• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.937-946
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• 1995

We proposed and efficient block segmentation and classification method for the document analysis using SGLDM(spatial gray level dependence matrix) and BP (back Propagation) neural network. Seven texture features are extracted directly from the SGLDM of each gray-level block image, and by using the nonlinear classifier of neural network BP, we can classify document blocks into 9 categories. The proposed method classifies the equation block, the table block and the flow chart block, which are mostly composed of the characters, out of the blocks that are conventionally classified as non-character blocks. By applying Sobel operator on the gray-level document image beforebinarization, we can reduce the effect of the background noises, and by using the additional horizontal-vertical smoothing as well as the vertical-horizontal smoothing of images, we can obtain an effective block segmentation that does not lead to the segmentation into small pieces. The result of experiment shows that a document can be segmented and classified into the character blocks of large fonts, small fonts, the character recognigible candidates of tables, flow charts, equations, and the non-character blocks of photos, figures, and graphs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1159-1174
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• 2004

In this paper, we present an efficient algorithm for region analysis of business card images acquired in a PDA by using DCT and information pixel density. The proposed method consists of three parts: region segmentation, information region classification, and text region classification. In the region segmentation, an input business card image is partitioned into 8 f8 blocks and the blocks are classified into information and background blocks using the normalized DCT energy in their low frequency bands. The input image is then segmented into information and background regions by region labeling on the classified blocks. In the information region classification, each information region is classified into picture region or text region by using a ratio of the DCT energy of horizontal and vertical edge components to that in low frequency band and a density of information pixels, that are black pixels in its binarized region. In the text region classification, each text region is classified into large character region or small character region by using the density of information pixels and an averaged horizontal and vertical run-lengths of information pixels. Experimental results show that the proposed method yields good performance of region segmentation, information region classification, and text region classification for test images of several types of business cards acquired by a PDA under various surrounding conditions. In addition, the error rates of the proposed region segmentation are about 2.2-10.1% lower than those of the conventional region segmentation methods. It is also shown that the error rates of the proposed information region classification is about 1.7% lower than that of the conventional information region classification method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1740-1747
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• 2004

In this paper, we proposed an effective method for detecting fingerprint ridge direction based on the run-length and chain codes. First, a fingerprint image is normalized, and it is thresholded to obtain binary image with foreground and background regions. The foreground regions is composed of fingerprint ridges, and the ridges is encoded with the run-length and chain codes. To detect directional information, the boundary of ridge codes is traced, and curvature is calculated at ecah point of boundary. And the detected direction value is smoothed with appropriate window locally. The proposed method is applied to NIST and FVC2002 fingerprint database to evaluate performance. By the experimental results, the proposed method can be used to obtain ridge direction value in fingerprint image.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.913-921
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• 2004

Steganography is a kind of data hiding which can hide secret information to digital media. It is performed so that another person does not recognize any information and make secret communication between each other. Specially, it is not easy to hide secret information without being visually recognized in scanned text image or cartoon image etc. In this paper, we propose an improved method that can embed a large quantity of secret information in a binary image without noticeable artifacts. Binary cartoon image is divided into block of 3-by-3 sizes. Secret information is embedded by using run-length of 8-neighborhood pixels except for the center pixel of the block. To improve the embedding capacity, we embed it into center pixel under to some condition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.88-94
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• 2009

This paper proposes real time object detection and tracking algorithm that can be applied to security and supervisory system field. A proposed system is devide into object detection phase and object tracking phase. In object detection, we suggest Adaptive background subtraction method and Adaptive block based model which are advanced motion detecting methods to detect exact object motions. In object tracking, we design a multiple vehicle tracking system based on Kalman filtering. As a result of experiment, motion of moving object can be estimated. the result of tracking multipul object was not lost and object was tracked correctly. Also, we obtained improved result from long range detection and tracking.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.4
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• pp.24-36
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• 2011

