the last step is the decision step. The proposed method is illustrated using SEM images of semiconductor wafer samples.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.548-555
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• 2001

In this paper, we proposed a HVS(human visual system) model-based digital image watermarking which is not only invariant to rotation and translation but also more robust to lossy compression, cropping, and scaling as compared to the conventional method. Fourier transform and log-polar mapping is used to make the proposed algorithm invariant to rotation and translation, and in addition, watermark energy is embedded maximally based on spatial frequency sensitivity of HVS without the deterioration of the invisibility. As a result, the robustness of watermarking is improved both in general image processing operations such as cropping, low pass filtering, and lossy compression and in geometrical transforms such as rotation, translation, and scaling. And, by disjoint embedding of the watermark and the template without intersection, the deterioration of invisibility and robustness is prevented. Experimental results show that proposed watermarking is about 30~75 [%] more robust af compared to the conventional methods.

• Journal of Internet Computing and Services
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• v.1 no.1
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• pp.1-14
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• 2000

Visual information retrieval and image databases are very important applications of spatial access methods. The quaries for these applications are visual and based not on exact match but on dubjective similarity. The individual aperations of spatial access methods are much more expensive than those of conventional one-dimensional access methods. Also, because the visual queries are much more complex than textual queries, an efficient processing technique for visual queries is one of the critical requirements in the development of large and scalable image databases. Therefore, efficient translation and execution for the complex visual queries are not less important than those of textual databases. In this paper, we introduce our cognitive and topological studies that are required to process subjective visual queries effectively. Then, we propose an efficient translation and execution techniques for similarity based visual queries by conducting these related studies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.1-6
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• 2016

Image rotation is one of main pre-processing step in image processing or image pattern recognition. It is implemented with rotation matrix multiplication. However it requires lots of floating point arithmetic operations and trigonometric function calculations, so it takes long execution time. We propose a new high speed image rotation algorithm without two major time-consuming operations. It use just 2 shear translation operations, so it is very fast. In addition, we apply a parallel computing technique with CUDA. CUDA is a massively parallel computing architecture using prevailed GPU recently. As GPU is a dedicated graphic processor, it is exellent for parallel processing of pixels. We compare the proposed algorithm with the conventional rotation one with various size images. Experimental results show that the proposed algorithm is superior to the conventional rotation ones.

• 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 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.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.292-302
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• 2020

Machine learning algorithms have made immense contributions in various fields including sonar and radar applications. Recently developed Cycle-Consistency Generative Adversarial Network (CycleGAN), a variant of GAN has been successfully used for unpaired image-to-image translation. We present a modified CycleGAN for translation of underwater ship engine sounds with high perceptual quality. The proposed network is composed of an improved generator model trained to translate underwater audio from one vessel type to other, an improved discriminator to identify the data as real or fake and a modified cycle-consistency loss function. The quantitative and qualitative analysis of the proposed CycleGAN are performed on publicly available underwater dataset ShipsEar by evaluating and comparing Mel-cepstral distortion, pitch contour matching, nearest neighbor comparison and mean opinion score with existing algorithms. The analysis results of the proposed network demonstrate the effectiveness of the proposed network.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.11-19
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• 2021

An abnormal object refers to a person, an object, or a mechanical device that performs abnormal and unusual behavior and needs observation or supervision. In order to detect this through artificial intelligence algorithm without continuous human intervention, a method of observing the specificity of temporal features using optical flow technique is widely used. In this study, an abnormal situation is identified by learning an algorithm that translates an input image frame to an optical flow image using a Generative Adversarial Network (GAN). In particular, we propose a technique that improves the pre-processing process to exclude unnecessary outliers and the post-processing process to increase the accuracy of identification in the test dataset after learning to improve the performance of the model's abnormal behavior identification. UCSD Pedestrian and UMN Unusual Crowd Activity were used as training datasets to detect abnormal behavior. For the proposed method, the frame-level AUC 0.9450 and EER 0.1317 were shown in the UCSD Ped2 dataset, which shows performance improvement compared to the models in the previous studies.