• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.3
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• pp.59-65
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• 2004

This paper explores an image segmentation and representation method using Vector Quantization(VQ) on color and texture for content-based image retrieval system. The basic idea is a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. These schemes are used for object-based image retrieval. Features for image retrieval are three color features from HSV color model and five texture features from Gray-level co-occurrence matrices. Once the feature extraction scheme is performed in the image, 8-dimensional feature vectors represent each pixel in the image. VQ algorithm is used to cluster each pixel data into groups. A representative feature table based on the dominant groups is obtained and used to retrieve similar images according to object within the image. The proposed method can retrieve similar images even in the case that the objects are translated, scaled, and rotated.

• Journal of Broadcast Engineering
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• v.14 no.4
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• pp.501-508
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• 2009

This paper proposes an efficient transform-domain noise reduction scheme in an H.264 video encoder, where the generalized Wiener filtering is performed in a quantization process by multiplying each transform block with its adaptive multiplication factor. In practice, the computational complexity of the proposed scheme is negligible by replacing the multiplication operation with a simple look-up table method. Also, experimental results show that the proposed scheme provides outstanding noise reduction performance in an H.264 video encoder.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2074-2079
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• 2018

Global state space's optimal policy is used for offline controller in the form of table by using Dynamic Programming. If an optimal policy table has a large amount of control data, it is difficult to use the system in a low capacity system. To resolve these problem, controller using the compressed optimal policy table is proposed in this paper. A DCT is used for compression method and the cosine function is used as a basis. The size of cosine function decreased as the frequency increased. In other words, an essential information which is used for restoration is concentrated in the low frequency band and a value of small size that belong to a high frequency band could be discarded by quantization because high frequency's information doesn't have a big effect on restoration. Therefore, memory could be largely reduced by removing the information. The compressed output is stored in memory of embedded system in offline and optimal control input which correspond to state of plant is computed by interpolation with Inverse DCT in online. To verify the performance of the proposed controller, computer simulation was accomplished with a one link inverted pendulum.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2913-2929
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• 2014

Traditional vector quantization (VQ) schemes encode image blocks as VQ indices, in which there is significant similarity between the image block and the codeword of the VQ index. Thus, the method can compress an image and maintain good image quality. This paper proposes a novel lossless VQ indices compression algorithm to further compress the VQ index table. Our scheme exploits the high correlation of adjacent image blocks to search for the same VQ index with the current encoding index from the neighboring indices. To increase compression efficiency, codewords in the codebook are sorted according to the degree of similarity of adjacent VQ indices to generate a state codebook to find the same index with the current encoding index. Note that the repetition indices both on the search path and in the state codebooks are excluded to increase the possibility for matching the current encoding index. Experimental results illustrated the superiority of our scheme over other compression schemes in the index domain.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.178-180
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• 2004

In this work, we propose new method of sigma filtering for efficient filtering and preserving edge regions in DCT Domain. In block-based image compression technique, the image is first divided into non-overlapping $8{\times}8$ blocks. Then, the two-dimensional DCT is computed for each $8{\times}8$ block. Once the DCT coefficients are obtained, they are quantized using a specific quantization table. Quantization of the DCT coefficients is a lossy process, and in this step, noise is added. In this work, we combine IDCT matrix and filter matrix to a new matrix to simplify filtering process to remove noise after IDCT in spatial domain, for each $8{\times}8$ DCT coefficient block, we determine whether this block is edge or homogeneous region. If this block is edge region, we divide this $8{\times}8$ block into four $4{\times}4$ sub-blocks, and do filtering process for sub-blocks which is homogeneous region. By this process, we can remove blocking artifacts efficiently preserving edge regions at the same time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.315-323
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• 2004

In this paper we present a method to generate the bit stream of static video test patterns for testing the picture quality in DTV system. The proposed user-defined quantization table is suitable for the static video test pattern and for minimizing the deterioration of picture quality by quantization, the underflow or overflow of video buffer generated on the process of coding the static video test pattern is compensated by a adaptive zero stuffing algorithm so that optimal picture quality is implemented. Experimental result showed that the test pattern stream encoded by MPEG-2 software with the proposed algorithm had a stable bit rate and good video quality during the decoding process, which is about 3 dB higher than that of the conventional case.

• Journal of IKEEE
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• v.25 no.4
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• pp.697-702
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• 2021

Fast Fourier Transform (FFT) is a major signal processing block being widely used. For long-point FFT processing, usually more than 1024 points, its low-complexity implementation becomes very important while retaining high SQNR (Signal-to-Quantization Noise Ratio). In this paper, we present a low-complexity FFT algorithm with a simple dynamic scaling scheme. For the 2048-point pipelined FFT processing, we can reduce the number of general multipliers by half compared to the well-known radix-2 algorithm. Also, the table size for twiddle factors is reduced to 35% and 53% compared to the radix-2 and radix-2² algorithms respectively, while achieving SQNR of more than 55dB without increasing the internal wordlength progressively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12C
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• pp.1231-1238
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• 2005

This paper presents a new fast encoding algorithm for image vector quantization that incorporates the partial distances of multiple features with a multidimensional look-up table (LUT). Although the methods which were proposed earlier use the multiple features, they handles the multiple features step by step in terms of searching order and calculating process. On the other hand, the proposed algorithm utilizes these features simultaneously with the LUT. This paper completely describes how to build the LUT with considering the boundary effect for feasible memory cost and how to terminate the current search by utilizing partial distances of the LUT Simulation results confirm the effectiveness of the proposed algorithm. When the codebook size is 256, the computational complexity of the proposed algorithm can be reduced by up to the $70\%$ of the operations required by the recently proposed alternatives such as the ordered Hadamard transform partial distance search (OHTPDS), the modified $L_2-norm$ pyramid ($M-L_2NP$), etc. With feasible preprocessing time and memory cost, the proposed algorithm reduces the computational complexity to below the $2.2\%$ of those required for the exhaustive full search (EFS) algorithm while preserving the same encoding quality as that of the EFS algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.744-747
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• 1997

High performance digital computer technology enables the digital computer-based controllers to replace traditional analog controllers used for factory automations. This replacement, however, brings up the side effects caused by discrete quantization and non-real-time execution of control softwares. This paper describes the structure of real-time simulator and controller that can be used for design and verification of real-time digital controllers. The virtual machine concept adopted by real-time simulator make the proposed simulator be independent from the specific hardware platforms. The proposed system can also be used in the loosely coupled distributed environments connected through local area network using real-time message passing algorithm and virtual data table based on the shared memory mechanism.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.115-121
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• 1999

Advanced digital computer technology enables the computer-based controllers to replace the traditional analog controllers used in factory automations. This replacement, however, brings up the side effects caused by the quantization error and non-real-time execution of control software. This paper describes the structure of real-time simulator and controller that can be used for design and verification of real-time digital controllers. The virtual machine concept adopted by the proposed real-time simulator makes the proposed simulator be independent from the specific hardware platforms. The proposed system can also be used in the loosely coupled distributed environments connected through local area network using real-time message passing algorithm and virtual data table based on the shared memory mechanism.