• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.731-740
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• 2003

Since motion estimation remove the redundant data to employ the temporal correlations between adjacent frames in a video sequence, it plays an important role in digital video coding. And in the block matching algorithm, search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image quality. In this paper, we propose a new fast block matching algorithm using the small-cross search pattern and the block-based gradient descent search pattern. Our algorithm first finds the motion vectors that are close to the center of search window using the small-cross search pattern, and then quickly finds the other motion vectors that are not close to the center of search window using the block-based gradient descent search pattern. Through experiments, compared with the block-based gradient descent search algorithm(BBGDS), the proposed search algorithm improves as high as 26-40% in terms of average number of search point per motion vector estimation.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1037-1044
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• 2007

Recently, we extract the representative melody of the music and index the music to reduce searching time at the content-based music retrieval system. The existing study has used MIDI data to extract a representative melody but it has a weak point that can use only MIDI data. Therefore, this paper proposes a representative melody retrieval method that can be use at all audio file format and uses digital signal processing. First, we use Fast Fourier Transform (FFT) and find the tempo and node for the representative melody retrieval. And we measure the frequency of high value that appears from PCM Data of each node. The point which the high value is gathering most is the starting point of a representative melody and an eight node from the starting point is a representative melody section of the audio data. To verity the performance of the method, we chose a thousand of the song and did the experiment to extract a representative melody from the song. In result, the accuracy of the extractive representative melody was 79.5% among the 737 songs which was found tempo.

• Journal of KIISE:Software and Applications
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• v.27 no.4
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• pp.422-431
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• 2000

This paper proposes a new codebook generation method, called a PCA-Based VQ, that incorporates the PCA (Principal Component Analysis) technique into VQ (Vector Quantization) codebook design. The PCA technique reduces the data dimensions by transforming input image vectors into the feature vectors. The cluster of feature vectors in the transformed domain is bisectioned into two subclusters by an optimally chosen partitioning hyperplane. We expedite the searching of the optimal partitioning hyperplane that is the most time consuming process by considering that (1) the optimal partitioning hyperplane is perpendicular to the first principal axis of the feature vectors, (2) it is located on the equilibrium point of the left and right cluster's distortions, and (3) the left and right cluster's distortions can be adjusted incrementally. This principal axis bisectioning is successively performed on the cluster whose difference of distortion between before and after bisection is the maximum among the existing clusters until the total distortion of clusters becomes as small as the desired level. Simulation results show that the proposed PCA-based VQ method is promising because its reconstruction performance is as good as that of the SOFM (Self-Organizing Feature Maps) method and its codebook generation is as fast as that of the K-means method.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.649-658
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• 2003

We propose a hierarchical architecture of ART2 Network for performance improvement and fast pattern classification model using fitness selection. This hierarchical network creates coarse clusters as first ART2 network layer by unsupervised learning, then creates fine clusters of the each first layer as second network layer by supervised learning. First, it compares input pattern with each clusters of first layer and select candidate clusters by fitness measure. We design a optimized fitness function for pruning clusters by measuring relative distance ratio between a input pattern and clusters. This makes it possible to improve speed and accuracy. Next, it compares input pattern with each clusters connected with selected clusters and finds winner cluster. Finally it classifies the pattern by a label of the winner cluster. Results of our experiments show that the proposed method is more accurate and fast than other approaches.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.889-897
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• 1999

This paper deals with a problem searching a target transfer function to meet the time-domain specifications for feedback system with given plant transfer function. For the Type I system, we first define three forms of transient response to unit step input, which are named by F, M, S-type. These are charaacterized as follows ; F-type has fast initial response and slow approach to the steady sate after reaching at 90% of the steady state value, S-type has slow initial response but fast approach to the steady state, and M-type is denoted by highly smooth response between F-type and S-type. Three prototypes corresponding to each form are proposed, time. For the order $n{\geq}4$, after determining admissible root structures of target characteristic polynomials empirically and expressing such polynomial coefficients by using special parameters ${\gamma}_i$ and $\epsilon$, the optimal prototypes that minimize the integral of the squared of the modified errors(ISME) have been obtained. Since the step responses of these prototypes have almost same wave forms irrespective to the order, the desired settling time or the rise time can be converted into the equibalent time constant $\tau$ and thus it is easy to obtain a target transfer function. It is shown through a design example that the present prototype is very useful for meeting the time-domain specifications and has been compared with different methods with a viewpoint of pertinence.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.559-566
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• 2012

