• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.95-104
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• 2012

Pattern recognition using ensemble classifiers is composed of strong classifier which consists of many weak classifiers. In this paper, we used feature extraction to organize strong classifier using static camera sequence. The strong classifier is made of weak classifiers which considers environmental factors. So the strong classifier overcomes environmental effect. Proposed method uses binary foreground image by frame difference method and the boosting is used to train crowdedness model and recognize crowdedness using features. Combination of weak classifiers makes strong ensemble classifier. The classifier could make use of potential features from the environment such as shadow and reflection. We tested the proposed system with road sequence and subway platform sequence which are included in "AVSS 2007" sequence. The result shows good accuracy and efficiency on complex environment.

• Convergence Security Journal
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• v.19 no.5
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• pp.75-84
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• 2019

Recently, the value of video as an important data of medical information technology is increasing due to the feature of rich clinical information. On the other hand, video is also required to be de-identified as a medical image, but the existing methods are mainly specialized in the stereotyped data and still images, which makes it difficult to apply the existing methods to the video data. In this paper, we propose an automated system to index candidate elements of personal identification information on a frame basis to solve this problem. The proposed system performs indexing process using text and person detection after preprocessing by scene segmentation and color knowledge based method. The generated index information is provided as metadata according to the purpose of use. In order to verify the effectiveness of the proposed system, the indexing speed was measured using prototype implementation and real surgical video. As a result, the work speed was more than twice as fast as the playing time of the input video, and it was confirmed that the decision making was possible through the case of the production of surgical education contents.

• Journal of the Korea Fashion and Costume Design Association
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• v.9 no.1
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• pp.1-11
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• 2007

This study suggests the new technique to express the texture that copes with the demands of the times by trying to apply the new Nuno-felt technique, to the silk, the representative material for emotion, in order to provide the basic data for the development of highly value added and competitive materials in the domestic and international markets as well as to meet the demand of consumers in the high emotion age pursuing the idiosyncrasy and qualify enhancement. Nuno-felt is the felting technique that places the wool of desired thickness on the thin fabric using wools and various kinds of fabric materials and rubs them. The samples are 3 kinds of silk including plain Chiffon with different touch, Pongee and Organza and Merino Wool, the best quality wool of wools. As a result, beyond the simple surface effect from the silk showing the superior drape feature with one color and soft wool, the Nuno-felt technique created the feminine as well as masculine, classic and modem image. Furthermore, the harmony of opacity and transparency produced the new dynamic and dimensional texture with the combination of different emotions through the visual emotion of different grey colors and rough, crude and soft touch. This study suggested the possibility that the Nuno-felt technique could create the new emotional materials for the modem sense by combining the materials with different features from the wools unlike the traditional simple felt technique.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.381-390
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• 2010

This paper describes a procedure of the map-based localization for mobile robots by using a sensor fusion technique in structured environments. A combination of various sensors with different characteristics and limited sensibility has advantages in view of complementariness and cooperation to obtain better information on the environment. In this paper, for robust self-localization of a mobile robot with a monocular camera and a laser structured light sensor, environment information acquired from two sensors is combined and fused by a Bayesian sensor fusion technique based on the probabilistic reliability function of each sensor predefined through experiments. For the self-localization using the monocular vision, the robot utilizes image features consisting of vertical edge lines from input camera images, and they are used as natural landmark points in self-localization process. However, in case of using the laser structured light sensor, it utilizes geometrical features composed of corners and planes as natural landmark shapes during this process, which are extracted from range data at a constant height from the navigation floor. Although only each feature group of them is sometimes useful to localize mobile robots, all features from the two sensors are simultaneously used and fused in term of information for reliable localization under various environment conditions. To verify the advantage of using multi-sensor fusion, a series of experiments are performed, and experimental results are discussed in detail.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.55-62
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• 1998

Matching two images is an essential step for many computer vision applications. A new approach to the scale and rotation invariant scene matching, using linear features, is presented. Scene or model images are described by a set of linear features approximating edge information, which can be obtained by the conventional edge detection, thinning, and piecewise linear approximation. A set of candidate parameters are hypothesized by mapping the angular difference and a new distance measure to the Hough space and by detecting maximally consistent points. These hypotheses are verified by a fast linear feature matching algorithm composed of a single-step relaxation and a Hough technique. The proposed method is shown to be much faster than the conventional one where the relaxation process is repeated until convergence, while providing matching performance robust to the random alteration of the linear features, without a priori information on the geometrical transformation parameters.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.5
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• pp.79-86
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• 2005

