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Efficient VLSI Architecture for Disparity Calculation based on Geodesic Support-weight (Geodesic Support-weight 기반 깊이정보 추출 알고리즘의 효율적인 VLSI 구조)

  • Ryu, Donghoon;Park, Taegeun
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.9
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    • pp.45-53
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    • 2015
  • Adaptive support-weight based algorithm can produce better disparity map compared to generic area-based algorithms and also can be implemented as a realtime system. In this paper, we propose a realtime system based on geodesic support-weight which performs better segmentation of objects in the window. The data scheduling is analyzed for efficient hardware design and better performance and the parallel architecture for weight update which takes the longest delay is proposed. The exponential function is efficiently designed using a simple step function by careful error analysis. The proposed architecture is designed with verilogHDL and synthesized using Donbu Hitek 0.18um standard cell library. The proposed system shows 2.22% of error rate and can run up to 260Mhz (25fps) operation frequency with 182K gates.

Design of MAC Algorithm Supporting Adaptive Transmission Rate on VANET (VANET에서 적정 전송속도를 지원하는 MAC 설계)

  • Park, Sanghyun;Kim, Nam-Il
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.11
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    • pp.132-138
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    • 2012
  • VANET(Vehicular Ad-hoc Network), standardization of IEEE 802.11p specification is in process. 802.11 MAC protocol grants all nodes equal opportunity to acquire channel without regard to their bit-rates, making it possible for lower bit-rate nodes to occupy communication channel for a fair amount of time thus keeping the higher bit-rate nodes from acquiring connection channel which downward-equalize the overall network performance. Also with the 802.11p MAC protocol, the probability of collision occurring increases as the number of nodes grow. The proposed algorithm is a new MAC protocol that guarantees nodes with acquired channel a firm priority over other nodes for a fixed amount of time with TXOP concept added to 'packet burst' according to the current transmitting speed. This newly designed algorithm allows the construction of wireless network with enhanced network throughput, decreased probability of collisions as well as providing the means to grant each node a fair chance of acquiring connection according to their channel conditions. The algorithm sets the CW's (Contention Window) width wider than the standard's and modulates the continuous transmitting threshold value depending on channel acquired time, thus improving the overall performance of the network.

Efficient QRS Detection and PVC(Premature Ventricular Contraction) Classification based on Profiling Method (효율적인 QRS 검출과 프로파일링 기법을 통한 심실조기수축(PVC) 분류)

  • Cho, Ik-Sung;Kwon, Hyeog-Soong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.3
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    • pp.705-711
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    • 2013
  • QRS detection of ECG is the most popular and easy way to detect cardiac-disease. But it is difficult to analyze the ECG signal because of various noise types. Also in the healthcare system that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. In other words, the design of algorithm that exactly detects QRS wave using minimal computation and classifies PVC by analyzing the persons's physical condition and/or environment is needed. Thus, efficient QRS detection and PVC classification based on profiling method is presented in this paper. For this purpose, we detected QRS through the preprocessing method using morphological filter, adaptive threshold, and window. Also, we applied profiling method to classify each patient's normal cardiac behavior through hash function. The performance of R wave detection, normal beat and PVC classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.77% in R wave detection and the rate of 0.65% in normal beat classification error and 93.29% in PVC classification.

Determining Method of Factors for Effective Real Time Background Modeling (효과적인 실시간 배경 모델링을 위한 환경 변수 결정 방법)

  • Lee, Jun-Cheol;Ryu, Sang-Ryul;Kang, Sung-Hwan;Kim, Sung-Ho
    • Journal of KIISE:Software and Applications
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    • v.34 no.1
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    • pp.59-69
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    • 2007
  • In the video with a various environment, background modeling is important for extraction and recognition the moving object. For this object recognition, many methods of the background modeling are proposed in a process of preprocess. Among these there is a Kumar method which represents the Queue-based background modeling. Because this has a fixed period of updating examination of the frame, there is a limit for various system. This paper use a background modeling based on the queue. We propose the method that major parameters are decided as adaptive by background model. They are the queue size of the sliding window, the sire of grouping by the brightness of the visual and the period of updating examination of the frame. In order to determine the factors, in every process, RCO (Ratio of Correct Object), REO (Ratio of Error Object) and UR (Update Ratio) are considered to be the standard of evaluation. The proposed method can improve the existing techniques of the background modeling which is unfit for the real-time processing and recognize the object more efficient.

