• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.287-295
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• 2006

This paper compares two different approaches based on wavelet and Gabor decomposition towards representing the texture of an arbitrary region. The Gabor-domain mean and standard deviation combination is considered to be best in representing the texture of rectangular regions. However, texture representation of arbitrary regions would enable generalized object-based image retrieval and other applications in the future. In this study, we have found that the wavelet features perform better than the Gabor features in representing the texture of arbitrary regions. Particularly, the wavelet-domain standard deviation and entropy combination results in the best retrieval accuracy. Based on our experiment with texture image sets, we present and compare tile retrieval accuracy of multiple wavelet and Gabor feature combinations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5605-5623
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• 2016

We propose a face recognition method that utilizes the LCP face descriptor. The proposed method applies a LoG mask to extract a face contour response, and employs the LCP algorithm to produce a binary pattern representation that ensures high recognition performance even under the changes in illumination, noise, and aging. The proposed LCP algorithm produces excellent noise reduction and efficiency in removing unnecessary information from the face by extracting a face contour response using the LoG mask, whose behavior is similar to the human eye. Majority of reported algorithms search for face contour response information. On the other hand, our proposed LCP algorithm produces results expressing major facial information by applying the threshold to the search area with only 8 bits. However, the LCP algorithm produces results that express major facial information with only 8-bits by applying a threshold value to the search area. Therefore, compared to previous approaches, the LCP algorithm maintains a consistent accuracy under varying circumstances, and produces a high face recognition rate with a relatively small feature vector. The test results indicate that the LCP algorithm produces a higher facial recognition rate than the rate of human visual's recognition capability, and outperforms the existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.723-743
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• 2016

Indoor positioning is considered an enabler for a variety of applications, the demand for an indoor positioning service has also been accelerated. That is because that people spend most of their time indoor environment. Meanwhile, the smartphone integrated powerful camera is an efficient platform for navigation and positioning. However, for high accuracy indoor positioning by using a smartphone, there are two constraints that includes: (1) limited computational and memory resources of smartphone; (2) users' moving in large buildings. To address those issues, this paper uses the TC-OFDM for calculating the coarse positioning information includes horizontal and altitude information for assisting smartphone camera-based positioning. Moreover, a unified representation model of image features under variety of scenarios whose name is FAST-SURF is established for computing the fine location. Finally, an optimization marginalized particle filter is proposed for fusing the positioning information from TC-OFDM and images. The experimental result shows that the wide location detection accuracy is 0.823 m (1σ) at horizontal and 0.5 m at vertical. Comparing to the WiFi-based and ibeacon-based positioning methods, our method is powerful while being easy to be deployed and optimized.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.350-359
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• 2011

Fast developments of broadcasting technologies since 1990s enabled not only High Definition Television service providing high quality audiovisual contents at home but also mobile broadcasting service providing audiovisual contents to high speed moving vehicle. Terrestrial Digital Multimedia Broadcasting (T-DMB) is one of the technologies developed for mobile broadcasting service, which has been successfully commercialized. One of the major technical breakthroughs achieved by T-DMB in addition to robust vehicular reception is an adoption of framework based on MPEG-4 System. It naturally enables integrated interactive data services by using Binary Format for Scene (BIFS) technology for scene description and representation of graphics object and Object Descriptor Framework representing multimedia service components as objects. T-DMB interactive data service has two fundamental limitations. Firstly, graphic data for interactive service should be always overlaid on top of a video not to be rendered out of it. Secondly, data for interactive service is only received by broadcasting channel. These limitations were considered as general in broadcasting systems. However, they are being considered as hard limitations for personalized data services using location information and user characteristics which are becoming widely used for data services of smart devices in these days. In this paper, the architecture of T-DMB hybrid data service is proposed which is utilizing broadcasting network, wireless internet and local storage for delivering BIFS data to overcome these limitations. This paper also presents hybrid BIFS technology to implement T-DMB hybrid data service while maintaining backward compatibility with legacy T-DMB players.

• Convergence Security Journal
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• v.19 no.2
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• pp.91-104
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• 2019

In this paper, we present a novel local descriptor, Local Prominent Directional Pattern (LPDP), to represent the description of facial images for gender recognition purpose. To achieve a clearly discriminative representation of local shape, presented method encodes a target pixel with the prominent directional variations in local structure from an analysis of statistics encompassed in the histogram of such directional variations. Use of the statistical information comes from the observation that a local neighboring region, having an edge going through it, demonstrate similar gradient directions, and hence, the prominent accumulations, accumulated from such gradient directions provide a solid base to represent the shape of that local structure. Unlike the sole use of gradient direction of a target pixel in existing methods, our coding scheme selects prominent edge directions accumulated from more samples (e.g., surrounding neighboring pixels), which, in turn, minimizes the effect of noise by suppressing the noisy accumulations of single or fewer samples. In this way, the presented encoding strategy provides the more discriminative shape of local structures while ensuring robustness to subtle changes such as local noise. We conduct extensive experiments on gender recognition datasets containing a wide range of challenges such as illumination, expression, age, and pose variations as well as sketch images, and observe the better performance of LPDP descriptor against existing local descriptors.

