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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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The KIPS Transactions:PartB
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Korea Information Processing Society
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Volume & Issues
Volume 11B, Issue 7 - Dec 2004
Volume 11B, Issue 6 - Oct 2004
Volume 11B, Issue 5 - Aug 2004
Volume 11B, Issue 4 - Aug 2004
Volume 11B, Issue 3 - Jun 2004
Volume 11B, Issue 2 - Apr 2004
Volume 11B, Issue 1 - Feb 2004
Volume 11, Issue 2 - 00 2004
Volume 11, Issue 1 - 00 2004
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A Feedback Buffer Control Algorithm for H.264 Video Coding
Son Nam Rye ; Lee Guee Sang ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 625~632
DOI : 10.3745/KIPSTB.2004.11B.6.625
Since the H.264 encoding adopts both forward prediction and hi-direction prediction modes and exploits Variable Length Coding(VLC), the amount of data generated from video encoder varies as Flaying time goes by. The fixed bit rate encoding system which has limited transmission channel capacity uses a buffer to control output bitstream It`s necessary to control the bitstream to maintain within manageable range so as to protect buffer from overflow or underflow. With existing bit amount control algorithms, the
which is relationship between distortion value and quantization parameter often excesses normal value to end up with video error. This paper proposes an algorithm to protect buffer from overflow or underflow by introducing a new quantization parameter against distortion value of H.264 video data. The test results of 6 exemplary data show that the proposed algorithm has the same PSNR as and up to 8% reduced bit rate against existing algorithms.
A NTSS of 3 Levels Block Matching Algorithm using Multi-Resolution
Joo Heon-Sik ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 633~644
DOI : 10.3745/KIPSTB.2004.11B.6.633
In this paper, we notice that the original NTSS algorithm can be proposed as the NTSS-3 Level algorithm by the multi-resolution technique. The fast block matching algorithm affects the speed by the patten combination and this paper proposes the block matching algorithm in different levels by multi-resolution technique, quite different from the original NTSS Patten. The block matching algorithm requires the multi-candidate to reduce the occurrence of low-image quality by the local minima problem. The simulation result compared to FS shows search speed 16 times quicker, and the PSNR 0.11-0.12［dB］ gets improved Image quality compared to the original fast block matching algorithm NTSS, and the speed is improved up to 0.1 times for improved image by the search point portion.
An Off-line Signature Verification Using PCA and LDA
Ryu Sang-Yeun ; Lee Dae-Jong ; Go Hyoun-Joo ; Chun Myung-Geun ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 645~652
DOI : 10.3745/KIPSTB.2004.11B.6.645
Among the biometrics, signature shows more larger variation than the other biometrics such as fingerprint and iris. In order to overcome this problem, we propose a robust offline signature verification method based on PCA and LDA. Signature is projected to vertical and horizontal axes by new grid partition method. And then feature extraction and decision is performed by PCA and LDA. Experimental results show that the proposed offline signature verification has lower False Reject Rate(FRR) and False Acceptance Rate(FAR) which are 1.45% and 2.1%, respectively.
Efficient Algorithms for Motion Parameter Estimation in Object-Oriented Analysis-Synthesis Coding
Lee Chang Bum ; Park Rae-Hong ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 653~660
DOI : 10.3745/KIPSTB.2004.11B.6.653
Object-oriented analysis-synthesis coding (OOASC) subdivides each image of a sequence into a number of moving objects and estimates and compensates the motion of each object. It employs a motion parameter technique for estimating motion information of each object. The motion parameter technique employing gradient operators requires a high computational load. The main objective of this paper is to present efficient motion parameter estimation techniques using the hierarchical structure in object-oriented analysis-synthesis coding. In order to achieve this goal, this paper proposes two algorithms : hybrid motion parameter estimation method (HMPEM) and adaptive motion parameter estimation method (AMPEM) using the hierarchical structure. HMPEM uses the proposed hierarchical structure, in which six or eight motion parameters are estimated by a parameter verification process in a low-resolution image, whose size is equal to one fourth of that of an original image. AMPEM uses the same hierarchical structure with the motion detection criterion that measures the amount of motion based on the temporal co-occurrence matrices for adaptive estimation of the motion parameters. This method is fast and easily implemented using parallel processing techniques. Theoretical analysis and computer simulation show that the peak signal to noise ratio (PSNR) of the image reconstructed by the proposed method lies between those of images reconstructed by the conventional 6- and 8-parameter estimation methods with a greatly reduced computational load by a factor of about four.
An Efficient Error Concealment Algorithm using Adaptive Selection of Adjacent Motion Vectors
Lee Hyun-Woo ; Seong Dong-Su ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 661~666
DOI : 10.3745/KIPSTB.2004.11B.6.661
In the wireless communication systems, transmission errors degrade the reconstructed image quality severely. Error concealment in video communication is becoming increasingly important because transmission errors can cause single or multiple loss of macroblocks in video delivery over unreliable channels such as wireless networks and internet. Among various techniques which can reduce the degradation of video quality, the error concealment techniques yield good performance without overheads and the modification of the encoder. In this paper, lost image blocks can be concealed with the OBMC(Overlapped Block Motion Compensation) after new motion vectors of the lost image blocks are allocated by median values using the adaptive selection with motion vectors of adjacent blocks. We know our algorithm is more effective in case of continuous GOB loss. The results show a significant improvement over the zero motion error concealment and other temporal concealment methods such as Motion Vector Rational Interpolation or Median＋OBMC by 3dB gain in PSNR.
