• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.38-40
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• 2007

In this paper, we propose a novel architecture, which is based on DCT (Discrete Cosine Transform), for ME (Motion Estimation) and MC (Motion Compensation). The traditional algorithms of ME and MC based on DCT did not suffer the advantage of the coarseness of the 2-dimensional DCT (2-D DCT) coefficients to reduce the operational time. Therefore, we derive a recursion equation for transform-domain ME and MC and design the structure by using highly regular, parallel, and pipeline processing elements. The main difference with others is removing the IDCT block by using to transform domain. Therefore, the performance of our algorithm is more efficient in practical image processing such as DVR (Digital Video Recorder) system. We present the simulation result which is compare with the spatial domain methods. it shows reducing the calculation cost. compression ratio. and peak signal to noise ratio (PSNR).

• Progress in Medical Physics
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• v.25 no.1
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• pp.53-63
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• 2014

The objective of this study is to investigate the difference of ITV lengths and ITVs between 4DCT and Slow-CT images according to respiratory patterns using a respiratory motion phantom. The respiratory periods 1~4 s and target motion 1~3 cm were applied on each respiratory pattern. 4DCT and Slow-CT images were acquired for 3 times. 4DCT and Slow-CT ITVs were measured with contouring the target in the Eclipse RTP system. The measured ITV lenghts and ITVs in 4DCT and Slow-CT images were compared to the known values. For the ITV lengths and ITVs in the 4DCT, the difference of them were reduced as the respiratory period is longer and target motion is shorter. For the Slow-CT, there was same tendency with change in 4DCT ITV lengths and ITVs about target motion. However, the difference of ITV lengths and ITVs for the respiratory periods were the lowest in respiratory period 1 second and different slightly within respiratory period 2-4 seconds. According to the respiratory patterns, pattern A had the highest reproducibility. Pattern B, C and D were showed the difference similar to each other. However, for pattern E, the reproducibility was the lowest compared with other four patterns. The difference of ITV lengths and ITVs between Slow-CT and 4DCT was increased by increasing the respiratory periods and target motion for all respiratory patterns. When the difference of Slow-CT ITV lengths and ITVs were compared with that of 4DCT ITV lengths and ITVs, Slow-CT ITV lengths and ITVs were approximately 22 % smaller than 4DCT, and the representations of target were different in each pattern. In case of pattern A, B and C, length difference was 3 mm at S (superior) and I (inferior) direction, and the length difference of pattern D was 1.45 cm at only "I" direction whereas the length difference of pattern E was 5 mm longer in "S" direction than "I" direction. Therefore, the margin in SI directions should be determined by considering the respiratory patterns when the margin of Slow-CT is compensated for 4DCT ITV lengths. Afterward, we think that the result of this study will be useful to analyze the ITV lengths and ITVs from the CT images on the basis of the patient respiratory signals.

• Journal of Microbiology
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• v.38 no.3
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• pp.176-179
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• 2000

A challenge phage system was used to study the DNA-protein interaction between C4-dicarboxylic acid transport protein D(DCTD) or $\sigma$54, and a $\sigma$54 -dependent promoter, dctAp. R. meliloti dctA promoter regulatory region replaced the Omnt site on the phage. S. typhimurium strains overproducing either DCTD or $\sigma$54 directed this challenge phage towards lysogency, indicating that DCTD or E$\sigma$54 recognized the dctA promoter on the phage and repressed transcription of the ant gene. These challenge phage constructs will be useful for examining interactions between DCTD(or $\sigma$54) and the dctA promoter region.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.553-565
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• 2021

