• Journal of Multimedia Information System
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• v.2 no.1
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• pp.171-178
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• 2015

This article describes 3 dimensional (3D) face recognition system using histogram of oriented gradients (HOG) based on face curvature. The surface curvatures in the face contain the most important personal feature information. In this paper, 3D face images are recognized by the face components: cheek, eyes, mouth, and nose. For the proposed approach, the first step uses the face curvatures which present the facial features for 3D face images, after normalization using the singular value decomposition (SVD). Fisherface method is then applied to each component curvature face. The reason for adapting the Fisherface method maintains the surface attribute for the face curvature, even though it can generate reduced image dimension. And histogram of oriented gradients (HOG) descriptor is one of the state-of-art methods which have been shown to significantly outperform the existing feature set for several objects detection and recognition. In the last step, the linear discriminant analysis is explained for each component. The experimental results showed that the proposed approach leads to higher detection accuracy rate than other methods.

• Journal of Platform Technology
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• v.6 no.4
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• pp.18-25
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• 2018

This paper describes a real-time human and robot tracking method in Intelligent Space with multi-camera networks. The proposed method detects candidates for humans and robots by using the histogram of oriented gradients (HOG) feature in an image. To classify humans and robots from the candidates in real time, we apply cascaded structure to constructing a strong classifier which consists of many weak classifiers as follows: a linear support vector machine (SVM) and a radial-basis function (RBF) SVM. By using the multiple view geometry, the method estimates the 3D position of humans and robots from their 2D coordinates on image coordinate system, and tracks their positions by using stochastic approach. To test the performance of the method, humans and robots are asked to move according to given rectangular and circular paths. Experimental results show that the proposed method is able to reduce the localization error and be good for a practical application of human-centered services in the Intelligent Space.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.33-47
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• 2007

The requirements have been changed during development progresses, since it is impossible to define all of software requirements. These requirements change leads to mistakes because the developers cannot completely understand the software's structure and behavior, or they cannot discover all parts affected by a change. Requirement changes have to be managed and assessed to ensure that they are feasible, make economic sense and contribute to the business needs of the customer organization. We propose a feature-oriented requirements change management method to manage requirements change with value analysis and feature-oriented traceability links including intermediate catalysis using features. Our approach offers two contributions to the study of requirements change: (1) We define requirements change tree to make user requirements change request generalize by feature level. (2) We provide overall process such as change request normalization, change impact analysis, solution dealing with change request, change request implementation, change request evaluation. In addition, we especially present the results of a case study which is carried out in asset management portal system in details.

• Journal of Multimedia Information System
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• v.4 no.1
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• pp.33-38
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• 2017

This article suggests a new algorithm for detecting two-wheelers on the road that have various shapes according to viewpoints. Because of complicated shapes, it is more difficult than detecting a human. In general, the Histograms of Oriented Gradients(HOG) feature is well known as a useful method of detecting a standing human. We propose a method of detecting a human on a two-wheelers using the spatial relocation of HOG (Histogram of Oriented Gradients) features. And this paper adapted the contrast method which is generally using in the image process to improve the detection rate. Our experimental results show that a two-wheelers detection system based on proposed approach leads to higher detection accuracy, less computation, and similar detection time than traditional features.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.219-227
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• 2011

Service Oriented Architecture (SOA) is rapidly emerging as the efficient approach in contemporary complex, heterogeneous computing environments. SOA increases the adaptability by loose coupling and its main feature is that three elements such as service provider, service requester and service registry are connected with each other systematically. To design the service-oriented system efficiently, a metric to measure the coupling between services accurately is needed. In this paper, we propose four coupling metrics for SOA based softwares. First, we suggest a coupling metric for service-oriented systems by modifying an established coupling metric of object-oriented systems. Then we suggest another coupling metric which includes indirect coupling between services. We also suggest two relative coupling metrics to measure coupling between subsystems. We investigate the theoretical soundness of the proposed metrics by the axioms of Briand et al. Finally, we apply the presented metrics to an industrial-scale case study.

• The Journal of Society for e-Business Studies
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• v.12 no.4
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• pp.1-15
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• 2007

Traceability links are logical links between individual requirements and other system elements such as architecture descriptions, source code, and test cases. These are useful for requirements change impact analysis, requirements conflict analysis, and requirements consistency checking. However, establishing and maintaining traceability links places a big burden since complex systems have especially yield an enormous number of various artifacts. We propose a feature-oriented requirements tracing method to manage requirements with cost benefit analysis, including value consideration and intermediate catalysis using features. Our approach offers two contributions to the study of requirements tracing: (1)We introduce feature modeling as intermediate catalysis to generate traceability links between user requirements and implementation artifacts. (2)We provide value consideration with cost and efforts to identify traceability links based on prioritized requirements, thus assigning a granularity level to each feature. In this paper, we especially present the results of a case study which is carried out in Apartment Ubiquitous Platform to integrate and connect home services in an apartment complex in details.

