• Journal of Digital Contents Society
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• v.15 no.2
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• pp.209-217
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• 2014

It is very important to classify a lot of table-form documents into the same type of classes or to extract information filled in the template automatically. For these, it is necessary to accurately analyze table-form structure. This paper proposes an algorithm to extract corner points based on line edge segments and to classify the type of junction from table-form images. The algorithm preprocesses image through binarization, skew correction, deletion of isolated small area of black color because that they are probably generated by noises.. And then, it processes detections of edge block, line edges from a edge block, corner points. The extracted corner points are classified as 9 types of junction based on the combination of horizontal/vertical line edge segments in a block. The proposed method is applied to the several unconstraint document images such as tax form, transaction receipt, ordinary document containing tables, etc. The experimental results show that the performance of point detection is over 99%. Considering that almost corner points make a correspondence pair in the table, the information of type of corner and width of line may be useful to analyse the structure of table-form document.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.179-185
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• 2018

Technology of Internet of Things (IoT) which is receiving the spotlight recently as a new growth engine of Information Communications Technology (ICT) industry in the $4^{th}$ Industrial Revolution needs trustworthiness beyond simple technology of security. IoT devices should consider trustworthiness from planning and design of IoTs so that everyone who develop, evaluate and use the device can measure and trust its security. Increased number of IoTs and long lifetime result in the increased securituy vulnerability due to the difficulty of software patch and update. In this paper, we investigated security and scalability issues of current IoT devices through research of the technical, political and industrial trend of IoT. In order to overcome the limitations, we propose an automatic verification of software integrity utilizing and a political solution to apply cyber killchain based security mechanism using hash which is an element technology of blockchain to solve these problems.

• Journal of Broadcast Engineering
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• v.11 no.2 s.31
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• pp.191-199
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• 2006

This paper presents an efficient pre echo control scheme for MPEG Audio coders based on the psychoacoustic model II (PAM-II). Pre echo control is the final step for the calculation of masking threshold in the PAM II. It is to minimize the spread of quantization error over the processing frame. In the conventional encoders, pre echo is reduced by restricting the estimated masking threshold not to exceed the one obtained in the previous frame. The conventional method performs pre echo control not only for short blocks but also for long blocks, which lowers the masking threshold in long blocks and, in turn, increases the quantization noise level of corresponding blocks. This paper proposes an efficient pre echo control process. The test result shows a mean enhancement of more than 0.4 especially for complex signals on the ITU R 5 point audio impairment scale.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.1-10
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• 2020

In this paper, we propose a new pornographic content detection scheme using bi-directional relationships between neighboring auditory signals in order to accurately detect sound-centered obscene contents that are rapidly spreading via the Internet. To capture the bi-directional relationships between neighboring signals, we design a multilayered bi-directional dilated-causal convolution network by stacking several dilated-causal convolution blocks each of which performs bi-directional dilated-causal convolution operations. To verify the performance of the proposed scheme, we compare its accuracy to those of the previous two schemes each of which uses simple auditory feature vectors with a support vector machine and uses only the forward relationships in audio signals by a previous stack of dilated-causal convolution layers. As the results, the proposed scheme produces an accuracy of up to 84.38% that is superior performance up to 25.80% than other two comparison schemes.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.745-754
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• 2005

This paper proposes an information hiding algorithm using channel coding technique which can be used to detect transmission errors and to protect copyright for MPEG-2 video The watermark signal is generated by applying copyright information of video data to a convolutional encoder, and the signal is embedded into macro blocks in every frame while encoding to MPEG-2 video stream In the decoder, the embedded signal is detected from macro blocks in every frame, and the detected signal is used to localize transmission errors in the video stream. The detected signal can also be used to claim ownership of the video data by decoding it to the copyright Information. In this stage, errors in the detected watermark signal can be corrected by channel decoder. The 3 video sequences which consist of 300 frames each are applied to the proposed MPEG-2 codec. Experimental results show that the proposed method can detect transmission errors in the video stream while decoding and it can also reconstruct copyright information more correctly than the conventional method.

