• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.84-89
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• 2019

JPEG is a most widely used standard image compression technology. This research introduces the JPEG image compression algorithm and describes each step in the compression and decompression. Image compression is the application of data compression on digital images. The DCT (discrete cosine transform) is a technique for converting a time domain to a frequency domain. First, the image is divided into 8 by 8 pixel blocks. Second, working from top to bottom left to right, the DCT is applied to each block. Third, each block is compressed through quantization. Fourth, the matrix of compressed blocks that make up the image is stored in a greatly reduced amount of space. Finally if desired, the image is reconstructed through decompression, a process using IDCT (inverse discrete cosine transform). The purpose of this research is to review all the processes of image compression / decompression using the discrete cosine transform method.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.37-44
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• 2019

With the advance of digital IT technology, the performance of the printing and scanning devices is improved and their price becomes cheaper. As a result, the public can easily access these devices for crimes such as forgery of official and private documents. Therefore, if we can identify which printing device is used to print the documents, it would help to narrow the investigation and identify suspects. In this paper, we propose a deep learning model for printer identification. A convolutional neural network model based on local features which is widely used for identification in recent is presented. Then, another model including a step to calculate global features and hence improving the convergence speed and accuracy is presented. Using 8 printer models, the performance of the presented models was compared with previous feature-based identification methods. Experimental results show that the presented model using local feature and global feature achieved 97.23% and 99.98% accuracy respectively, which is much better than other previous methods in accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.493-495
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• 2014

With the expansion of the medical field worldwide, interest in medical devices is also increasing. However, since the field of the special nature of the medical device, is utilized in accordance with the respective devices is determined, the amount depending on the fields, to purchase a medical device is increased. Function digital parts (such as ECG, SpO2) are similar to each other, but there is a disadvantage by applying the method of designing separate each product, the reproduction of the program is difficult, Each product, each product the various OS is used, so that either can not be reused even if a program for the same function, it takes time to develop additional. In this paper, I would like to propose a study of the implementation of the platform of the biological signal of medical equipment to try solve the problems of the medical equipment of these.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.655-658
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• 2016

Xilinx 7-Series FPGA(Field Programmable Gate Array)s mainly used for the implementation of high-performance digital circuit have SRAM-type configuration memory and can malfunction when soft errors occur in their configuration memory. SEM(Soft Error Mitigation Controller) offered by Xilinx helps users mitigate the influence of soft errors in configuration memory. When soft errors occur, SEM Controller can recover the state of FPGA through partial reconfiguration if the soft errors are correctable by ECC(Error Correction Code) and CRC(Cyclic Redundancy Code). This paper presents the availability analysis of Xilinx 7-Series FPGAs against soft errors under the protection of the SEM Controller. Availability functions are derived and compared according to the correction capability of the SEM Controller. The result may help to estimate the reliability of SRAM-based FPGA running in an environment where soft errors may occur.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.158-166
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• 2019

Implementing proper land management techniques, such as selecting the best crops and applying the best cultivation techniques at the farm level, is an effective way for farmers to adapt to climate change. Also it will be helpful if the farmer can get the information of agro-weather and the growth status of cultivating crops in real time and the simulated results of applying optional technologies. To test this, a system (web site) was developed to produce agro-weather data and crop growth information of farms by combining agricultural climate maps and crop growth modeling techniques to highland area for summer-season Chinese cabbage production. The system has been shown to be a viable tool for producing farm-level information and providing it directly to farmers. Further improvements will be required in the speed of information access, the microclimate models for some meteorological factors, and the crop growth models to test different options.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.37-51
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• 2020

With the development of machine learning and deep learning technologies, there has been increasing interest and attempt to apply these technologies to the detection of urban changes. However, the traditional methods of detecting changes and constructing spatial information are still often performed manually by humans, which is costly and time-consuming. Besides, a large number of people are needed to efficiently detect changes in buildings in urban areas. Therefore, in this study, a methodology that can detect changes by classifying road, building, and vegetation objects that are highly utilized in the geospatial information field was proposed by applying deep learning technology to point clouds. As a result of the experiment, roads, buildings, and vegetation were classified with an accuracy of 92% or more, and attributes information of the objects could be automatically constructed through this. In addition, if time-series data is constructed, it is thought that changes can be detected and attributes of existing digital maps can be inspected through the proposed methodology.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.655-661
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• 2020

