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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 16B, Issue 6 - Dec 2009
Volume 16B, Issue 5 - Oct 2009
Volume 16B, Issue 4 - Aug 2009
Volume 16B, Issue 3 - Jun 2009
Volume 16B, Issue 2 - Apr 2009
Volume 16B, Issue 1 - Feb 2009
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An Implementation of Gaze Direction Recognition System using Difference Image Entropy
Lee, Kue-Bum ; Chung, Dong-Keun ; Hong, Kwang-Seok ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 93~100
DOI : 10.3745/KIPSTB.2009.16-B.2.93
In this paper, we propose a Difference Image Entropy based gaze direction recognition system. The Difference Image Entropy is computed by histogram levels using the acquired difference image of current image and reference images or average images that have peak positions from
to prevent information omission. There are two methods about the Difference Image Entropy based gaze direction. 1) The first method is to compute the Difference Image Entropy between an input image and average images of 45 images in each location of gaze, and to recognize the directions of user`s gaze. 2) The second method is to compute the Difference Image Entropy between an input image and each 45 reference images, and to recognize the directions of user`s gaze. The reference image is created by average image of 45 images in each location of gaze after receiving images of 4 directions. In order to evaluate the performance of the proposed system, we conduct comparison experiment with PCA based gaze direction system. The directions of recognition left-top, right-top, left-bottom, right-bottom, and we make an experiment on that, as changing the part of recognition about 45 reference images or average image. The experimental result shows that the recognition rate of Difference Image Entropy is 97.00% and PCA is 95.50%, so the recognition rate of Difference Image Entropy based system is 1.50% higher than PCA based system.
Protection of Windows Media Video Providing Selective Encryption
Park, Ji-Hyun ; Ryou, Jae-Cheol ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 101~108
DOI : 10.3745/KIPSTB.2009.16-B.2.101
As content serviced for IP set-top boxes is streamed over IP network, the existing hacking tools for IP network can be used to capture the streamed content. Until recently, most of the content serviced on IP set-top boxes has been MPEG-2 TS. However, this content will be gradually moved to WMV, MPEG-4 or H.264 because of the relatively low compression efficiency and overhead of the TS packet. In this paper, we propose a DRM scheme other than WMRM for streamed WMV content. Our approach is to design a DRM scheme independent to the existing WMV streaming system. We also design this scheme in order to provide the feature for controlling the DRM processing time considering device performance. We verified it through the experiment.
Stereo Images-Based Real-time Object Tracking Using Active Feature Model
Park, Min-Gyu ; Jang, Jong-Whan ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 109~116
DOI : 10.3745/KIPSTB.2009.16-B.2.109
In this thesis, an object tracking method based on the active feature model and the optical flow in stereo images is proposed. We acquired the translation information of object of interest and the features of object by utilizing the geometric information and depth of stereo images. Tracking performance is improved for the occlude object with this information by predicting the movement information of features of the occlude object. Rigid and non-rigid objects are experimented. From the result of experiment, the OOI can be real-time tracked from complicate back ground. Besides, we got the improved result of object tracking in any occlusion state, no matter what it is rigid or non-rigid object.
A Development of Unicode-based Multi-lingual Namecard Recognizer
Jang, Dong-Hyeub ; Lee, Jae-Hong ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 117~122
DOI : 10.3745/KIPSTB.2009.16-B.2.117
We developed a multi-lingual namecard recognizer for building up a global client management systems. At first, we created the Unicode-based character image database for character recognition and learning of multi languages, and applied many color image processing techniques to get more correct data for namecard images which were acquired by various input devices. And by applying multi-layer perceptron neural network, individual character recognition applied for language types, and post-processing utilizing keyword databases made for individual languages, we increased a recognition rate for multi-lingual namecards.
Efficient Integer pel and Fractional pel Motion Estimation on H.264/AVC
Yoon, Hyo-Sun ; Kim, Hye-Suk ; Jung, Mi-Gyoung ; Kim, Mi-Young ; Cho, Young-Joo ; Kim, Gi-Hong ; Lee, Guee-Sang ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 123~130
DOI : 10.3745/KIPSTB.2009.16-B.2.123
Motion estimation (ME) plays an important role in digital video compression. But it limits the performance of image quality and encoding speed and is computational demanding part of the encoder. To reduce computational time and maintain the image quality, integer pel and fractional pel ME methods are proposed in this paper. The proposed method for integer pel ME uses a hierarchical search strategy. This strategy method consists of symmetrical cross-X pattern, multi square grid pattern, diamond patterns. These search patterns places search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum and to reduce the computational time. The proposed method for fractional pel uses full search pattern, center biased fractional pel search pattern and the proposed search pattern. According to block sizes, the proposed method for fractional pel decides the search pattern adaptively. Experiment results show that the speedup improvement of the proposed method over Unsymmetrical cross Multi Hexagon grid Search (UMHexagonS) and Full Search (FS) can be up to around
times faster. Compared to image quality of FS, the proposed method shows an average PSNR drop of 0.01 dB while showing an average PSNR gain of 0.02 dB in comparison to that of UMHexagonS.
Segmentation Method of Overlapped nuclei in FISH Image
Jeong, Mi-Ra ; Ko, Byoung-Chul ; Nam, Jae-Yeal ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 131~140
DOI : 10.3745/KIPSTB.2009.16-B.2.131
This paper presents a new algorithm to the segmentation of the FISH images. First, for segmentation of the cell nuclei from background, a threshold is estimated by using the gaussian mixture model and maximizing the likelihood function of gray value of cell images. After nuclei segmentation, overlapped nuclei and isolated nuclei need to be classified for exact nuclei analysis. For nuclei classification, this paper extracted the morphological features of the nuclei such as compactness, smoothness and moments from training data. Three probability density functions are generated from these features and they are applied to the proposed Bayesian networks as evidences. After nuclei classification, segmenting of overlapped nuclei into isolated nuclei is necessary. This paper first performs intensity gradient transform and watershed algorithm to segment overlapped nuclei. Then proposed stepwise merging strategy is applied to merge several fragments in major nucleus. The experimental results using FISH images show that our system can indeed improve segmentation performance compared to previous researches, since we performed nuclei classification before separating overlapped nuclei.
