• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.1
• /
• pp.121-126
• /
• 2003

In this paper, we propose a new wavelet-based fuzzy modeling using a DNA coding method. Generally, it is well known that the DNA coding method is more diverse in the knowledge expression and better in the optimization performance than the genetic algorithm (GA) because it can encode more plentiful genetic informations based on the biological DNA. The proposed method can construct a fuzzy model using the wavelet transform, in which the coefficients are identified by the DNA coding method. Thus, we can effectively get the fuzzy model of the nonlinear system by using the advantages of both wavelet transform and DNA coding method. In order to demonstrate the superiority of the proposed method, it is compared with modeling method using the conventional GA.

• IEIE Transactions on Smart Processing and Computing
• /
• v.1 no.3
• /
• pp.171-181
• /
• 2012

In the new video coding standard, called high efficiency video coding (HEVC), the coding unit (CU) is adopted as a basic unit of a coded block structure. Therefore, the rate control (RC) methods of H.264/AVC, whose basic unit is a macroblock, cannot be applied directly to HEVC. This paper proposes the largest CU (LCU) level RC method for hierarchical video coding in a HEVC. In the proposed method, the effective bit allocation is performed first based on the hierarchical structure, and the quantization parameters (QP) are then determined using the Cauchy density based rate-quantization (RQ) model. A novel method based on the linear rate model is introduced to estimate the parameters of the Cauchy density based RQ model precisely. The experimental results show that the proposed RC method not only controls the bitrate accurately, but also generates a constant number of bits per second with less degradation of the decoded picture quality than with the fixed QP coding and latest RC method for HEVC.

• The Journal of the Acoustical Society of Korea
• /
• v.19 no.3
• /
• pp.26-34
• /
• 2000

In this paper, we propose a 4kbps speech coder that combines the harmonic vector excitation coding with time-separated transition coding. The harmonic vector excitation coding uses the harmonic excitation coding in the voiced frame and uses the vector excitation coding with the structure of analysis-by-synthesis in the unvoiced frame, respectively. But two mode coding method is not effective for transition frame mixed in voiced and unvoiced signal and a new method beyond using unvoiced/voiced mode coding is needed. Thus, we designed a time-separated transition coding method for transition frame in which a voiced/unvoiced decision algorithm separates unvoiced and voiced duration in a frame, and harmonic-harmonic excitation coding and vector-harmonic excitation coding method is selectively used depending on the previous frame U/V decision. In the decoder, the voiced excitation signals are generated efficiently through the inverse FFT of harmonic magnitudes and the unvoiced excitation signals are made by the inverse vector quantization. The reconstructed speech signal are synthesized by the Overlap/Add method.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.6C
• /
• pp.355-360
• /
• 2011

In this paper, we propose a new context-based adaptive binary arithmetic coding (CABAC) method for lossless image compression. Since the conventional CABAC in H.264/AVC was originally designed for lossy coding, it does not yield adequate performance during lossless coding. Therefore, we proposed an improved CABAC method for lossless intra coding by considering the statistical characteristics of residual data in lossless intra coding. Experimental results showed that the proposed method reduced the bit rate by 18.2%, compared to the conventional CABAC for lossless intra coding.

• Journal of Broadcast Engineering
• /
• v.14 no.5
• /
• pp.601-615
• /
• 2009

This paper proposes an efficient depth-map coding method for generating virtual-view images in 3D-Video. Virtual-view images can be generated by the view-interpolation based on the depth-map of the image. A conventional video coding method such as H.264 has been used. However, a conventional video coding method does not consider the image characteristics of the depth-map. Therefore, this paper proposes an adaptive depth-map coding method that can select between the H.264/AVC coding scheme and the proposed gray-coded bit plane-based coding scheme in a unit of block. This improves the coding efficiency of the depth-map data. Simulation results show that the proposed method, in comparison with the H.264/AVC coding scheme, improves the average BD-rate savings by 7.43% and the average BD-PSNR gains by 0.5dB. It also improves the subjective picture quality of synthesized virtual-view images using decoded depth-maps.

