• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.57-66
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• 2011

In this paper, it is proposed for algorithm to detect human efficiently using a edge symmetry and gradient directional characteristics in realtime by the feature extraction in a single input image. Proposed algorithm is composed of three stages, preprocessing, region partition of human candidates, verification of candidate regions. Here, preprocessing stage is strong the image regardless of the intensity and brightness of surrounding environment, also detects a contour with characteristics of human as considering the shape features size and the condition of human for characteristic of human. And stage for region partition of human candidates has separated the region with edge symmetry for human and size in the detected contour, also divided 1st candidates region with applying the adaboost algorithm. Finally, the candidate region verification stage makes excellent the performance for the false detection by verifying the candidate region using feature vector of a gradient for divided local area and classifier. The results of the simulations, which is applying the proposed algorithm, the processing speed of the proposed algorithms is improved approximately 1.7 times, also, the FNR(False Negative Rate) is confirmed to be better 3% than the conventional algorithm which is a single structure algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.624-630
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• 2010

As electrocardiogram(ECG) signals are generally sampled with a frequency of over 200Hz, a method to compress diagnostic information without losing data is required to store and transmit them efficiently. In this paper, an ECG signal compression method, which uses feature points based on curvature, is proposed. The feature points of P, Q, R, S, T waves, which are critical components of the ECG signal, have large curvature values compared to other vertexes. Thus, these vertexes are extracted with the proposed method, which uses local extremum of curvatures. Furthermore, in order to minimize reconstruction errors of the ECG signal, extra vertexes are added according to the iterative vertex selection method. Through the experimental results on the ECG signals from MIT-BIH Arrhythmia database, it is concluded that the vertexes selected by the proposed method preserve all feature points of the ECG signals. In addition, they are more efficient than the AZTEC(Amplitude Zone Time Epoch Coding) method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.6
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• pp.1449-1457
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• 2007

A panorama image is constructed by merging several overlapped images to a big one. There are two kinds of methods, feature based and direct method, in the construction. Feature based one has a merit of processing speed faster than direct one. But, it is difficult to be implemented under slower processing environments such as mobile device. This paper proposed high speed construction method of a panorama image. The algorithm extremely improved matching speed by reducing the number of matching parameters using scene shot guider, and additionally adapted local matching technique to reduce matching error caused by the fewer matching parameters. In the experiments, it was shown that the proposed method required about 0.078 second in processing time, about 17 times shorter than the feature based one, for 24-bit color images of $320{\times}240$ size.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.53-60
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• 2009

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking; and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.603-607
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• 2004

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1437-1443
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• 2009

This paper is presented an simultaneous localization and mapping (SLAM) algorithm using ultrasonic for robot and electric compass, encoder, and gyro. Generally, localization based upon electric compass, encoder, and gyro can be measured just local position in workspace. However, actual robot must need an information of the absolute position in workspace to perform its mission, Absolute position in workspace could be calculated using SLAM algorithm. To implement SLAM in this paper, a map is built using ultrasonic sensor and hierarchical map building method. And then, we the map will be transformed into a feature map. The absolute position could be calculated using the feature map and map mapping method. As a test bed, we designed and construct an autonomous robot and showed the experimental performance of the proposed SLAM algorithm based on feature map. Experimental result, we verified that robot can found all absolute position on experiments using proposed SLAM algorithm.

• Environmental and Resource Economics Review
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• v.15 no.5
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• pp.939-959
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• 2006

This paper studies the introduction of flood quota system for efficient flood prevention. In the present system where local governments decide its flood prevention independently, the optimal flood prevention in a river basin can not be achieved. Thus, the flood quota system is necessary. In deciding the flood quota for each local government in a river basin, its social and economic characteristics as well as geographical feature of the area should be considered. In order to promote the cooperation among local governments in a river basin, the flood quota is necessary to be accompanied with the trading system of the quota.

• Convergence Security Journal
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• v.14 no.7
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• pp.9-15
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• 2014

In this paper, we proposed a new LDP code to solve a previous LDP code's problem and can include a face-color information. To include the face-color information, we developed various methods reducing the existing LDP code and analyzed the results. A new LDP code is represented by 6-bits different from the previous LDP code To adapt to a noise and environmental changes effectively and include 2-bits face-color information. The result shows better recognition rates of face and facial-expression than the existing methods effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1390-1403
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• 2016

Facial expression recognition (FER) plays a very significant role in computer vision, pattern recognition, and image processing applications such as human computer interaction as it provides sufficient information about emotions of people. For video-based facial expression recognition, depth cameras can be better candidates over RGB cameras as a person's face cannot be easily recognized from distance-based depth videos hence depth cameras also resolve some privacy issues that can arise using RGB faces. A good FER system is very much reliant on the extraction of robust features as well as recognition engine. In this work, an efficient novel approach is proposed to recognize some facial expressions from time-sequential depth videos. First of all, efficient Local Binary Pattern (LBP) features are obtained from the time-sequential depth faces that are further classified by Generalized Discriminant Analysis (GDA) to make the features more robust and finally, the LBP-GDA features are fed into Hidden Markov Models (HMMs) to train and recognize different facial expressions successfully. The depth information-based proposed facial expression recognition approach is compared to the conventional approaches such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Linear Discriminant Analysis (LDA) where the proposed one outperforms others by obtaining better recognition rates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5A
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• pp.709-716
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• 2000

We present an efficient algorithm using region-based average of variations of local correlation coefficients (LCC) for the extraction of texture regions. The key idea of this algorithm for the classification of texture and shade regions is to utilize the fact that the averages of the variations of LCCs according to different orientations texture regions are clearly larger than those in shade regions. In order to evaluate the performance of the proposed algorithm, we use nine test images (Lena, Bsail, Camera Man, Face, Woman, Elaine, Jet, Tree, and Tank) of 8-bit 256$\times$256 pixels. Experimental results show that the proposed feature extracts well the regions which appear visually as texture regions.