Text Region Verification in Natural Scene Images using Multi-resolution Wavelet Transform and Support Vector Machine
Bae Kyungsook ; Choi Youngwoo ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 667~674
DOI : 10.3745/KIPSTB.2004.11B.6.667
Extraction of texts from images is a fundamental and important problem to understand the images. This paper suggests a text region verification method by statistical means of stroke features of the characters. The method extracts 36 dimensional features from
sized text and non-text images using wavelet transform - these 36 dimensional features express stroke and direction of characters - and select 12 sub-features out of 36 dimensional features which yield adequate separation between classes. After selecting the features, SVM trains the selected features. For the verification of the text region, each
image block is scanned and classified as text or non-text. Then, the text region is finally decided as text region or non-text region. The proposed method is able to verify text regions which can hardly be distin guished.
Facial Feature Verification System based on SVM Classifier
Park Kang Ryoung ; Kim Jaihie ; Lee Soo-youn ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 675~682
DOI : 10.3745/KIPSTB.2004.11B.6.675
With the five-day workweek system in bank and the increased usage of ATM(Automatic Toller Machine), it is required that the financial crime using stolen credit card should be prevented. Though a CCTV camera is usually installed in near ATM, an intelligent criminal can cheat it disguising himself with sunglass or mask. In this paper, we propose facial feature verification system which can detect whether the user`s face can be Identified or not, using image processing algorithm and SVM(Support Vector Machine). Experimental results show that FAR(Error Rate for accepting a disguised man as a non-disguised one) is 1% and FRR(Error Rate for rejecting a normal/non-disguised man as a disguised one) is 2% for training data. In addition, it shows the FAR of 2.5% and the FRR of 1.43% for test data.
Digital Hanbok Modeling for Virtual Characters : A Knowledge-driven Approach
Lee Bo-Ran ; Oh Sue-Jung ; Nam Yang-Hee ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 683~690
DOI : 10.3745/KIPSTB.2004.11B.6.683
Garment modeling and simulation is now one of the important elements in broad range of digital contents. Though there have been recent products on garment simulation, general users do not know well enough how to design a virtual costume that meets some requirements about its specific clothing pattern. In particular, Hanbok - the Korean traditional costume - has many different characteristics against western ones in the aspect of its pattern design and of draping. This paper presents a knowledge-driven approach for virtual Hanbok modeling without knowing how to make real Hanbok. First, parameterized knowledge for several fabric types art solicited using visual similarity assessment from simulated and real cloth. Secondly, based on the analysis of designer`s knowledge, we defined multi-level adjustment processes of Hanbok measurements with regard to body shape features for different virtual actors. An experimental system is developed as the form of a Maya plug-in and the result shows the applicability of the proposed method.
A Cooperative Proxy Caching for Continuous Media Services in Mobile Environments
Lee Seung-Won ; Lee Hwa-Sei ; Park Seong-Ho ; Chung Ki-Dong ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 691~700
DOI : 10.3745/KIPSTB.2004.11B.6.691
This paper proposes a user`s mobility based cooperative proxy caching policy for effective resource management of continuous media objects in mobile environments. This policy is different from the existing proxy caching policies in terms of how to exploit users` mobility. In other words, existing caching policies work based on the information about objects by referring to user`s requests within a specified domain whereas the proposed caching policy runs by utilizing a number of user`s requests across several domains. So, the proposed policy is applicable to random requests in mobile environments Moreover, we also propose a replacement policy based on weights and playback time. To check the efficiency of the proposed caching policy, the proposed replacement policy is run with different size of caching unit object or segment. The result of performance analyze tells what a ratio of user`s mobility is are major factors for the efficient operation of the cooperative caching.
A Multimedia Database System using Method of Automatic Annotation Update and Multi-Partition Color Histogram
Ahn Jae-Myung ; Oh Hae-Seok ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 701~708
DOI : 10.3745/KIPSTB.2004.11B.6.701
Existing contents-based video retrieval systems search by using a single method such as annotation-based or feature-based retrieval. Hence, it not only shows low search efficiency, but also requires many efforts to provide system administrator or annotator with a perfect automatic processing. Tn this paper, we propose an agent-based, and automatic and unified semantics-based video retrieval system, which support various semantics-retrieval of the massive video data by integrating the feature-based retrieval and the annotation-based retrieval. The indexing agent embodies the semantics about annotation of extracted key frames by analyzing a fundamental query of a user and by selecting a key-frame image that is ed by a query. Also, a key frame selected by user takes a query image of the feature-based retrieval and the indexing agent searches and displays the most similar key-frame images after comparing query images with key frames in the database by using the color-multiple-partition histogram techniques. Furthermore, it is shown that the performance of the proposed system can be significantly improved.