SGM (Semi Global Matching) can be used to find all the conjugate points between stereo images. Therefore, it enables high-density DSM (Digital Surface Model) production from high-resolution satellite images. However, water, shadows, and occlusion areas cause mismatching of the surrounding points in this method. Particularly, in buildings with large-parallax and elongated-shapes such as a Korean style apartment, it is difficult to reconstruct the 3D building even if the SGM method is applied to a high-resolution 50cm satellite image. This study proposed and performed the SGM technique with a classified image and an edge image from the IKONOS-2 satellite stereo-image with a 1m resolution to produce DSM. It was compared with the DSMs from the general SGM and the high-density ABM (Area Based Matching) matching of ERDAS software. The results of the apartment DSM by the proposed method were the best in the test area. As a result, despite the image having a resolution of 1m, the outline of the building DSM could be expressed more clearly than the existing method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2086-2097
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• 2021

The current cultural assets are being restored depending on the opinions of experts (craftsmen). We intend to introduce digitalized artificial intelligence techniques, excluding the personal opinions of experts on reconstruction of such cultural properties. The first step toward restoring digitized cultural properties is separation. The restoration of cultural properties should be reorganized based on recorded documents, period historical backgrounds and regional characteristics. The cultural properties in the form of photographs or images should be collected by separating the background. In addition, when restoring cultural properties most of them depend a lot on the tendency of the restoring person workers. As a result, it often occurs when there is a problem in the accuracy and reliability of restoration of cultural properties. In this study, we propose a search method for learning stored digital cultural assets using AI technology. Pagoda was selected for restoration of Cultural Properties. Pagoda data collection was collected through the Internet and various historical records. The pagoda data was classified by period and region, and grouped into similar buildings. The collected data was learned by applying the well-known CNN algorithm for artificial intelligence learning. The pagoda search used Yolo Marker to mark the tower shape. The tower was used a total of about 100-10,000 pagoda data. In conclusion, it was confirmed that the probability of searching for a tower differs according to the number of pagoda pictures and the number of learning iterations. Finally, it was confirmed that the number of 500 towers and the epochs in training of 8000 times were good. If the test result exceeds 8,000 times, it becomes overfitting. All so, I found a phenomenon that the recognition rate drops when the enemy repeatedly learns more than 8,000 times. As a result of this study, it is believed that it will be helpful in data gathering to increase the accuracy of tower restoration.

• (The) Research of the performance art and culture
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• no.35
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• pp.373-404
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• 2017

As an art, Korean dance is a history, a tradition, and a continuing activity of consciousness. It is a present and future activity in the past that will continue the identity of Korean people. So storytelling is not just a description of the historical background, but of eternity that is being recreated. From this study, the inquiry of artistic beauty of Korean traditional dance is questioning the original essence and value of 'storytelling' through old tradition and historical art. If the study of the Korean dance among them was a study of the theorists for the aesthetic essence or the ideological system, the point of view of the storytelling of the Korean dance is that the public understanding about the core structure and reason of Korean dance and the study of the humanistic value It reminded me of a desperate attitude. The meaning of this study is to verify the usefulness of storytelling as a way to construct various contents of Korean dance in conceptual definition of storytelling. In the symbolic meaning of Korean dance, Cheoyongmu text formed the deep meaning network of the original art beyond the linguistic narrative structure and suggested the importance of storytelling development as DB of original contents.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.2
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• pp.15-22
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• 2004

For an ElGamal-type signature scheme using a generate g of order q, it has been well-known that the message nonce should be chosen randomly in the interval (0, q-1) for each message to be signed. In (2), H. Kuwakado and H. Tanaka proposed a polynomial time algorithm that gives the private key of the signer if two signatures with message nonces 0＜$k_1$, $k_2$$\leq$Ο(equation omitted) are available. Recently, R. Gallant, R. Lambert, and S. Vanstone suggested a method to improve the efficiency of elliptic curve crytosystem using integer decomposition. In this paper, by applying the integer decomposition method to the algorithm proposed by Kuwakado and Tanaka, we extend the algorithm to work in the case when ｜$k_1$ ｜,｜$k_2$, ｜$\leq$Ο(equation mitted) and improve the efficiency and completeness of the algorithm.