• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.172-181
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• 2010

In this paper, we propose an adaptive block quantization method. The propose method perfrect reconstructs side information without high complexity in the encoder side, as transmitting motion vectors from a decoder to an encoder side. Also, at the encoder side, residual signals between reconstructed side information and original frame are adaptively quantized to minimize parity bits to be transmitted to the decoder. The proposed method can effectively allocate bits based on bit error rate of side information. Also, we can achieved bit-saving by transmission of parity bits based on the error correction ability of the LDPC channel decoder, because we can know bit error rate and positions of error bit in encoder side. Experimental results show that the proposed algorithm achieves bit-saving by around 66% and delay of feedback channel, compared with the convntional algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.244-249
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• 2010

The design of error correction code with low complexity has a good attraction for next generation multi-level cell flash memory. Sharing sub-expressions is effective method to reduce complexity and chip size. This paper proposes a new design method of m-bit parallel BCH encoder based on serial linear feedback shift register structure with low complexity using sub-expression. In addition, general algorithm for obtaining the sub-expression is introduced. The sub-expression can be expressed by matrix operation between sub-matrix of generator matrix and sum of two different variables. The number of the sub-expression is restricted by. The obtained sub-expressions can be shared for implementation of different m-parallel BCH encoder. This paper is not focused on solving a problem (delay) induced by numerous fan-out, but complexity reduction, expecially the number of gates.

• Smart Media Journal
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• v.9 no.1
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• pp.16-22
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• 2020

In this study, a neural network method performing both Detection and Classification of diseases and insects in paprika is proposed with Multi-Tasking U-net. Paprika on farms does not have a wide variety of diseases in this study, only two classes such as powdery mildew and mite, which occur relatively frequently are made as the targets. Aiming to this, a U-net is used as a backbone network, and the last layers of the encoder and the decoder of the U-net are utilized for classification and segmentation, respectively. As the result, the encoder of the U-net is shared for both of detection and classification. The training data are composed of 680 normal leaves, 450 mite-damaged leaves, and 370 powdery mildews. The test data are 130 normal leaves, 100 mite-damaged leaves, and 90 powdery mildews. Its test results shows 89% of recognition accuracy.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.125-131
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• 2010

This paper presents the implementation of a EBCOT TIER-1 for JPEG2000 Encoder. JPEG2000 is new standard for the compression of still image for overcome the artifact of JPEG. JPEG2000 standard is based on DWT(Discrete Wavelet Transform) and EBCOT Entropy coding technology. EBCOT(Embedded block coding with optimized truncation) is the most important technology that is compressed the image data in the JPEG2000. However, EBCOT has the artifact because the operations are bit-level processing and occupy the harf of the computation time of JPEG2000 Compression. Therefore, in this paper, we present modified context extraction method for enhance EBCOT computational efficiency and implemented MQ- Coder as arithmetic coder. The proposed system is implemented by Verilog-HDL, under the condition of TSMC 0.25um ASIC library, gate counts are 30,511EA and satisfied the 50MHz operating condition.

• The Journal of the Korean dental association
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• v.43 no.1 s.428
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• pp.41-52
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• 2005

Information Technology has extended its scope to the medical field as well as dental field. Like medical field, network ststem for dental field requires acquisition, storage, and display of images. However, unlike the medical field, the system to integrate several information including medical images has not been developed according to industrial standard for management of digital image for medical use, so called DICOM conformance. which makes the digital environment in dental field more and more difficult and expensive for this standardization and comfortable communication in LAN and WAN. To solve this problem, the DICOM encoder and server has to be developed because the DICOM file can be easily retrieved with patient's information from the DICOM server in the system as DICOM file has the standard specification to integrate the patient's information. The information including image and other discrete data can be easily integrated in DICOM file and can be used without any difficulty for precise diagnosis and for contribution to the decision making for each treatment protocol. Therefore, the system composed of DICOM encoder and server in dental practive for DICOM file must be developed with prudent consideration of the several strategic factors: I) Enhanced diagnostic capability through the integrated information of image and clinical data. ii) Clinician-friendly interface to simulate the systemic treatment procedure in clinical practice iii) Implementation of multidisciplinary treatment protocol The development of DICOM encoder and server based on these strategic considerations will provide paperless and filmless hospital environments by the seamless integration and management of patient's history, several clinical data and clinical images through image processing for quantitative analysis. The system also allows clinicians to provide more predictable dental care for the patients.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.814-819
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• 2010