In this paper, we propose a fast fractal image coding algorithm to shorten long time to take on fractal image encoding. For its performance evaluation, the algorithm compares with other traditional fractal coding methods. In the traditional fractal image coding methods, an original image is contracted by a factor in order to make the corresponding image to be compared with. Then, the whole area of the contracted image is searched in order to find the fixed point of contractive transformation of the original image corresponding to the contracted image. It needs a lot of searching time on encoding. However, the proposed algorithm considerably reduces encoding time by using scaling method and limited search area method. On comparison of the proposed algorithm with Jacquin's method, the proposed algorithm is dozens of times as fast as that of Jacquin's method on encoding time with a little degradation of the decoded image quality and a little increase of the compression rate. Therefore, it is found that the proposed algorithm largely improves the performance in the aspect of encoding time when compared with other fractal image coding methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1232-1239
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• 2006

In video standards such as MPEG-1/2/4 and H.264/AVC, motion estimation / compensation(ME/MC) process causes the most encoding complexity of video encoder. The full search method, which is used in general video codecs, exhausts much encoding time because it compares current macroblock with those at all positions within search window for searching a matched block. For the alleviation of this problem, the fast search methods such as TSS, NTSS, DS and HEXBS are exploited at first. Thereafter, DS based MVFAST, PMVFAST, MAS and FAME, which utilize temporal or spacial correlation characteristics of motion vectors, are developed. But there remain the problems of image quality degradation and algorithm complexity increase. In this thesis, the proposed algorithm maximizes search speed and minimizes the degradation of image quality by determining initial search point correctly and using simple one-dimension search patterns considering motion characteristics of each frame.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.2
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• pp.95-102
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• 2010

This paper proposes a SPIT(Spam over IP Telephony) prevention framework which is using expanded white-list in real-time VoIP environment. The existing schemes are vulnerable to attack from spammers since they can continue to transfer SPIT upon changing their ID. And existing frameworks have experienced the time delay and overload as session initiates due to real-time operation. To solve these problems, the proposed scheme expands the scope of white lists by forming social networks using the white list, but it is to decide quickly whether pass a caller ID without searching the entire database. The proposed framework takes the three-stage architecture and the fast scoring system. The proposed framework minimize user's inconvenience and time delay for initiation of session, therefore, it is proper for real-time VoIP environment.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.638-648
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• 2000

This paper introduces a new technique for block is matching motion estimation. Since the temporal correlation of the image sequence, the motion vector of a block is highly related to the motion vector of the same coordinate block in the previous image frame. If we can obtain useful and enough information from the motion vector of the same coordinate block of the previous frame, the total number of search points used to find the motion vector of the current block may be reduced significantly. Using that idea, an efficient predicted direction search algorithm (PDSA) for block matching algorithm is proposed. Based on the direction of the blocks of the two successive previous frames, if the direction of the to successive blocks is same, the first search point of the proposed PDSA is moved two pixels to the direction of the block. The searching process after moving the first search point is processed according to the fixed search patterns. Otherwise, full search is performed with search area $\pm$2. Simulation results show that PSNR values are improved up to the 3.4dB as depend on the image sequences and improved about 1.5dB on an average. Search times are reduced about 20% than the other fast search algorithms. Simulation results also show that the performance of the PDSA scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS(Full Search) algorithm.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.93-98
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• 2012

Recently, we can easily create high resolution images with digital cameras for high-performance and make use them at variety fields. Especially, the image stitching method which adjusts couple of images has been researched. Image stitching can be used for military purposes such as satellites and reconnaissance aircraft, and computer vision such as medical image and the map. In this paper, we have proposed fast image stitching based on improved SURF algorithm using meaningful features in the process of images matching after extracting features from scenery image. The features are extracted in each image to find out corresponding points. At this time, the meaningful features can be searched by removing the error, such as noise, in extracted features. And these features are used for corresponding points on image matching. The total processing time of image stitching is improved due to the reduced time in searching out corresponding points. In our results, the processing time of feature matching and image stitching is faster than previous algorithms, and also that method can make natural-looking stitched image.