• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.45-55
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• 2013

In this study, we propose a tongue diagnosis system which detects the tongue from face image and divides the tongue area into six areas, and finally generates tongue fur ratio of each area. To detect the tongue area from face image, we use ASM as one of the active shape models. Detected tongue area is divided into six areas and the distribution of tongue coating of six areas is examined by SVM. For SVM, we use a 3-dimensional vector calculated by PCA from a 12-dimensional vector consisting of RGB, HSV, Lab, and Luv. As a result, we stably detected the tongue area using ASM. Furthermore, we recognized that PCA and SVM helped to raise the ratio of tongue coating detection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.155-161
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• 2024

In this paper, we propose a new model by adding landmark information as a feature vector to the existing CNN-based facial emotion classification model. Facial emotion classification research using CNN-based models is being studied in various ways, but the recognition rate is very low. In order to improve the CNN-based models, we propose algorithms that improves facial expression classification accuracy by combining the CNN model with a landmark-based fully connected network obtained by ASM. By including landmarks in the CNN model, the recognition rate was improved by several percent, and experiments confirmed that further improved results could be obtained by adding FACS-based action units to the landmarks.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.173-178
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• 2014

In this study, we introduce ASM-based face recognition classifier and its design methodology with the aid of 2-dimensional 2-directional hybird preprocessing algorithm. Since the image of face recognition is easily affected by external environments, ASM(active shape model) as image preprocessing algorithm is used to resolve such problem. In particular, ASM is used widely for the purpose of feature extraction for human face. After extracting face image area by using ASM, the dimensionality of the extracted face image data is reduced by using $(2D)^2$hybrid preprocessing algorithm based on LDA and PCA. Face image data through preprocessing algorithm is used as input data for the design of the proposed polynomials based radial basis function neural network. Unlike as the case in existing neural networks, the proposed pattern classifier has the characteristics of a robust neural network and it is also superior from the view point of predictive ability as well as ability to resolve the problem of multi-dimensionality. The essential design parameters (the number of row eigenvectors, column eigenvectors, and clusters, and fuzzification coefficient) of the classifier are optimized by means of ABC(artificial bee colony) algorithm. The performance of the proposed classifier is quantified through yale and AT&T dataset widely used in the face recognition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5357-5365
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• 2013

In this paper, we propose that a model based design for a electric tractor system by using ASM(Automotive Simulation Models). Before developing a realistic electric tractor, it is essential that defining the capacities of power sources and optimizing the parameters of electric tractor. In additionally, because the electric tractor must have not only driving function but also working function, two PMSM are used at electric tractor. ASM which is based on simulink and Carsim were used to design a electric system and powertrain of electric tractor. For verifying the electric tractor system, we compared the design parameters such as max power, state of charge, drive distance, velocity which were carried out by the simulation and experimental method. The predicted results by the development model were in good agreement with the simulation results. According to simulation of tractor, it is possible to arrange the advanced research of dynamical characteristic of tractor and present the guidelines for the electrical driving system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.8
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• pp.2069-2078
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• 1993

The buoyancy-driven turbulent thermal convection is predicted using an anisotropic hybrid turbulence model, which is incorporated with a low Reynolds k-.epsilon. turbulence model and an anisotropic buoyant part of algebraic stress model(ASM). The numerical predictions are compared with the Davidson's model,(1) the full ASM and the experimental results of Cheesewright et al.(2) All the models are shown to predict good agreements with the experiments for the averaged turbulence quantities. It is found that the effect of an anisotropic part on the Reynolds stress and the turbulent heat fluxes is substantial. In this study, the present hybrid model gives a fairly reasonable prediction in terms of the computational accuracy, convergence and stability. The contribution of an anisotropic buoyant part to turbulent heat fluxes are also scrutinized over the range of Rayleigh numbers $(4.79{\times}10^{10}{\le}Ra{\le}7.46{\times}10^{10}).$

• Journal of Korea Multimedia Society
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• v.6 no.6
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• pp.968-976
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• 2003

In this paper, we propose a novel method for lip recognition. Lip model is built based on the concatenated gray level distribution model, and the recognition problem is simplified as the minimization problem of matching object function. The Down Hill Simplex Algorithm is used for the minimization with the proposed novel method for setting initial condition, which can refrain Iteration from converging to local minima. The proposed algorithm shows extracting lip shape from the test image where Active Shape Model fails.

• Journal of Wetlands Research
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• v.17 no.4
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• pp.421-427
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• 2015

In ASM model, organic matters are classified according to their characteristics and general classification into COD and BOD cannot satisfy conditions required by ASM. In this study, it was performed to study classification of organic matters required by ASM on the basis of microorganisms' respiration rate subject to wastewater and sludge treatment. As results of analysis of the organic matter's appearance, it was found that there were some differences in composition of organic matters between wastewaters. It is considered that it is an important characteristic of wastewater that should be understood in treating wastewater in each process. Therefore, it is considered that appearance of organic matters in each wastewater identified by this study will be used as important basic data for operation of municipal wastewater treatment plant. It was identified that SS was an important factor affecting nitrification through organic matter and ammonium nitrogen change analysis according to reaction time in the nitrification. It is considered that the nitrification has close relationship with choice of optimal retention time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.141-149
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• 2007

Associating the shoulder line with head location of the human body is useful in verifying, localizing and tracking persons in an image. Since the head line and the shoulder line, what we call ${\Omega}$-shape, move together in a consistent way within a limited range of deformation, we can build a statistical shape model using Active Shape Model (ASM). However, when the conventional ASM is applied to ${\Omega}$-shape fitting, it is very sensitive to background edges and clutter because it relies only on the local edge or gradient. Even though appearance is a good alternative feature for matching the target object to image, it is difficult to learn the appearance of the ${\Omega}$-shape because of the significant difference between people's skin, hair and clothes, and because appearance does not remain the same throughout the entire video. Therefore, instead of teaming appearance or updating appearance as it changes, we model the discriminative appearance where each pixel is classified into head, torso and background classes, and update the classifier to obtain the appropriate discriminative appearance in the current frame. Accordingly, we make use of two features in fitting ${\Omega}$-shape, edge gradient which is used for localization, and discriminative appearance which contributes to stability of the tracker. The simulation results show that the proposed method is very robust to pose change, occlusion, and illumination change in tracking the head and shoulder line of people. Another advantage is that the proposed method operates in real time.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.512-517
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• 2011

In this paper, we propose an Active Shape Model (ASM) and Lucas-Kanade (LK) optical flow-based feature extraction and analysis method for analyzing the emotional features from facial images. Considering the facial emotion feature regions are described by Facial Action Coding System, we construct the feature-related shape models based on the combination of landmarks and extract the LK optical flow vectors at each landmarks based on the centre pixels of motion vector window. The facial emotion features are modelled by the combination of the optical flow vectors and the emotional states of facial image can be estimated by the probabilistic estimation technique, such as Bayesian classifier. Also, we extract the optimal emotional features that are considered the high correlation between feature points and emotional states by using common spatial pattern (CSP) analysis in order to improvise the operational efficiency and accuracy of emotional feature extraction process.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.335-336
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• 2006

In this paper, we propose an active shape image segmentation method for three-dimensional(3-D) medical images using a generation method of the 3-D shape model. The proposed method generates the shape model using a distance transform and a tetrahedron method for landmarking. After generating the 3-D model, we extend the training and segmentation processes of 2-D active shape model(ASM) and improve the searching process. The proposed method provides comparative results to 2-D ASM, region-based or contour-based methods. Experimental results demonstrate that this algorithm is effective for a semi-automatic segmentation method of 3-D medical images.