• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.367-370
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• 2015

This paper proposes an improve method of the detection performance of traffic lights for autonomous driving cars. Earlier detection methods used to adopt color thresholding, template matching and based learning maching methods, but its have some problems such as recognition rate decreasing, slow processing time. The proposed method uses both detection mask and morphological preprocessing. Firstly, input color images are converted to YCbCr image in order to strengthen its illumination, and horizontal edge components are extracted in the Y Channel. Secondly, the region of interest is detected according to morphological characteristics of the traffic lights. Finally, the traffic signal is detected based on color distributions. The proposed method showed that the detection rate and processing time improved rather than the conventional algorithm about some surrounding environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.93-96
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• 2015

In this paper, we introduce a fire detection system using context-aware sensor. In existing weather and based on vision sensor of fire detection system case, acquired image through sensor of camera is extracting features about fire range as processing to convert HSI(Hue, Saturation, Intensity) model HSI which is color space can have durability in illumination changes. However, in this case, until a fire occurs wide range of sensing a fire in a single camera sensor, it is difficult to detect the occurrence of a fire. Additionally, the fire detection in complex situations as well as difficult to separate continuous boundary is set for the required area is difficult. In this paper, we propose an algorithm for real-time by using a temperature sensor, humidity, Co2, the flame presence information acquired and comparing the data based on multiple conditions, analyze and determine the weighting according to fire it. In addition, it is possible to differential management to intensive fire detection is required zone dividing the state of fire.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.711-720
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• 2012

In this paper, we introduce the implementation of driver fatigue monitering system and its result. Input video device is selected commercially available web-cam camera. Haar transform is used to face detection and adopted illumination normalization is used for arbitrary illumination conditions. Facial image through illumination normalization is extracted using Haar face features easily. Eye candidate area through illumination normalization can be reduced by anthropometric measurement and eye detection is performed by PCA and Circle Mask mixture model. This methods achieve robust eye detection on arbitrary illumination changing conditions. Drowsiness state is determined by the level on illumination normalize eye images by a simple calculation. Our system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. Our algorithm is implemented with low computation complexity and high recognition rate. We achieve 97% of correct detection rate through in-car environment experiments.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.119-130
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• 2017

In many literatures on VaR and CTE for multivariate distribution, these are estimated by using transformed univariate distribution with a specific ratio of many kinds of portfolios. Even though there are lots of works to define quantiles for multivariate distributions, there does not exist a quantile uniquely. Hence, it is not easy to define the VaR and CTE. In this paper, we propose the weighted CTE vectors corresponding to various ratio combinations of many kinds of portfolios by extending the researches on the alternative VaR and integrated multivariate CTE based on multivariate quantiles. We extend relation equations about univariate CTEs to multivariate CTE vectors and discuss their characteristics. The proposed weighted CTEs are explored with some data from multivariate normal distribution and illustrative examples.

• Journal of the Korea Computer Graphics Society
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• v.21 no.3
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• pp.55-61
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• 2015

In this paper, we introduce a method to synthesize realistic make-up effects on input images efficiently. In particular, we focus on shading on the make-up effects due to the lighting and face curvature. By doing this, we can synthesize a wider range of effects realistically than the previous methods. To do this, the information about lighting information together with the normal vectors on all pixels over the face region in the input image. Since the previous methods that compute lighting information and normal vectors require relatively heavy computation cost, we introduce an approach to approximate lighting information using cascade pose regression process and normal vectors by transforming, rendering, and warping a standard 3D face model. The proposed method consumes much less computation time than the previous methods. In our experiment, we show the proposed approximation technique can produce naturally looking virtual make-up effects.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.10
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• pp.969-982
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• 2016

Recently, the researches to discovery drug candidates from natural herbs have received considerable attention. In human body, enzyme mostly metabolize the compounds of natural herbs. In this study, we analysis the enzyme interactions using assoication mining. We get this data from BRENDA(: BRaunschweig ENzyme DAtabase) system. Based on enzyme interaction model, we divide the metabolites into substrate metabolites, product metabolites, inhibitor metabolites, and activating metabolites. We then compose substrate metabolite transaction, product metabolite transaction with each metabolites and enzyme interaction transaction with all metabolites. Also we take account of organism for each transactions. We mine frequent metabolites and patterns from six transactions using association rule mining. And we analysis the relationship among metabolites. As a result, we identify the distributions and patterns of metabolites consist in enzyme interactions. We found that metabolites include in only substrate are identified and have very low supports. This results can be useful to develop the effective metabolism prediction model for compounds of natural herbs.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.449-463
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• 2015

Video object tracking is important for variety of applications, such as security, video indexing and retrieval, video surveillance, communication, and compression. This paper proposes an object tracking method in HEVC bitstreams. Without pixel reconstruction, motion vector (MV) and size of prediction unit in the bitstream are employed in an Spatio-Temporal Markov Random Fields (ST-MRF) model which represents the spatial and temporal aspects of the object's motion. Coefficient-based object shape adjustment is proposed to solve the over-segmentation and the error propagation problems caused in other methods. In the experimental results, the proposed method provides on average precision of 86.4%, recall of 79.8% and F-measure of 81.1%. The proposed method achieves an F-measure improvement of up to 9% for over-segmented results in the other method even though it provides only average F-measure improvement of 0.2% with respect to the other method. The total processing time is 5.4ms per frame, allowing the algorithm to be applied in real-time applications.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.2
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• pp.211-217
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• 2015

Emission gas regulations and constantly increasing fuel costs call for the worldwide use of environmentally friendly and energy-efficient machines in industry. To meet these requirements, a hybrid excavator prototype has been developed that incorporates an electric swing motor, engine assist motor, and ultra-capacitor module into a conventional hydraulic excavator of the 22-ton class. This paper mainly describes a few techniques to optimize its energy efficiency. These include 1) controlling the engine speed in proportion to the load torque, 2) controlling the pump displacement when driving the electric swing system, 3) managing the ultra-capacitor voltage to minimize the electrical energy loss, and 4) reducing the cooling fan speed to improve the energy efficiency of the system.

• 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 the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.85-94
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• 2012

Lane marking detection is essential to both ITS and DAS systems. The objective of this paper is to provide more robust technique for lane marking detection than traditional techniques by using scale-space technique. Variable thresholding that is based on the local statistics may be very effective for detecting such objects as lane markings that have prominent intensities. However, such techniques that only rely on local statistics have limitations containing irrelevant areas as well. We reduce the candidate areas by combining the variable thresholding result with cost-efficient horizontal 1D LoG filtered scale space. Through experiments using practical images, we could achieve significant improvement over the techniques based not only on the variable thresholding but also on the Hough transform that is another very popular technique for this purpose.