• Journal of Power System Engineering
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• v.16 no.2
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• pp.66-74
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• 2012

In this paper, the authors propose a new approach to control a barge type surface vessel. It is based on the Dynamic Positioning System(DPS) design. The main role of barge ship is to carry and supply the materials to the floating units and other places. To carry out this job, it should be positioned in the specified area. However sometimes the thrust systems are installed on it, and in general the rope control by mooring winch system is used. It may be difficult to compare the control performances of two types. If we consider this problem in point of usefulness, we can easily find out that the winch control system is more useful and applicable to the real field than the thrust control system except a special use. Therefore, in this paper we consider a DPS design problem which can be extended to the many application fields. The goal of this paper is twofold. First, the sliding mode controller (SMC) for positioning the our vessel is proposed. Especially, in this paper, a robust stability condition is given based on descriptor system representation. In the result, the sliding mode control law guarantees to keep the vessel in the defined area in the presence of environmental disturbances. And second, the thrust allocation problem is solved by using redistributed pseudo-inverse (RPI) algorithm to determine the thrust force and direction of each individual actuator. The proposed approach has been simulated with a supply vessel model and found work well.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.13-22
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• 2004

Because video sequence consists of dynamic objects in nature, the object motion in video is an effective feature in describing the contents of video sequence and motion feature plays an important role in video retrieval. In this paper, we propose a method that converts motion vectors (MVs) to a uniform set on MPEG coded domain, independent of the frame type and the direction of prediction, and utilizes these normalized MVs (N-MVs) as motion descriptor to understand video contents. We describe a frame-type independent representation of the various types of frames presented in an MPEG video in which all frames can be considered equivalently, without full-decoding. In the experiments, we show that the proposed method is better than the conventional one in terms of performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.1-14
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• 2010

With the rapid growth of 3D content industry fields, 3D content-based hashing (or hash function) has been required to apply to authentication, trust and retrieval of 3D content. A content hash can be a random variable for compact representation of content. But 3D content-based hashing has been not researched yet, compared with 2D content-based hashing such as image and video. This paper develops a robust 3D content-based hashing based on key-dependent 3D surface feature. The proposed hashing uses the block surface coefficient using shape coordinate of 3D SSD and curvedness for 3D surface feature and generates a binary hash by a permutation key and a random key. Experimental results verified that the proposed hashing has the robustness against geometry and topology attacks and has the uniqueness of hash in each model and key.

• Journal of Navigation and Port Research
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• v.36 no.5
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• pp.379-385
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• 2012

In this paper, the stability and stabilization problems for marine vessels including surface and underwater vehicles are described. In the marine vessels, there are many and strong nonlinear parameters. These give hard design process and difficulties to us. In this article, at first we make a descriptor system representation as a controlled system to preserve the physical parameters of the system as it is. And we propose a new stability and stabilizability conditions based on the quadratic stabilization approach which gives a solution for the unreasonable problems produced by added mass. That is, the proposed conditions are not interfered with the nonsymmetric matrix constraint. And the stability condition is given by an matrix inequality such that it makes us to obtain a solution easily for something.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.739-748
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• 2014

In this paper, we propose pyramid appearance and global structure action descriptors on both RGB and depth motion history images and a model-free method for human action recognition. In proposed algorithm, we firstly construct motion history image for both RGB and depth channels, at the same time, depth information is employed to filter RGB information, after that, different action descriptors are extracted from depth and RGB MHIs to represent these actions, and then multimodality information collaborative representation and recognition model, in which multi-modality information are put into object function naturally, and information fusion and action recognition also be done together, is proposed to classify human actions. To demonstrate the superiority of the proposed method, we evaluate it on MSR Action3D and DHA datasets, the well-known dataset for human action recognition. Large scale experiment shows our descriptors are robust, stable and efficient, when comparing with the-state-of-the-art algorithms, the performances of our descriptors are better than that of them, further, the performance of combined descriptors is much better than just using sole descriptor. What is more, our proposed model outperforms the state-of-the-art methods on both MSR Action3D and DHA datasets.