The Qis visualizational spreadsheet environment is shown to be extremely effective in supporting the organized visualization of multi-dimensional data sets. The Qis consists of the reconfigurative 2D arrangement of spreadsheet elements at run time and each spreadsheet element has a novel framestack. As the feature, it supports 3D data structure of each element on the Qis. It enables the visualization spreadsheet to effectively manage, rapidly organize, and compactly encapsulate multi-dimensional data sets for visualization. Using several experiments with scientific users, the Qis has been demonstrated to be a highly interactive visual browsing tool for the analysis of multidimensional data, displaying 2D and 3D graphics, and rendering in each frame of the spreadsheet.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.267-268
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• 2002

Microbeam is a new avenue of radiation research especially in radiation biology and radiation protection. Selective irradiation of an ionizing particle to a targeted cell organelle may disclose such mechanisms as signal transaction among cell organelles and cell-to-cell communication in the processes toward an endpoint observed. Bystander effect, existence of which is clearly evidenced by application of the particle microbeam to biological experiments, suggests potential underestimation in the conventional risk estimation at low particle fluence rates, such as environment of space radiations in ISS (International Space Station). To promote these studies we started the construction of our microbeam facility (named as SPICE) to our HVEE Tandem accelerator (3.4 MeV proton and 5.1 MeV $^4$He$\^$2+/). For our primary goal, "irradiation of single particle to cell organelle within a position resolution of 2 micrometer in a reasonable irradiation time", special features are considered. Usage of a triplet Q magnet for focussing the beam to submicron of size is an outstanding feature compared to facilities of other institutes. Followings are other features: precise position control of cell dish holder, design of the cell dish, data acquisition of microscopic image of a cell organelle (cell nucleus) and data processing, a reliable particle detection, soft and hard wares to integrate all these related data, to control and irradiate exactly determined number of particles to a targeted spot.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.98-103
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• 2001

The binaural auditory system of human has the capability of differentiating the direction and distance of sound sources. This feature is well characterised in terms of the inter-aural intensity difference (IID), the inter-aural time difference (ITD) and/or the spectral shape difference (SSD) arising from the acoustic transfer of a sound source to the outer ears. This paper proposes an effective way of extracting the three sound perception factors (IID, ITD, SSD) from the head-related transfer functions (HRTF's) that depends on the direction and distance of the acoustic source from the listener. It includes the estimation method of the equivalent ITD and 1/3-octave band-based IID factors and their usage to locate a sound source in space. Subjective and objective tests were carried out to examine the effectiveness of the proposed methodology and its applicability to real sound systems. Those experimental results are illustrated in this paper.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.5
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• pp.266-279
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• 2003

In this paper, we propose machine printed character recognition methods which utilize the character type information and divide the character clusters. The characters are subdivided into a total of seven types, of which six types are for Hangul according to the grapheme combination fashions and one type for English characters, numerals, and symbols. According to the character type, we separate input character image into several recognition units and recognize them by using the direction angle feature. The recognition for each character type is completed by combining recognition units which are recognized by neural networks respectively For combining a total of seven character recognizers, we implemented seven methods such as switching method, integrating method, and their several variants. As experimental results, we obtained 98.2% recognition rate of simple switching method, 90.54% of integrating one, and between 97.35% and 98.65% of five variants.

• Journal of the Korea Society of Computer and Information
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• v.17 no.5
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• pp.21-28
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• 2012

Recently, the necessity for good techniques of detecting network traffic attack has increased. In this paper, we suggest a new method of detecting abnormal patterns of network traffic data by visualizing their IP and port information into two dimensional images. The proposed approach first generates four 2D images from IP data of transmitters and receivers, and makes one 2D image from port data. Analyzing those images, it then extracts their major features such as linear patterns or high intensity values, and determines if traffic data contain DDoS or DoS Attacks. To comparatively evaluate the performance of the proposed algorithm, we show that our abnormal pattern detection method outperforms the existing algorithm in terms of accuracy and speed.