• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.210-212
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• 1999

This paper proposes a novel wavelet transform based technique for prediction of System Marginal Price(SMP). In this paper, Daubechies D1(haar), D2, D4 wavelet transforms are adopted to predict SMP and the numerical results reveal that certain wavelet components can effectively be used to identify the SMP characteristics with relation to the system demand in electric power systems. The wavelet coefficients associated with certain frequency and time localisation are adjusted using the conventional multiple regression method and then reconstructed in order to predict the SMP on the next scheduling day through a five-scale synthesis technique. The outcome of the study clearly indicates that the proposed wavelet transform approach can be used as an attractive and effective means for the SMP forecasting.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1092-1099
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• 2017

This paper proposes a novel way of vehicle detection and classification based on image features. There are two main processes in the proposed system, which are database construction and vehicle classification processes. In the database construction, there is a tight censorship for choosing appropriate images of the training set under the rigorous standard. These images are trained using Haar features for vehicle detection and histogram of oriented gradients extraction for vehicle classification based on the support vector machine. Additionally, in the vehicle detection and classification processes, the region of interest is reset using a number plate to reduce complexity. In the experimental results, the proposed system had the accuracy of 0.9776 and the $F_1$ score of 0.9327 for vehicle classification.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.229-235
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• 2011

To make a robust object tracking and identifying system for an intelligent robot and/or home system, heterogeneous sensor fusion between visible ray system and infrared ray system is proposed. The proposed system separates the object by combining the ROI (Region of Interest) estimated from two different images based on a heterogeneous sensor that consolidates the ordinary CCD camera and the IR (Infrared) camera. Human's body and face are detected in both images by using different algorithms, such as histogram, optical-flow, skin-color model and Haar model. Also the pose of human body is estimated from the result of body detection in IR image by using PCA algorithm along with AdaBoost algorithm. Then, the results from each detection algorithm are fused to extract the best detection result. To verify the heterogeneous sensor fusion system, few experiments were done in various environments. From the experimental results, the system seems to have good tracking and identification performance regardless of the environmental changes. The application area of the proposed system is not limited to robot or home system but the surveillance system and military system.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.297-302
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• 2012

In this paper, we present a object detection and tracking method based on image context analysis. It is robust from the image variations such as complicated background, dynamic movement of the object. Image context analysis is carried out using the hybrid network of k-means and RBF. The proposed object detection employs context-driven adaptive Bayesian framework to relive the effect due to uneven object images. The proposed method used feature vector generator using 2D Haar wavelet transform and the Bayesian discriminant method in order to enhance the speed of learning. The system took less time to learn, and learning in a wide variety of data showed consistent results. After we developed the proposed method was applied to real-world environment. As a result, in the case of the object to detect pass outside expected area or other changes in the uncertain reaction showed that stable. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5113-5119
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• 2010

Anthropometry has been broadly explored in various fields including automobile industry, home electronic appliances, medical appliances and sports goods with aiming at reaching satisfaction to consumer's need and efficiency. However, current technologies to measure a human body still have barriers in which the methods mostly seem to be contingent on expensive devices such as scanner and digital measuring instruments and to be directly touchable to the body when obtaining body size.. Therefore, in this paper, we present a general method to automatically extract size of body from a real body image acquired from a camera and to utilize it into recommend systems including clothing and bicycle fitting. At first, Haar-like features and AdaBoost algorithm are employed to detect body position. Then features of body can be recognized using AAM. Finally clothing and bicycle recommending modules have been implemented and experimented to validate the proposed method.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.7-15
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• 2014

This paper proposed a recognition algorithm of human facial expressions using the PCA and the template matching. Firstly, face image is acquired using the Haar-like feature mask from an input image. The face image is divided into two images. One is the upper image including eye and eyebrow. The other is the lower image including mouth and jaw. The extraction of facial components, such as eye and mouth, begins getting eye image and mouth image. Then an eigenface is produced by the PCA training process with learning images. An eigeneye and an eigenmouth are produced from the eigenface. The eye image is obtained by the template matching the upper image with the eigeneye, and the mouth image is obtained by the template matching the lower image with the eigenmouth. The face recognition uses geometrical properties of the eye and mouth. The simulation results show that the proposed method has superior extraction ratio rather than previous results; the extraction ratio of mouth image is particularly reached to 99%. The face recognition system using the proposed method shows that recognition ratio is greater than 80% about three facial expressions, which are fright, being angered, happiness.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.2
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• pp.235-240
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• 2015

Active Safety system is requested on the market of the medium and heavy duty commercial vehicle over 4.5ton beside the market of passenger car with advancement of the digital equipment proportionally. Unlike the passenger car, the mounting position of camera in case of the medium and heavy duty commercial vehicle is relatively high, it is disadvantaged conditions for lane recognition in contradiction to passenger car. In this work, we show the method of lane recognition through the Sobel edge, based on the spatial domain processing, Hough transform and color conversion correction. Also we suggest the low error method of front vehicles recognition in order to reduce the detection error through Haar-like, Adaboost, SVM and Template matching, etc., which are the object recognition methods by frontal camera vision. It is verified that the reliability over 98% on lane recognition is obtained through the vehicle test.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1435-1444
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• 2006

We present an effective and real-time face detection method based on Principal Component Analysis(PCA) and Support Vector Machines(SVMs). We extract simple Haar-like features from training images that consist of face and non-face images, reinterpret the features with PCA, and select useful ones from the large number of extracted features. With the selected features, we construct a face detector using an SVM appropriate for binary classification. The face detector is not affected by the size of a training data set in a significant way, so that it showed 90.1 % detection rates with a small quantity of training data. it can process 8 frames per second for $320{\times}240$ pixel images. This is an acceptable processing time for a real-time system.

• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.5-10
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• 2004

Body movement is one of the important factors in sleep analysis. In this study, a thermopile detector with four channels was implemented as a non-contacting detector of body movement in sleep. Using a thermopile mathematical model and several frames of thermal images, the possibility of detecting body movement was evaluated. Instant body movement signals were evaluated for the upper, lower, and entire body using the Haar wavelet. This decomposition shows the points in time when the upper-body or lower-body movement occurred and the level of body movement. Additionally, partial body movement was decomposed in head-only, whole body, and leg-only movement using the ANFIS algorithm. Finally, three subject's data were evaluated for 60 minutes, and the detection rates of instant and partial body movement, on average, were 96.3％ and 89.2％, respectively.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.7 s.361
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• pp.47-52
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• 2007

This paper analyzes the output signal-to-interference-plus-noise ratio (SINR) for a multiple-input-multiple-output (MIMO) multicarrier code division multiple access (MC-CDMA) system with minium mean square error receivers in multi-cell environments. A previous work in single cell environments is extended into analysis in multi-cell environments. The use of Haar unitary code matrix for asymptotic analysis causes other cell interferences expressed with a diagonal matrix haying different diagonal values. This paper shows that other cell interferences converge to an identity matrix whose gain is expressed by only other cell interference power in mean square sense and finds asymptotic deterministic SINRs for a given other cell interference. Under the assumption that the sum of lognormal fading components is distributed by other lognormal function, we show the comparison between theoretical performances and simulations from the view point of bit error rate and present average throughput performance according to the cell radius.