• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.27-34
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• 2004

This paper proposes a method to trace and interpret a moving object based on the information which can be directly obtained from MPEG-2 compressed video stream without decoding process. In the proposed method, the motion flow is constructed from the motion vectors included in compressed video. We calculate the amount of pan, tilt, and zoom associated with camera operations using generalized Hough transform. The local object motion can be extracted from the motion flow after the compensation with the parameters related to the global camera motion. Initially, a moving object to be traced is designated by user via bounding box. After then automatic tracking Is performed based on the accumulated motion flows according to the area contributions. Also, in order to reduce the cumulative tracking error, the object area is reshaped in the first I-frame of a GOP by matching the DCT coefficients. The proposed method can improve the computation speed because the information can be directly obtained from the MPEG-2 compressed video, but the object boundary is limited by macro-blocks rather than pixels. Also, the proposed method is proper for approximate object tracking rather than accurate tracing of an object because of limited information available in the compressed video data.

• Journal of Biomedical Engineering Research
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• v.16 no.4
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• pp.507-516
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• 1995

The nonstationary identifier in the DCT domain is suggested in this study for the identification of AR parameters of above-lesion upper-trunk electromyographic (EMG) signals as a means of developing a reliable real time signal to control functional electrical stimulation (FES) in paraplegics to enable primitive walking. As paraplegic shifts his posture from one attitude to another, there is transition period where the signal is clearly nonstationary. Also as muscle fatigues, nonstationarities become more prevalent even during stable postures. So, it requires a develpment of time varying nonstationary EMG signal identifier. In this paper, time varying nonstationary EMG signals are transformed into DCT domain and the transformed EMG signals are modeled and analyzed in the transform domain. In the DCT domain, we verified reduction of condition number and increment of the smallest eigenvalue of input correlation matrix that influences numerical properties and mean square error were compared with SLS algorithm, and the proposed algorithm is implemented using IMS T-805 parallel processing computer for real time application.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.58-65
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• 2002

In order to reduce blocking artifacts in inter-frame coded images, we propose a new image restoration algorithm, which directly processes differential images before reconstruction. We note that blocking artifact in inter-frame coded images is caused by both 8$\times$8 DCT and 16$\times$16 macroblock based motion compensation, while that of intra-coded images is caused by 8$\times$8 DCT only. According to the observation, we Propose a new degradation model for differential images and the corresponding restoration algorithm that utilizes additional constraints and convex sets for discontinuity inside blocks. The proposed restoration algorithm is a modified version of standard regularization that incorporate!; spatially adaptive lowpass filtering with consideration of edge directions by utilizing a part of DCT coefficients. Most of video coding standard adopt a hybrid structure of block-based motion compensation and block discrete cosine transform (BDCT). By this reason, blocking artifacts are occurred on both block boundary and block interior For more complete removal of both kinds of blocking artifacts, the restored differential image must satisfy two constraints, such as, directional discontinuities on block boundary and block interior Those constraints have been used for defining convex sets for restoring differential images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.48-60
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• 2007

In previous researches for iris feature extraction, they transform a original iris image into rectangular one by stretching and interpolation, which causes the distortion of iris patterns. Consequently, it reduce iris recognition accuracy. So we are propose the method that extracts iris feature by using polar coordinates without distortion of iris patterns. Our proposed method has three strengths compared with previous researches. First, we extract iris feature directly from polar coordinate circular iris image. Though it requires a little more processing time, there is no degradation of accuracy for iris recognition and we compares the recognition performance of polar coordinate to rectangular type using by Hamming Distance, Cosine Distance and Euclidean Distance. Second, in general, the center position of pupil is different from that of iris due to camera angle, head position and gaze direction of user. So, we propose the method of iris feature detection based on polar coordinate circular iris region, which uses pupil and iris position and radius at the same time. Third, we overcome override point from iris patterns by using polar coordinates circular method. each overlapped point would be extracted from the same position of iris region. To overcome such problem, we modify Gabor filter's size and frequency on first track in order to consider low frequency iris patterns caused by overlapped points. Experimental results showed that EER is 0.29%, d' is 5,9 and EER is 0.16%, d' is 6,4 in case of using conventional rectangular image and proposed method, respectively.

• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.637-646
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• 2005

Most of the multimedia contents for DBM services art provided as MPEG-2 bit streams. However, they have to be transcoded to H.264 bit streams for practical services because the standard video codec for DMB is H.264. The existing transcoder architecture is Cascaded Pixel-Domain Transcoding Architecture, which consists of the MPEG-2 dacoding phase and the H.264 encoding phase. This architecture can be easily implemented using MPEG-2 decoder and H.264 encoder without source modifying. However. It has disadvantages in transcoding time and DCT-mismatch problem. In this paper, we propose two kinds of transcoder architecture, DCT-OPEN and DCT-CLOSED, to complement the CPDT architecture. Although DCT-OPEN has lower PSNR than CPDT due to drift problem, it is efficient for real-time transcoding. On the contrary, the DCT-CLOSED architecture has the advantage of PSNR over CPDT at the cost of transcoding time.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.1-10
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• 2011

While the broadband network and multimedia technologies have been developing, the commercial market of digital contents has also been widely spreading with recently starting IPTV. Generally, PC player can display digital contents obtained through middleware like a settop box and can only bring the informations about contents like CODEC, bitrate etc. useful for only experts. But general users want to know more optional informations like content's subject, description etc. So unlike previous PC player, we proposed a player system that can get inserted informations, namely EPG(Electronic Program Guide), without database after bringing contents to PC through settop box. In addition, we also proposed DCT(Discrete Cosine Transform) based blind watermark generating method to insert EPG informations. We can extract watermark without original image and insert robust watermark in proportion to coefficients in frequency domain. And we analyzed and parsed PSI data from MPEG-TS. So we could insert wanted information using watermark from EPG. And we composed UI by extracting EPG information from watermark interted contents. Finally we modularized whole system into the watermark insert/extract application and directshow filter based player. So we tried to design this system so that the general developer can do in a way that is easier and faster.

• The Journal of the Acoustical Society of Korea
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• v.30 no.8
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• pp.446-460
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• 2011

The use of induction motors has been recently increasing with automation in aeronautical and automotive industries, and it playes a significant role. This has motivated that many researchers have studied on developing fault detection and classification systems of an induction motor in order to minimize economical damage caused by its fault. With this reason, this paper proposed feature vector extraction methods based on STE (short-time energy)+SVD (singular value decomposition) and DCT (discrete cosine transform)+SVD techniques to early detect and diagnose faults of induction motors, and classified faults of an induction motor into different types of them by using extracted features as inputs of BPNN (back propagation neural network) and multi-layer SVM (support vector machine). When BPNN and multi-lay SVM are used as classifiers for fault classification, there are many settings that affect classification performance: the number of input layers, the number of hidden layers and learning algorithms for BPNN, and standard deviation values of Gaussian radial basis function for multi-layer SVM. Therefore, this paper quantitatively simulated to find appropriate settings for those classifiers yielding higher classification performance than others.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.3 s.345
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• pp.48-58
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• 2006

This paper presents 8x8 two dimensional DCT/IDCT processor of adder-based distributed arithmetic architecture without applying ROM units in conventional memories. To reduce hardware cost in the coefficient matrix of DCT and IDCT, an odd part of the coefficient matrix was shared. The proposed architecture uses only 29 adders to compute coefficient operation in the 2-D DCT/IDCT processor, while 1-D DCT processor consists of 18 adders to compute coefficient operation. This architecture reduced 48.6% more than the number of adders in 8x8 1-D DCT NEDA architecture. Also, this paper proposed a form of new transpose network which is different from the conventional transpose memory block. The proposed transpose network block uses 64 registers with reduction of 18% more than the number of transistors in conventional memory architecture. Also, to improve throughput, eight input data receive eight pixels in every clock cycle and accordingly eight pixels are produced at the outputs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.31-37
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• 2015

The security of the image information is very important in many areas of the IoT(Internet of Things), and study a number of ways to display the security (copyright, etc.). In this paper, information of image that is used by the IoT is converted to a DCT(Discrete Cosine Transform) and QC(Quantization Coefficient). And watermark (message) is to create a new encoded message(WMQR) through a QR Code. QC and WMQR applies LSB steganography techniques, can get the security (copyright, etc.) of image information. LSB steganographic techniques may be inserted according to a message (Watermark) to determine the location (Secret Key). The encoded image is sent to the recipient via the Internet. The reverse process can be obtained image and a QR code, a watermark (Message). A method for extracting a watermark from the security of the image information is coded using only the image and Secret Key, through the DCT and quantization process, so obtained by separating the watermark (Message) for the image. In this paper, we were able to improve the security of the method of image information, the image quality of the image by the simulations (PSNR), in turn, benefits were also normalized correlation (NC) and security.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.13-20
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• 2005

In this paper, I recognized Korean isolated words using CVEM which is suggested by M. Bilginer et al. CVEM is an algorithm which is easy to extract the common properties from training voice signals and also doesn't need complex calculation. In addition CVEM shows high accuracy in recognition results. But, CVEM has couple of problems which are impossible to use for many training voices and no discriminant information among extracted common vectors. To get the optimal common vectors from certain voice classes, various voices should be used for training. But CVEM is impossible to get continuous high accuracy in recognition because CVEM has a limitation to use many training voices and the absence of discriminant information among common vectors can be the source of critical errors. To solve above problems and improve recognition rate, k-clustering subspace method and DCVEM suggested. And did various experiments using voice signal database made by ETRI to prove the validity of suggested methods. The result of experiments shows improvements in performance. And with proposed methods, all the CVEM problems can be solved with out calculation problem.