This paper is presented to study the error minimization of angular velocity for AGV(autonomous ground vehicle). The error minimization of angular velocity is related to localization technique which is the most important technique for autonomous vehicle. Accelerometer, yaw gyro and electronic compass have been used to measure angular velocity. And methods for error minimization of angular velocity have been actively studied through probabilistic methods and sensor fusion for AGVs. However, those sensors still occure accumulated error by mathematical error, system characters of each sensor, and computational cost are increased greatly when several sensor are used to correct accumulated error. Therefore, this paper studies about error minimization of angular velocity that just uses encoder and gyro. To experiment, we use autonomous vehicle which is made by ourselves. In experimental result, we verified that the localization error of proposed method has even less than the localization errors which we just used encoder and gyro respectively.

• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.59-66
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• 2020

In this paper, we propose a pipe leak detection system through data collection using low-power wireless acoustic sensor modules and data analysis using deep auto-encoder. Based on the Fourier transform, we propose a low-power wireless acoustic sensor module that reduces data traffic by reducing the amount of acoustic sensor data to about 1/800, and we design the system that is robust to noise generated in the audible frequency band using only 20kHz~100kHz frequency signals. In addition, the proposed system is designed using a deep auto-encoder to accurately detect pipe leaks even with a reduced amount of data. Numerical experiments show that the proposed pipe leak detection system has a high accuracy of 99.94% and Type-II error of 0% even in the environment where high frequency band noise is mixed.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.717-724
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• 2020

Due to the important role played by emotion in human interaction, affective computing is dedicated in trying to understand and regulate emotion through human-aware artificial intelligence. By understanding, emotion mental diseases such as depression, autism, attention deficit hyperactivity disorder, and game addiction will be better managed as they are all associated with emotion. Various studies for emotion recognition have been conducted to solve these problems. In applying machine learning for the emotion recognition, the efforts to reduce the complexity of the algorithm and improve the accuracy are required. In this paper, we investigate emotion Electroencephalogram (EEG) feature reduction and classification using Stack AutoEncoder (SAE) and Long-Short-Term-Memory/Recurrent Neural Networks (LSTM/RNN) classification respectively. The proposed method reduced the complexity of the model and significantly enhance the performance of the classifiers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1018-1024
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• 2011

For the driving of the sinusoidal type permanent magnet synchronous motor with a maximum continuous torque, the 1200 delayed three phase sinusoidal current inputs which matched with the absolute rotor position are needed at the stator coil. Therefore, the detection of a absolute rotor position is required inevitably. And the right angle relationship between stator magnetic field and rotor magnetic field has to be preserved at a stator by this commutation action. The detection of a absolute position for the commutation can be made generally by the output signal analysis of the encoder attached at a motor shaft. The purposes of this study are to design signal processing logic circuits which could detect the absolute position of motor with a modern encoder system and generate the three reference wave for making sinusoidal current input at a stator coil.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11C
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• pp.1491-1497
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• 2004

The psychoacoustic model in MPEG audio layer-III (MP3) encoder is optimized for the fixed-point processing. The optimization process consists of determining the data word length of arithmetic unit and the algorithm for transcendental functions that are often used in the psychoacoustic model. In order to determine the data word length, we defined a statistical model expressing the relation between the fixed-point operation errors of the psychoacoustic model and the probability of alteration of the allocated bits doe to these errors. Based on the simulations using this model, we chose a 24-bit data path and constructed a 24-bit fixed-point MP3 encoder. Sound quality tests using the constructed fixed-point encoder showed a mean degradation of -0.2 on ITU-R 5-point audio impairment scale.