• Journal of KIISE:Software and Applications
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• v.33 no.7
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• pp.589-604
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• 2006

Software product lines (SPL) are recently an emerging software reuse paradigm, which helps organizations develop their products from reusable core assets rather than from scratch. For developing these assets, understanding commonality and variability (C&V) is essential. A feature-oriented approach has been used extensively for C&V analysis in the SPL. However, this contains no proposal to systematically identify features and provide the rationale for the features. Further, the approach does not directly show how the results of C&V analysis will satisfy an organization's high-level business goals and provide the rationale for the C&V. Therefore, this paper presents a domain analysis method for the SPL based on goals, scenarios, and features in order to overcome some of the deficiencies and limitations of the feature-oriented approach. In particular, the paper proposes a domain requirements model (DRM) and a domain requirements modeling method based on the DRM. This method has been applied to the home integration system (HIS) domain to demonstrate its feasibility with a supporting tool, namely IDEAS. Our approach makes it possible to systematically identify the features and provide the rationale for both the features and the C&V.

• Journal of Power Electronics
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• v.16 no.3
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• pp.994-1003
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• 2016

Two major obstacles in the utilization of electrical vehicles are their price and range. The collaboration of direct torque control (DTC) with induction motor (IM) is preferred for its low cost, easy implementation, and parameter independency. However, in terms of edges, the method has drawbacks, such as variable switching frequency and undesired current harmonic distortion. These drawbacks result in acoustic noise, reduced efficiency, and electromagnetic interference. A feed-forward approach for stator-flux-oriented DTC with space vector pulse-width modulation is presented in in this paper. The outcome of the proposed method is low current harmonic distortion with fixed switching frequency while preserving the torque performance and simple application feature of basic DTC. The method is applicable to existing and forthcoming IM drive systems via software adaptation. The validity of the proposed method is confirmed by simulation and experimental results.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.7
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• pp.337-352
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• 2017

Clone-and-own reuse is an approach to creating new software variants by copying and modifying existing software products. A family of legacy software products developed by clone-and-own reuse often requires high maintenance cost and tends to be error-prone due to patch-ups without refactoring and structural degradation. To overcome these problems, many organizations that have used clone-and-own reuse now want to migrate their legacy products to software product line (SPL) for more systematic reuse and management of software asset. However, with most of existing methods, variation points are embedded directly into design and code rather than modeled and managed separately; variation points are not created ("engineered") systematically based on a variability model. This approach causes the following problems: it is difficult to understand the relationships between variation points, thus it is hard to maintain such code and the asset tends to become error-prone as it evolves. Also, when SPL evolves, design/code assets tend to be modified directly in an ad-hoc manner rather than engineered systematically with appropriate refactoring. To address these problems, we propose a feature-oriented method for extracting a SPL asset from a family of legacy applications. With the approach, we identify and model variation points and their relationships in a feature model separate from implementation, and then extract and manage a SPL asset from legacy applications based on the feature model. We have applied the method to a family of legacy Notepad++ products and demonstrated the feasibility of the method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2124-2148
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• 2017

Accurate facial expression recognition (FER) requires reliable signal filtering and the effective feature extraction. Considering these requirements, this paper presents a novel approach for FER which is robust to noise. The main contributions of this work are: First, to preserve texture details in facial expression images and remove image noise, we improved the anisotropic diffusion filter by adjusting the diffusion coefficient according to two factors, namely, the gray value difference between the object and the background and the gradient magnitude of object. The improved filter can effectively distinguish facial muscle deformation and facial noise in face images. Second, to further improve robustness, we propose a new feature descriptor based on a combination of the Histogram of Oriented Gradients with the Canny operator (Canny-HOG) which can represent the precise deformation of eyes, eyebrows and lips for FER. Third, Canny-HOG's block and cell sizes are adjusted to reduce feature dimensionality and make the classifier less prone to overfitting. Our method was tested on images from the JAFFE and CK databases. Experimental results in L-O-Sam-O and L-O-Sub-O modes demonstrated the effectiveness of the proposed method. Meanwhile, the recognition rate of this method is not significantly affected in the presence of Gaussian noise and salt-and-pepper noise conditions.