In this paper, we verify the channel synthesis and decomposition of polar codes using successive cancellation decoding algorithm over binary discrete memoryless symmetric channel by modifying Arikan's algebraic formular on encoding and decoding of polar codes. In addition, we found that information bits are sent by efficiently consisting of polar codes with their size $2^n$ through polarizing matrix ${G_2}^{{\otimes}n}$ over binary discrete memoryless symmetric channel W. Expecially, if $N{\geq}2$, the complexity of Arikan's encoding and decoding for polar codes is O($Nlog_2N$). Furthermore, we found that polar codes are one of the solution to the challenging problems for the multipoint communication.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.4 no.1
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• pp.37-44
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• 2005

본 논문에서는 멀티 코드 CDMA(Code Division Multiple Access)시스템에서 고속의 멀티미디어 서비스를 지원하기 위해 정보 데이터열을 QAM(Quadrature Amplitude Modulation) 부호화하는 방법을 제안한다. 송신 구조는 입력 비트를 정진폭 다중부호 이진직교 변조(Constant amplitude code biorthogonal modulation: 이하 CACB라 칭함)로 부호화하여 전송 심볼의 크기를 일정하게 하고 이렇게 이진화된 신호를 QAM 부호화하여 전송속도를 높인다. 복조기의 구조는 수신된 신호로부터 QAM 연판정기 블록을 거쳐 생성된 신호를 CACB 복호화기를 거쳐 데이터를 복조해 낸다. 제안된 시스템은 기존의 멀티 코드 방식에 비해 대역폭 효율을 크게 개선시킬 수 있어 전송 속도를 많이 향상시킬 수 있고, 멀티 코드 방식을 기반으로 하기 때문에 디지털 가전기기나 3세대 이동통신과, WPAN과 관련된 무선 네트워크 응용과 같은 미래의 고속의 무선 멀티미디어 서비스를 지원하기에 적합하다.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.111-120
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• 2016

Wire recognition is one of the important tasks in chip reverse engineering since connectivity comes from wires. Recognized wires are used to recover logical or functional representation of the corresponding circuit. Though manual recognition provides accurate results, it becomes impossible, as the number of wires is more than hundreds of thousands. Wires on a chip usually have specific intensity or color characteristics since they are made of specific materials. This paper proposes two stage wire recognition scheme; image binarization and then the process of determining whether regions in binary image are wires or not. We employ existing techniques for two processes. Since the second process requires the characteristics of wires, the users needs to select the typical wire region in the given image. The histogram characteristic of the selected region is used in calculating histogram similarity between the typical wire region and the other regions. The first experiment is to select the most appropriate binarization scheme for the second process. The second experiment on the second process compares three proposed methods employing histogram similarity of grayscale or HSV color since there have not been proposed any wire recognition method comparable by experiment. The best method shows more than 98% of true positive rate for 25 test examples.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.303-310
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• 2018

Bitcoin (BTC) is a cryptocurrency proposed by Satoshi Nakamoto in 2009. Bitcoin makes its transactions with no central authorities. This decentralization is accomplished with its mining, which is an operation that makes people compete to solve math puzzles to include new transactions into block, and eventually block chains (ledger) of bitcoin. Because miners need to solve a complex puzzles, they need a lot of computing resources. In return for miners' resources, bitcoin network gives newly minted bitcoins as a reward to miners when they succeed in mining. To prevent inflation, the reward is halved every 4 years. For example, in 2009 block reward was 50 BTC, but today, the block reward is 12.5 BTC. On the other hands, exchange rate for bitcoin and Korean Won (KRW) changed drastically from 924,000 KRW/BTC (January 12th, 2017) to 16,103,306 KRW/BTC (December 10th, 2017), which made mining more attractive. However, there are no rigorous researches on the profitability of bitcoin mining. In this paper, we evaluate the profitability of bitcoin mining.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.6
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• pp.385-393
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• 2017

As the use of mobile devices such as smartphones increases, there is growing interest on the benefits of virtualization in embedded systems. Full virtualization has the advantage of running the guest virtual machine without modifying the guest operating system. However, full virtualization suffers slow execution speed due to the cost of context switching between the virtual machines and the virtual machine monitor. In this paper, we propose a translated block and context switching optimization to improve the guest execution speed in the embedded system. As a result, the improved dynamic binary translator is up to 5.95 times faster than the native execution. Performance degradation is less than that of the other virtualization system.