Automatic Music Transcription System Using SIDE
Hyoung, A-Young ; Lee, Joon-Whoan ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 141~150
DOI : 10.3745/KIPSTB.2009.16-B.2.141
This paper proposes a system that can automatically write singing voices to music notes. First, the system uses Stabilized Diffusion Equation(SIDE) to divide the song to a series of syllabic parts based on pitch detection. By the song segmentation, our method can recognize the sound length of each fragment through clustering based on genetic algorithm. Moreover, this study introduces a concept called `Relative Interval` so as to recognize interval based on pitch of singer. And it also adopted measure extraction algorithm using pause data to implement the higher precision of song transcription. By the experiments using 16 nursery songs, it is shown that the measure recognition rate is 91.5% and DMOS score reaches 3.82. These findings demonstrate effectiveness of system performance.
Implementation of Music Signals Discrimination System for FM Broadcasting
Kang, Hyun-Woo ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 151~156
DOI : 10.3745/KIPSTB.2009.16-B.2.151
This paper proposes a Gaussian mixture model(GMM)-based music discrimination system for FM broadcasting. The objective of the system is automatically archiving music signals from audio broadcasting programs that are normally mixed with human voices, music songs, commercial musics, and other sounds. To improve the system performance, make it more robust and to accurately cut the starting/ending-point of the recording, we also added a post-processing module. Experimental results on various input signals of FM radio programs under PC environments show excellent performance of the proposed system. The fixed-point simulation shows the same results under 3MIPS computational power.
The Correctness Comparison of MCIH Model and WMLF/GI Model for the Individual Haplotyping Reconstruction
Jeong, In-Seon ; Kang, Seung-Ho ; Lim, Hyeong-Seok ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 157~161
DOI : 10.3745/KIPSTB.2009.16-B.2.157
Minimum Letter Flips(MLF) and Weighted Minimum Letter Flips(WMLF) can perform the haplotype reconstruction more accurately from SNP fragments when they have many errors and gaps by introducing the related genotype information. And it is known that WMLF is more accurate in haplotype reconstruction than those based on the MLF. In the paper, we analyze two models under the conditions that the different rates of homozygous site in the genotype information and the different confidence levels according to the sequencing quality. We compare the performance of the two models using neural network and genetic algorithm. If the rate of homozygous site is high and sequencing quality is good, the results of experiments indicate that WMLF/GI has higher accuracy of haplotype reconstruction than that of the MCIH especially when the error rate and gap rate of SNP fragments are high.
Fuzzy Cluster Based Diagnosis System for Digital Mammogram
Rhee, Hyun-Sook ; Yoon, Seok-Min ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 165~172
DOI : 10.3745/KIPSTB.2009.16-B.2.165
According to the American Cancer Society, breast cancer is the second largest cause of cancer deaths and most frequently diagnosed cancer in women. The currently most popular method for early detection of breast cancer is the digital mammography. A mass or calcification lesion has been known as the most important clue for the diagnosis. In this paper, we propose a diagnosis approach based on fuzzy cluster knowledge base. We combine different two sources of feature data in duel OFUN-NET and produce the diagnosis result with possibility degree. We also present the experimental results on the dataset of mass and calcification lesions extracted from the public real world mammogram database DDSM. These results show higher classification accuracy than conventional methods and the feasibility as a decision supporting tool for diagnosis of digital mammogram.
Accuracy Improvement of an Automated Scoring System through Removing Duplicately Reported Errors
Lee, Hyun-Ah ; Kim, Jee-Eun ; Lee, Kong-Joo ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 173~180
DOI : 10.3745/KIPSTB.2009.16-B.2.173
The purpose of developing an automated scoring system for English composition is to score English writing tests and to give diagnostic feedback to the test-takers without human`s efforts. The system developed through our research detects grammatical errors of a single sentence on morphological, syntactic and semantic stages, respectively, and those errors are calculated into the final score. The error detecting stages are independent from one another, which causes duplicating the identical errors with different labels at different stages. These duplicated errors become a hindering factor to calculating an accurate score. This paper presents a solution to detecting the duplicated errors and improving an accuracy in calculating the final score by eliminating one of the errors.
A Two Phases Plagiarism Detection System for the Newspaper Articles by using a Web Search and a Document Similarity Estimation
Cho, Jung-Hyun ; Jung, Hyun-Ki ; Kim, Yu-Seop ;
The KIPS Transactions:PartB, volume 16B, issue 2, 2009, Pages 181~194
DOI : 10.3745/KIPSTB.2009.16-B.2.181
With the increased interest on the document copyright, many of researches related to the document plagiarism have been done up to now. The plagiarism problem of newspaper articles has attracted much interest because the plagiarism cases of the articles having much commercial values in market are currently happened very often. Many researches related to the document plagiarism have been so hard to be applied to the newspaper articles because they have strong real-time characteristics. So to detect the plagiarism of the articles, many human detectors have to read every single thousands of articles published by hundreds of newspaper companies manually. In this paper, we firstly sorted out the articles with high possibility of being copied by utilizing OpenAPI modules supported by web search companies such as Naver and Daum. Then, we measured the document similarity between selected articles and the original article and made the system decide whether the article was plagiarized or not. In experiment, we used YonHap News articles as the original articles and we also made the system select the suspicious articles from all searched articles by Naver and Daum news search services.