• The KIPS Transactions:PartD
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• v.17D no.6
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• pp.395-404
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• 2010

Solid-State Disks (SSDs) have been currently considered as a promising candidate to replace hard disks, due to their significantly short access time, low power consumption, and shock resistance. SSDs, however, have drawbacks such that their write throughput and life span are decreased by random-writes, nearly regardless of SSDs controller designs. Previous studies have mostly focused on better designs of SSDs controller and reducing the number of write operations to SSDs. We suggest another method that reallocates data pages that tend to be simultaneously written to contiguous blocks. Our method gathers write operations during a period of time and generates write traces. After transforming each trace to a set of transactions, our method mines frequent itemsets from the transactions and reallocates the pages of the frequent itemsets. In addition, we introduce an algorithm that reallocates the pages of the frequent itemsets with moderate time complexity. Experiments using TPC-C workload demonstrated that our method successfully reduce 6% of total logical block access.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.417-425
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• 2019

Storage snapshot technology allows to preserve data at a specific point in time, and recover and access data at a desired point in time. It is an essential technology for storage protection application. Existing snapshot methods have some problems in that they dependent on storage hardware vendor, file system or virtual block device. In this paper, we propose a new snapshot method for solving the problems and creating snapshots on-line. The proposed snapshot method uses a method of extracting the log records of update operations at the virtual file system layer to enable the snapshot method to operate independently on file systems, virtual block devices, and storage hardwares. In addition, the proposed snapshot mehod creates and manages snapshots for directories and files without interruption to the storage service. Finally, through experiments we measure the snapshot creation time and the performance degradation caused by the snapshot.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.165-170
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• 2023

With the recent rise of blockchain technology, cryptocurrency platforms using it are increasing, and currency transactions are being actively conducted. However, crimes that abuse the characteristics of cryptocurrency are also increasing, which is a problem. In particular, phishing scams account for more than a majority of Ethereum cybercrime and are considered a major security threat. Therefore, effective phishing scams detection methods are urgently needed. However, it is difficult to provide sufficient data for supervised learning due to the problem of data imbalance caused by the lack of phishing addresses labeled in the Ethereum participating account address. To address this, this paper proposes a phishing scams detection method that uses both Trans2vec, an effective graph embedding techique considering Ethereum transaction networks, and semi-supervised learning model Tri-training to make the most of not only labeled data but also unlabeled data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.335-343
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• 2001

The conventional wavelet-based fractal image coding has the disadvantage that the encoding takes a long time, since each range block finds the best domain in the image. In this Paper, we propose wavelet-based fractal image coding using SAS(Self Affine System) method and multi-scale factor. It consists of the range and domain blocks in DWT(discrete wavelet transform) region. Using SAS method, the proposed method is that the searching process of the domain block is not required, and the range block selects the domain which is relatively located the same position in the upper level. The proposed method can perform a fast encoding by reducing the computational complexity in the encoding process. In order to improve the disadvantage of SAS method which is reduced image qualify, the proposed method is improved image qualify using the different scale factors for each level. As a result, there is not influence on an image quality, the proposed method is enhanced the encoding time and compression ratio, and it is able to the progressive transmission.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.741-747
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• 2012

In this paper, we propose a fast and robust framework for detecting and tracking multiple targets. The proposed system includes two modules: object detection module and object tracking module. In the detection module, we preprocess the input images frame by frame, such as gray and binarization. Next after extracting the foreground object from the input images, morphology technology is used to reduce noises in foreground images. We also use a block-based histogram analysis method to distinguish human and other objects. In the tracking module, color-based tracking algorithm and Kalman filter are used. After converting the RGB images into HSV images, the color-based tracking algorithm to track the multiple targets is used. Also, Kalman filter is proposed to track the object and to judge the occlusion of different objects. Finally, we show the effectiveness and the applicability of the proposed method through experiments.