Adaptive Buffer Control over Disordered Streams (비순서화된 스트림 처리를 위한 적응적 버퍼 제어 기법)

  • Kim, Hyeon-Gyu;Kim, Cheol-Gi;Lee, Chung-Ho;Kim, Myoung-Ho
    • Journal of KIISE:Databases
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    • v.34 no.5
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    • pp.379-388
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    • 2007
  • Disordered streams may cause inaccurate or delayed results in window-based queries. Existing approaches usually leverage buffers to hand]e the streams. However, most of the approaches estimate the buffer size simply based on the maximum network delay in the streams, which tends to over-estimate the buffer size and result in high latency. In this paper, we propose a probabilistic approach to estimate the buffer size adaptively according to the fluctuated network delays. We first assume that intervals of tuple generations follow an exponential distribution and network delays have a normal distribution. Then, we derive an estimation function from the assumptions. The function takes a drop ratio as an input parameter, which denotes a percentage of tuple drops permissible during query execution. By describing the drop ratio in a query specification, users can control the quality of query results such as accuracy or latency according to application requirements. Our experimental results show that the proposed function has better adaptivity than the existing function based on the maximum network delay.

A SVM-based Spam Filtering System for Short Message Service (SMS) (휴대폰 SMS를 위한 SVM 기반의 스팸 필터링 시스템)

  • Joe, In-Whee;Shim, Hye-Taek
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.9B
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    • pp.908-913
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    • 2009
  • Mobile phones became important household appliance that cannot be without in our daily lives. And the short messaging service (SMS) in these mobile phones is 1.5 to 2 times more than the voice service. However, the spam filtering functions installed in mobile phones take a method to receive specific number patterns or words and recognize spam messages when those numbers or words are present. However, this method cannot properly filters various types of spam messages currently dispatched. This paper proposes a more powerful and more adaptive spam filtering system using SVM and thesaurus. The system went through a process of isolating words from sample data through pro-processing device and integrating meanings of isolated words using a thesaurus. Then it generated characteristics of integrated words through the chi-square statistics and studied the characteristics. The proposed system is realized in a Window environment and the performance is confirmed through experiments.

A Method to Suppress False Alarms of Sentinel-1 to Improve Ship Detection

  • Bae, Jeongju;Yang, Chan-Su
    • Korean Journal of Remote Sensing
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    • v.36 no.4
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    • pp.535-544
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    • 2020
  • In synthetic aperture radar (SAR) based ship detection application, false alarms frequently occur due to various noises caused by the radar imaging process. Among them, radio frequency interference (RFI) and azimuth smearing produce substantial false alarms; the latter also yields longer length estimation of ships than the true length. These two noises are prominent at cross-polarization and relatively weak at co-polarization. However, in general, the cross-polarization data are suitable for ship detection, because the radar backscatter from background sea surface is much less in comparison with the co-polarization backscatter, i.e., higher ship-sea image contrast. In order to improve the ship detection accuracy further, the RFI and azimuth smearing need to be mitigated. In the present letter, Sentinel-1 VV- and VH-polarization intensity data are used to show a novel technique of removing these noises. In this method, median image intensities of noises and background sea surface are calculated to yield arithmetic tendency. A band-math formula is then designed to replace the intensities of noise pixels in VH-polarization with adjusted VV-polarization intensity pixels that are less affected by the noises. To verify the proposed method, the adaptive threshold method (ATM) with a sliding window was used for ship detection, and the results showed that the 74.39% of RFI false alarms are removed and 92.27% false alarms of azimuth smearing are removed.

