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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 18B, Issue 6 - Dec 2011
Volume 18B, Issue 5 - Oct 2011
Volume 18B, Issue 4 - Aug 2011
Volume 18B, Issue 3 - Jun 2011
Volume 18B, Issue 2 - Apr 2011
Volume 18B, Issue 1 - Feb 2011
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Detection of Gaze Direction for the Hearing-impaired in the Intelligent Space
Oh, Young-Joon ; Hong, Kwang-Jin ; Kim, Jong-In ; Jung, Kee-Chul ;
The KIPS Transactions:PartB, volume 18B, issue 6, 2011, Pages 333~340
DOI : 10.3745/KIPSTB.2011.18B.6.333
The Human-Computer Interaction(HCI) is a study of the method for interaction between human and computers that merges the ergonomics and the information technology. The intelligent space, which is a part of the HCI, is an important area to provide effective user interface for the disabled, who are alienated from the information-oriented society. In the intelligent space for the disabled, the method supporting information depends on types of disability. In this paper, we only support the hearing-impaired. It is material to the gaze direction detection method because it is very efficient information provide method to present information on gazing direction point, except for the information provide location perception method through directly contact with the hearing-impaired. We proposed the gaze direction detection method must be necessary in order to provide the residence life application to the hearing-impaired like this. The proposed method detects the region of the user from multi-view camera images, generates candidates for directions of gaze for horizontal and vertical from each camera, and calculates the gaze direction of the user through the comparison with the size of each candidate. In experimental results, the proposed method showed high detection rate with gaze direction and foot sensing rate with user`s position, and showed the performance possibility of the scenario for the disabled.
Research on the modified algorithm for improving accuracy of Random Forest classifier which identifies automatically arrhythmia
Lee, Hyun-Ju ; Shin, Dong-Kyoo ; Park, Hee-Won ; Kim, Soo-Han ; Shin, Dong-Il ;
The KIPS Transactions:PartB, volume 18B, issue 6, 2011, Pages 341~348
DOI : 10.3745/KIPSTB.2011.18B.6.341
ECG(Electrocardiogram), a field of Bio-signal, is generally experimented with classification algorithms most of which are SVM(Support Vector Machine), MLP(Multilayer Perceptron). But this study modified the Random Forest Algorithm along the basis of signal characteristics and comparatively analyzed the accuracies of modified algorithm with those of SVM and MLP to prove the ability of modified algorithm. The R-R interval extracted from ECG is used in this study and the results of established researches which experimented co-equal data are also comparatively analyzed. As a result, modified RF Classifier showed better consequences than SVM classifier, MLP classifier and other researches` results in accuracy category. The Band-pass filter is used to extract R-R interval in pre-processing stage. However, the Wavelet transform, median filter, and finite impulse response filter in addition to Band-pass filter are often used in experiment of ECG. After this study, selection of the filters efficiently deleting the baseline wandering in pre-processing stage and study of the methods correctly extracting the R-R interval are needed.
Fast Dynamic ROI Coding using the Mask Patterns in JPEG2000
Kang, Juong-Hyon ; Seo, Yeong-Geon ;
The KIPS Transactions:PartB, volume 18B, issue 6, 2011, Pages 349~354
DOI : 10.3745/KIPSTB.2011.18B.6.349
In ROI processing of JPEG2000, a region of large image indicated by the user must be processed preferentially, because it takes a considerable amount of time to display the full image. When the user indicates a region of the outlined image, then the browser masks the region and sends the mask information to the server that transmitted the outlined image. The server that receives the mask information preferentially sends the corresponding code blocks. Here, a quick generation of mask information is important. In this paper, we use 48 predefined mask patterns, which are defined according to the distribution shape of ROI and background to reduce the computing time. As a result, compared to other methods that precisely handles the ROI and background, the processing time of the method is remarkably reduced, but the quality is short of the existing methods just a little bit.
Block-based Image Authentication Algorithm using Differential Histogram-based Reversible Watermarking
Yeo, Dong-Gyu ; Lee, Hae-Yeoun ;
The KIPS Transactions:PartB, volume 18B, issue 6, 2011, Pages 355~364
DOI : 10.3745/KIPSTB.2011.18B.6.355
In most applications requiring high-confidential images, reversible watermarking is an effective way to ensure the integrity of images. Many watermarking researches which have been adapted to authenticate contents cannot recover the original image after authentication. However, reversible watermarking inserts the watermark signal into digital contents in such a way that the original contents can be restored without any quality loss while preserving visual quality. To detect malicious tampering, this paper presents a new block-based image authentication algorithm using differential histogram-based reversible watermarking. To generate an authentication code, the DCT-based authentication feature from each image block is extracted and combined with user-specific code. Then, the authentication code is embedded into image itself with reversible watermarking. The image can be authenticated by comparing the extracted code and the newly generated code and restored into the original image. Through experiments using multiple images, we prove that the presented algorithm has achieved over 97% authentication rate with high visual quality and complete reversibility.