Point cloud is a set of points for representing a 3D object, and consists of geometric information, which is 3D coordinate information, and attribute information, which is information representing color, reflectance, and the like. In this way of expressing, it has a vast amount of data compared to 2D images. Therefore, a process of compressing the point cloud data in order to transmit the point cloud data or use it in various fields is required. Unlike color information corresponding to all 2D geometric information constituting a 2D image, a point cloud represents a point cloud including attribute information such as color in only a part of the 3D space. Therefore, separate processing of geometric information is also required. Based on these characteristics of point clouds, MPEG under ISO/IEC standardizes V-PCC, which imitates point cloud images and compresses them into 2D DCT-based 2D image compression codecs, as a compression method for high-density point cloud data. This has limitations in accurately representing 3D spatial information to proceed with compression by converting 3D point clouds to 2D, and difficulty in processing non-existent points when utilizing 3D DCT. Therefore, in this paper, we present 3D Discrete Cosine Transform-based Point Cloud Compression (3DCT PCC), a method to compress point cloud data, which is a 3D image by utilizing 3D DCT, and confirm the efficiency of 3D DCT compared to V-PCC based on 2D DCT.

• 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.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.51-59
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• 2016

This paper presents a method of DCT-based illuminant compensation to enhance the accuracy of face recognition under an illuminant change. The basis of the proposed method is that the illuminant is generally located in low-frequency components in the DCT domain. Therefore, the effect of the illuminant can be compensated by controlling the low-frequency components. Moreover, a directional high-order local pattern descriptor is used to detect robust features in the case of face motion. Experiments confirm the performance of the proposed algorithm got up to 95% when tested using a real database.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.8
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• pp.1227-1237
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• 1989

In this paper, we propose a lossless progressive image transmission scheme using hierarchical pyramid structure and classified vector quantizer in DCT domain. By adopting DCT to the hierarchical pyramid signals, we can reduce the spatial redundance. Moreover, the DCT coefficients can be encoded efficiently by using classified vector quantizer in DCT domain. The classifier is simply based on the variance of a subblock. Also, the mirror set of training set of images can improve the robustness of codebooks. Progressive image transmission can be achieved through following processes: from top to bottom level of planes in a pyramid, and from high to low AC variance class in a plane. Some simulation results with real images show that the proposed coding scheme yields a good performance at below 0.3 bpp and an excellent result at 0.409 bpp. The proposed coding scheme is well suited for lossless progressive image transmission as well as image data compression.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.267-272
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• 2007

This paper proposes a new approach fur the detection of facial feature regions using the characteristic of DCT(discrete cosine transformation) thatconcentrates the energy of an image into lower frequency coefficients. Since the facial features are pertained to relatively high frequency in a face image, the inverse DCT after removing the DCT's coefficients corresponding to the lower frequencies generates the image where the facial feature regions are emphasized. Thus the facial regions can be easily segmented from the inversed image using any differential operator. In the segmented region, facial features can be found using face template. The proposed algorithm has been tested with the image MIT's CBCL DB and the Yale facedatabase B. The experimental results have shown superior performance under the variations of image size and lighting condition.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.97-106
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• 1999

We propose a new watermarking method to embed a label in a video which is robust against the change of the group of picture. The proposed method embeds labels in the pixel domain, but detects the label in the DCT frequency domain. For embedding a label, the size of watermark based on the human visual system is calculated to keep a quality of videos. A lookup table haying the pixel patterns and the sequences of a sign of DCT coefficients is used for detecting a label in the DCT frequency domain. In this paper, we analyze bit error rates for labels of videos compressed by MPEG2 using the central limit theorem and compare the simulation results with previous methods.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.605-608
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• 1999

A conventional image coder, such as JPEG, requires not only DCT and quantization but also additional pre-filtering under noisy environment. Since the pre-filtering removes camera noise and improves coding efficiency dramatically, its efficient implementation has been an important issue. Based on well-known noise removal techniques in image processing fields, this paper introduces an efficient scheme by adapting a noise removal procedure to block-based image coders. By using two-dimensional DCT factorization, the proposed image coder has only a modified DCT and a VLC, and performs pre-filtering and quantization simultaneously in the modified DCT operation.