• Smart Media Journal
• /
• v.1 no.2
• /
• pp.6-11
• /
• 2012

In the HEVC standard, transform coefficient coding that affects the output bitstream directly is a core part of the encoder and it includes coefficient scanning and entropy coding. Recently, JCT-VC(Joint Collaborative Team on Video Coding) advances to HEVC Committee Draft (CD). In this paper, we explain HEVC transform coefficient coding and propose an efficient transform coefficient coding method considering statistics of transform coefficients in the intra frame coder. The proposed method reduces BD-Rate by up to 0.74%, compared to the conventional HEVC transform coefficient coding.

• Journal of Yeungnam Medical Science
• /
• v.36 no.3
• /
• pp.225-230
• /
• 2019

Background: It is not possible to measure how much activity is required to understand and code a medical data. We introduce an assessment method in clinical coding, and applied this method to neurosurgical terms. Methods: Coding activity consists of two stages. At first, the coders need to understand a presented medical term (informational activity). The second coding stage is about a navigating terminology browser to find a code that matches the concept (code-matching activity). Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) was used for the coding system. A new computer application to record the trajectory of the computer mouse and record the usage time was programmed. Using this application, we measured the time that was spent. A senior neurosurgeon who has studied SNOMED CT has analyzed the accuracy of the input coding. This method was tested by five neurosurgical residents (NSRs) and five medical record administrators (MRAs), and 20 neurosurgical terms were used. Results: The mean accuracy of the NSR group was 89.33%, and the mean accuracy of the MRA group was 80% (p=0.024). The mean duration for total coding of the NSR group was 158.47 seconds, and the mean duration for total coding of the MRA group was 271.75 seconds (p=0.003). Conclusion: We proposed a method to analyze the clinical coding process. Through this method, it was possible to accurately calculate the time required for the coding. In neurosurgical terms, NSRs had shorter time to complete the coding and higher accuracy than MRAs.

• ETRI Journal
• /
• v.36 no.4
• /
• pp.528-536
• /
• 2014

High Efficiency Video Coding (HEVC) is the most recent video coding standard to achieve a higher coding performance than the previous H.264/AVC. In order to accomplish this improved coding performance, HEVC adopted several advanced coding tools; however, these cause heavy computational complexity. Similar to previous video coding standards, motion estimation (ME) of HEVC requires the most computational complexity; this is because ME is conducted for three inter prediction modes - namely, uniprediction in list 0, uniprediction in list 1, and biprediction. In this paper, we propose an efficient inter prediction mode (EIPM) decision method to reduce the complexity of ME. The proposed EIPM method computes the priority of all inter prediction modes and performs ME only on a selected inter prediction mode. Experimental results show that the proposed method reduces computational complexity arising from ME by up to 51.76% and achieves near similar coding performance compared to HEVC test model version 10.1.

• Proceedings of the IEEK Conference
• /
• 2002.07b
• /
• pp.1003-1006
• /
• 2002

In the communications systems with diversity, we are commonly faced on needing of new source coding technique, error resilient coding. The error resilient coding addresses the coding algorithm that has the robustness to unreliability of communications channel. In recent years, many error resilient coding techniques were proposed such as data partitioning, resynchronization, error detection, concealment, reference picture selection and multiple description coding (MDC). Especially, the MDC using correlating transform explicitly adds correlation between two descriptions to enable the estimation of one set from the other. However, in the conventional correlating transform method, there is a critical problem that decoder must know statistics of original image. In this paper, we propose an enhanced method, the MDC using whitening transform that is not necessary additional statistical information to decode image because the DCT coefficients to apply whitening transform to an image have uni-variance statistics. Our experimental results show that the proposed method achieves a good trade-off between the coding efficiency and the reconstruction quality. In the proposed method, the PSNR of images reconstructed from two descriptions is about 0.7dB higher than conventional method at the 1.0 BPP and from only one description is about 1,8dB higher at the same rate.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2314-2316
• /
• 2000

In the construction of successful fuzzy models and/or controllers for nonlinear systems, identification of a good fuzzy Neural inference system is an important yet difficult problem, which is traditionally accomplished by trial and error process. In this paper, we propose a systematic identification procedure for complex multi-input single- output nonlinear systems with DNA coding method.DNA coding method is optimization algorithm based on biological DNA as are conventional genetic algothms (GAs). We also propose a new coding method for applying the DNA coding method to the identification of fuzzy Neural models. To acquire optimal TS fuzzy model with higher accuracy and economical size, we use the DNA coding method to optimize the parameters and the number of fuzzy inference system.