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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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The KIPS Transactions:PartB
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Journal DOI :
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
Selecting the target year
A Study on Air Interface System (AIS) Using Infrared Ray (IR) Camera
Kim, Hyo-Sung ; Jung, Hyun-Ki ; Kim, Byung-Gyu ;
The KIPS Transactions:PartB, volume 18B, issue 3, 2011, Pages 109~116
DOI : 10.3745/KIPSTB.2011.18B.3.109
In this paper, we introduce non-touch style interface system technology without any touch style controlling mechanism, which is called as "Air-interface". To develop this system, we used the full reflection principle of infrared (IR) light and then user`s hand is separated from the background with the obtained image at every frame. The segmented hand region at every frame is used as input data for an hand-motion recognition module, and the hand-motion recognition module performs a suitable control event that has been mapped into the specified hand-motion through verifying the hand-motion. In this paper, we introduce some developed and suggested methods for image processing and hand-motion recognition. The developed air-touch technology will be very useful for advertizement panel, entertainment presentation system, kiosk system and so many applications.
Robust Vision Based Algorithm for Accident Detection of Crossroad
Jeong, Sung-Hwan ; Lee, Joon-Whoan ;
The KIPS Transactions:PartB, volume 18B, issue 3, 2011, Pages 117~130
DOI : 10.3745/KIPSTB.2011.18B.3.117
The purpose of this study is to produce a better way to detect crossroad accidents, which involves an efficient method to produce background images in consideration of object movement and preserve/demonstrate the candidate accident region. One of the prior studies proposed an employment of traffic signal interval within crossroad to detect accidents on crossroad, but it may cause a failure to detect unwanted accidents if any object is covered on an accident site. This study adopted inverse perspective mapping to control the scale of object, and proposed different ways such as producing robust background images enough to resist surrounding noise, generating candidate accident regions through information on object movement, and by using edge information to preserve and delete the candidate accident region. In order to measure the performance of proposed algorithm, a variety of traffic images were saved and used for experiment (e.g. recorded images on rush hours via DVR installed on crossroad, different accident images recorded in day and night rainy days, and recorded images including surrounding noise of lighting and shades). As a result, it was found that there were all 20 experiment cases of accident detected and actual effective rate of accident detection amounted to 76.9% on average. In addition, the image processing rate ranged from 10~14 frame/sec depending on the area of detection region. Thus, it is concluded that there will be no problem in real-time image processing.
Performance Comparison Between New Level Set Method and Previous Methods for Volume Images Segmentation
Lee, Myung-Eun ; Cho, Wan-Hyun ; Kim, Sun-Worl ; Chen, Yan-Juan ; Kim, Soo-Hyung ;
The KIPS Transactions:PartB, volume 18B, issue 3, 2011, Pages 131~138
DOI : 10.3745/KIPSTB.2011.18B.3.131
In this paper, we compare our proposed method with previous methods for the volumetric image segmentation using level set. In order to obtain an exact segmentation, the region and boundary information of image object are used in our proposed speed function. The boundary information is defined by the gradient vector flow obtained from the gradient images and the region information is defined by Gaussian distribution information of pixel intensity in a region-of-interest for image segmentation. Also the regular term is used to remove the noise around surface. We show various experimental results of real medical volume images to verify the superiority of proposed method.
A Correction of Color Temperature and Consistency for 3D Stereoscopic Images
Kim, Jeong-Yeop ; Kim, Sang-Hyun ;
The KIPS Transactions:PartB, volume 18B, issue 3, 2011, Pages 139~146
DOI : 10.3745/KIPSTB.2011.18B.3.139
The color correction is the important process of influencing on the picture quality of the 3D stereoscopic images. Existing colorcorrecting methods handle the processing intensifying a correspondence among a left and right image using a histogram based on any one side. In case of color correction based on a histogram, it is difficult to correct tone of image, because the color temperature is not converted enough. And in this paper, the color temperature correction and color consistency correction is proposed without using histogram. The proposed color correction method by color temperature gives 3 in CIE-
for each pixel on the images captured with same illuminants and the conventional gives similar results. For color consistency, the proposed gives 9 in CIE-
on the images captured with different illuminants while the conventional gives 18. The proposed method shows better results than the conventional in color consistency processing.
Highly Reliable Fault Detection and Classification Algorithm for Induction Motors
Hwang, Chul-Hee ; Kang, Myeong-Su ; Jung, Yong-Bum ; Kim, Jong-Myon ;
The KIPS Transactions:PartB, volume 18B, issue 3, 2011, Pages 147~156
DOI : 10.3745/KIPSTB.2011.18B.3.147
This paper proposes a 3-stage (preprocessing, feature extraction, and classification) fault detection and classification algorithm for induction motors. In the first stage, a low-pass filter is used to remove noise components in the fault signal. In the second stage, a discrete cosine transform (DCT) and a statistical method are used to extract features of the fault signal. Finally, a back propagation neural network (BPNN) method is applied to classify the fault signal. To evaluate the performance of the proposed algorithm, we used one second long normal/abnormal vibration signals of an induction motor sampled at 8kHz. Experimental results showed that the proposed algorithm achieves about 100% accuracy in fault classification, and it provides 50% improved accuracy when compared to the existing fault detection algorithm using a cross-covariance method. In a real-world data acquisition environment, unnecessary noise components are usually included to the real signal. Thus, we conducted an additional simulation to evaluate how well the proposed algorithm classifies the fault signals in a circumstance where a white Gaussian noise is inserted into the fault signals. The simulation results showed that the proposed algorithm achieves over 98% accuracy in fault classification. Moreover, we developed a testbed system including a TI`s DSP (digital signal processor) to implement and verify the functionality of the proposed algorithm.
Fast and Scalable Path Re-routing Algorithm Using A Genetic Algorithm
Lee, Jung-Kyu ; Kim, Seon-Ho ; Yang, Ji-Hoon ;
The KIPS Transactions:PartB, volume 18B, issue 3, 2011, Pages 157~164
DOI : 10.3745/KIPSTB.2011.18B.3.157
This paper presents a fast and scalable re-routing algorithm that adapts to dynamically changing networks. The proposed algorithm integrates Dijkstra`s shortest path algorithm with the genetic algorithm. Dijkstra`s algorithm is used to define the predecessor array that facilitates the initialization process of the genetic algorithm. After that, the genetic algorithm re-searches the optimal path through appropriate genetic operators under dynamic traffic situations. Experimental results demonstrate that the proposed algorithm produces routes with less traveling time and computational overhead than pure genetic algorithm-based approaches as well as the standard Dijkstra`s algorithm for large-scale networks.
Solving the Gale-Shapley Problem by Ant-Q learning
Kim, Hyun ; Chung, Tae-Choong ;
The KIPS Transactions:PartB, volume 18B, issue 3, 2011, Pages 165~172
DOI : 10.3745/KIPSTB.2011.18B.3.165
In this paper, we propose Ant-Q learning Algorithm, which uses the habits of biological ants, to find a new way to solve Stable Marriage Problem(SMP) presented by Gale-Shapley. The issue of SMP is to find optimum matching for a stable marriage based on their preference lists (PL). The problem of Gale-Shapley algorithm is to get a stable matching for only male (or female). We propose other way to satisfy various requirements for SMP. ACS(Ant colony system) is an swarm intelligence method to find optimal solution by using phermone of ants. We try to improve ACS technique by adding Q learning concept. This Ant-Q method can solve SMP problem for various requirements. The experiment results shows the proposed method is good for the problem.