Multimedia Statistic Post-office Box System using Fuzzy Filtering Structures
Lee Chong Deuk ; Kim Dae Kyung ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 709~716
DOI : 10.3745/KIPSTB.2004.11B.6.709
According to the current increase of the usefulness of information by Internet Communication network, several methods are proposed in which a specific domain information nay be efficiently constructed and serviced. This paper proposes Relationship Grouping of Fuzzy Filtering Objects for Multimedia Statistic Post-office Box Construction. The proposed method exploits RelCRO(
, Gi), RelSRO(
, Gi) and FAS in order to group using (equation omitted)-cut. To know how well the proposed method is able to work, this paper have test against the methods with 1600 items of multimedia type information, and our system are compared with Random-Key, OGM and the proposed method. The results shows that the proposed method provides the better performance than the other methods.
Extracting Wisconsin Breast Cancer Prediction Fuzzy Rules Using Neural Network with Weighted Fuzzy Membership Functions
Lim Joon Shik ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 717~722
DOI : 10.3745/KIPSTB.2004.11B.6.717
This paper presents fuzzy rules to predict diagnosis of Wisconsin breast cancer using neural network with weighted fuzzy membership functions (NNWFM). NNWFM is capable of self-adapting weighted membership functions to enhance accuracy in prediction from the given clinical training data. n set of small, medium, and large weighted triangular membership functions in a hyperbox are used for representing n set of featured input. The membership functions are randomly distributed and weighted initially, and then their positions and weights are adjusted during learning. After learning, prediction rules are extracted directly from the enhanced bounded sums of n set of weighted fuzzy membership functions. Two number of prediction rules extracted from NNWFM outperforms to the current published results in number of rules and accuracy with 99.41%.
Web Page Classification System based upon Ontology
Choi Jaehyuk ; Seo Haesung ; Noh Sanguk ; Choi Kyunghee ; Jung Gihyun ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 723~734
DOI : 10.3745/KIPSTB.2004.11B.6.723
In this paper, we present an automated Web page classification system based upon ontology. As a first step, to identify the representative terms given a set of classes, we compute the product of term frequency and document frequency. Secondly, the information gain of each term prioritizes it based on the possibility of classification. We compile a pair of the terms selected and a web page classification into rules using machine learning algorithms. The compiled rules classify any Web page into categories defined on a domain ontology. In the experiments, 78 terms out of 240 terms were identified as representative features given a set of Web pages. The resulting accuracy of the classification was, on the average, 83.52%.
Implementation of Neural Networks using GPU
Oh Kyoung-su ; Jung Keechul ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 735~742
DOI : 10.3745/KIPSTB.2004.11B.6.735
We present a new use of common graphics hardware to perform a faster artificial neural network. And we examine the use of GPU enhances the time performance of the image processing system using neural network, In the case of parallel computation of multiple input sets, the vector-matrix products become matrix-matrix multiplications. As a result, we can fully utilize the parallelism of GPU. Sigmoid operation and bias term addition are also implemented using pixel shader on GPU. Our preliminary result shows a performance enhancement of about thirty times faster using ATI RADEON 9800 XT board.
Korean Parsing Model using Various Features of a Syntactic Object
Park So-Young ; Kim Soo-Hong ; Rim Hae-Chang ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 743~748
DOI : 10.3745/KIPSTB.2004.11B.6.743
In this paper, we propose a probabilistic Korean parsing model using a syntactic feature, a functional feature, a content feature, and a site feature of a syntactic object for effective syntactic disambiguation. It restricts grammar rules to binary-oriented form to deal with Korean properties such as variable word order and constituent ellipsis. In experiments, we analyze the parsing performance of each feature combination. Experimental results show that the combination of different features is preferred to the combination of similar features. Besides, it is remarkable that the function feature is more useful than the combination of the content feature and the size feature.
Target Word Selection Disambiguation using Untagged Text Data in English-Korean Machine Translation
Kim Yu-Seop ; Chang Jeong-Ho ;
The KIPS Transactions:PartB, volume 11B, issue 6, 2004, Pages 749~758
DOI : 10.3745/KIPSTB.2004.11B.6.749
In this paper, we propose a new method utilizing only raw corpus without additional human effort for disambiguation of target word selection in English-Korean machine translation. We use two data-driven techniques; one is the Latent Semantic Analysis(LSA) and the other the Probabilistic Latent Semantic Analysis(PLSA). These two techniques can represent complex semantic structures in given contexts like text passages. We construct linguistic semantic knowledge by using the two techniques and use the knowledge for target word selection in English-Korean machine translation. For target word selection, we utilize a grammatical relationship stored in a dictionary. We use k- nearest neighbor learning algorithm for the resolution of data sparseness Problem in target word selection and estimate the distance between instances based on these models. In experiments, we use TREC data of AP news for construction of latent semantic space and Wail Street Journal corpus for evaluation of target word selection. Through the Latent Semantic Analysis methods, the accuracy of target word selection has improved over 10% and PLSA has showed better accuracy than LSA method. finally we have showed the relatedness between the accuracy and two important factors ; one is dimensionality of latent space and k value of k-NT learning by using correlation calculation.