Using the fusion of spatial and temporal features for malicious video classification
Jeon, Jae-Hyun ; Kim, Se-Min ; Han, Seung-Wan ; Ro, Yong-Man ;
The KIPS Transactions:PartB, volume 18B, issue 6, 2011, Pages 365~374
DOI : 10.3745/KIPSTB.2011.18B.6.365
Recently, malicious video classification and filtering techniques are of practical interest as ones can easily access to malicious multimedia contents through the Internet, IPTV, online social network, and etc. Considerable research efforts have been made to developing malicious video classification and filtering systems. However, the malicious video classification and filtering is not still being from mature in terms of reliable classification/filtering performance. In particular, the most of conventional approaches have been limited to using only the spatial features (such as a ratio of skin regions and bag of visual words) for the purpose of malicious image classification. Hence, previous approaches have been restricted to achieving acceptable classification and filtering performance. In order to overcome the aforementioned limitation, we propose new malicious video classification framework that takes advantage of using both the spatial and temporal features that are readily extracted from a sequence of video frames. In particular, we develop the effective temporal features based on the motion periodicity feature and temporal correlation. In addition, to exploit the best data fusion approach aiming to combine the spatial and temporal features, the representative data fusion approaches are applied to the proposed framework. To demonstrate the effectiveness of our method, we collect 200 sexual intercourse videos and 200 non-sexual intercourse videos. Experimental results show that the proposed method increases 3.75% (from 92.25% to 96%) for classification of sexual intercourse video in terms of accuracy. Further, based on our experimental results, feature-level fusion approach (for fusing spatial and temporal features) is found to achieve the best classification accuracy.
Recognition of Facial Expressions of Animation Characters Using Dominant Colors and Feature Points
Jang, Seok-Woo ; Kim, Gye-Young ; Na, Hyun-Suk ;
The KIPS Transactions:PartB, volume 18B, issue 6, 2011, Pages 375~384
DOI : 10.3745/KIPSTB.2011.18B.6.375
This paper suggests a method to recognize facial expressions of animation characters by means of dominant colors and feature points. The proposed method defines a simplified mesh model adequate for the animation character and detects its face and facial components by using dominant colors. It also extracts edge-based feature points for each facial component. It then classifies the feature points into corresponding AUs(action units) through neural network, and finally recognizes character facial expressions with the suggested AU specification. Experimental results show that the suggested method can recognize facial expressions of animation characters reliably.
Lossless Deformation of Brain Images for Concealing Identification
Lee, Hyo-Jong ; Yu, Du Ruo ;
The KIPS Transactions:PartB, volume 18B, issue 6, 2011, Pages 385~388
DOI : 10.3745/KIPSTB.2011.18B.6.385
Patients` privacy protection is a heated issue in medical business, as medical information in digital format transmit everywhere through networks without any limitation. A current protection method for brain images is to deface from the brain image for patient`s privacy. However, the defacing process often removes important brain voxels so that the defaced brain image is damaged for medical analysis. An ad-hoc method is proposed to conceal patient`s identification by adding cylindrical mask, while the brain keep all important brain voxels. The proposed lossless deformation of brain image is verified not to loose any important voxels. Futhermore, the masked brain image is proved not to be recognized by others.
A Study on Monitoring of Liver Function Based on Voice Signal Analysis for u-Health System
Kim, Bong-Hyun ; Cho, Dong-Uk ;
The KIPS Transactions:PartB, volume 18B, issue 6, 2011, Pages 389~396
DOI : 10.3745/KIPSTB.2011.18B.6.389
There is getting worse to various liver diseases due to change in eating habits, stress, alcohol etc in modern society. Therefore, we proposed methodology to diagnose early for liver disease to study the influence on voice in liver diseases. To this end, we carried out experiment to apply parameter of voice analysis to collect each voice inpatients and patients by treatment of liver diseases patients. Particularly, we carried out experiment to apply element value of pronunciation and the third formant frequency bandwidths about velar sounds associated liver in oriental medicine, then to produce objective index resonance cavity and influence vocalization in liver diseases. In addition, we carried out to study about design of system to monitoring a liver function in u-Health environment based on result by experiment.
The Effect of Helium Gas Intake on the Characteristics Change of the Acoustic Organs for Voice Signal Analysis Parameter Application
Kim, Bong-Hyun ; Cho, Dong-Uk ;
The KIPS Transactions:PartB, volume 18B, issue 6, 2011, Pages 397~404
DOI : 10.3745/KIPSTB.2011.18B.6.397
In this paper, we were carried out experiments to apply parameter of voice analysis to measure changing characteristic articulator according to inhale the helium gas. The helium gas was used to overcome air embolism nitrogen gas to deal a fatal blow in body nitrogen gas by diver. However, the helium gas has been much trouble interpretation about abnormal voice of diver to cause squeaky voice of low articulation. Therefor, we was carried out experiments about pitch and spectrogram measurement, analysis based on to influence in acoustic organs before and after of inhaled helium gas.
Generalization of error decision rules in a grammar checker using Korean WordNet, KorLex
So, Gil-Ja ; Lee, Seung-Hee ; Kwon, Hyuk-Chul ;
The KIPS Transactions:PartB, volume 18B, issue 6, 2011, Pages 405~414
DOI : 10.3745/KIPSTB.2011.18B.6.405
Korean grammar checkers typically detect context-dependent errors by employing heuristic rules that are manually formulated by a language expert. These rules are appended each time a new error pattern is detected. However, such grammar checkers are not consistent. In order to resolve this shortcoming, we propose new method for generalizing error decision rules to detect the above errors. For this purpose, we use an existing thesaurus KorLex, which is the Korean version of Princeton WordNet. KorLex has hierarchical word senses for nouns, but does not contain any information about the relationships between cases in a sentence. Through the Tree Cut Model and the MDL(minimum description length) model based on information theory, we extract noun classes from KorLex and generalize error decision rules from these noun classes. In order to verify the accuracy of the new method in an experiment, we extracted nouns used as an object of the four predicates usually confused from a large corpus, and subsequently extracted noun classes from these nouns. We found that the number of error decision rules generalized from these noun classes has decreased to about 64.8%. In conclusion, the precision of our grammar checker exceeds that of conventional ones by 6.2%.