Adaptively Compensated-Disparity Prediction Scheme for Stereo Image Compression and Reconstruction (스테레오 영상 압축 및 복원을 위한 적응적 변이보상 예측기법)

  • 배경훈;김은수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.7A
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    • pp.676-682
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    • 2002
  • In this paper, an effective stereo image compression and reconstruction technique using a new adaptively compensated-disparity prediction scheme is proposed. That is, by adaptively predicting the mutual correlation between the stereo image using the proposed method, the bandwidth of the stereo input image can be compressed to the level of the conventional 2D image and the predicted image also can be effectively reconstructed using this transmitted reference image and disparity data in the receiver. Especially, in the proposed method, once the feature values are extracted from the input stereo image, then the matching window size for the predicted image reconstruction is adaptively selected in accordance with the magnitude of this feature values. From this adaptive disparity estimation method, reduction of the mismatching probability of the disparity vectors is expected and as a result, the image quality in the reconstructed image can be improved. In addition, from some experiments using the CCETT's stereo images of 'Fichier', 'Manege' and 'Tunnel', it is shown that the proposed method improves the PSNR of the reconstructed image to about 9.08 dB on average by comparing with that of the conventional methods. And also, it is found that there is almost no difference between the original image and the predicted image reconstructed through the proposed method by comparison to that of the conventional methods.

Small Target Detection Using Bilateral Filter Based on Edge Component (에지 성분에 기초한 양방향 필터 (Bilateral Filter)를 이용한 소형 표적 검출)

  • Bae, Tae-Wuk;Kim, Byoung-Ik;Lee, Sung-Hak;Kim, Young-Choon;Ahn, Sang-Ho;Sohng, Kyu-Ik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.9C
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    • pp.863-870
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    • 2009
  • Bilateral filter (BF) is a nonlinear filter for sharpness enhancement and noise removal. The BF performs the function by the two Gaussian filters, the domain filter and the range filter. To apply the BF to infrared (IR) small target detection, the standard deviation of the two Gaussian filters need to be changed adaptively between the background region and the target region. This paper presents a new BF with the adaptive standard deviation based on the analysis of the edge component of the local window, also having the variable filter size. This enables the BF to perform better and become more suitable in the field of small target detection Experimental results demonstrate that the proposed method is robust and efficient than the conventional methods.

A Narrowband Interference Excision Algorithm in the Frequency Domain for GNSS Receivers

  • Shin, Mi-Young;Park, Chan-Sik;Lee, Ho-Keun;Lee, Dae-Yearl;Hwang, Dong-Hwan;Lee, Sang-Jeong
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.2
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    • pp.359-364
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    • 2006
  • Interference can seriously degrade the performance of GPS receiver because GPS signal has extremely low power at earth surface. This paper presents a Narrowband Interference Excision Filter (NIEF) in frequency domain that removes narrowband interferences with small signal loss. A NIEF transforms the received GPS signals with interferences into the frequency domain with FFT and then compute statistics such as mean and standard deviation to determine an excision threshold. All spectrums exceeding the threshold are removed and the remaining spectrums are restored by IFFT. A NIEF effectively can remove various and strong interferences with a simple structure. However, the signal power loss is unavoidable during FFT and IFFT. Besides the hamming window and overlap technique, a threshold-whitening technique and an adaptive detection threshold are adopted to effectively reduce the signal power loss. The performance of implemented NIEF is evaluated using real signals obtained by 12 bit GPS signal acquisition board. The output of NIEF is fed into the Software Defined Receiver to evaluate the acquisition and tracking performance. Experimental results shows that many types of interference such as single-tone CWI, AM, FM, swept CWI and multi-tones CWI are effectively mitigated with small signal power loss.

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