• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.751-754
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• 2007

This research executes recognition research on politics realities to highschool students. Their evaluation under 60 point was 48.5%, between 61 and 70 was 36.5%. It shows that most high school students recognize that politics realities is not good. Specially, evaluation of qualities of politician under 60 points was 63.1%. On the other hand, the biggest problem which they think was politicians. This response was 64.1%, it's the highest rate. And they response that the thing needed for developing our country were : first, improvement of politician's qualities, it's 64.1%. second, changing politics culture, it's 11.2%, third, improving government system, it's 9.5%. fourth, reforming politics system. It tells us most respondents think that politicians should improve their qualities. And in question for improving awareness of politics of young people, they answered visiting a political party(26.7%), education of politics (24.1%), a mock politics programs(21.9%).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.1
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• pp.158-164
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• 2009

The real time security system using web camera shall correspond in commensurate with it in real time through classifying moving object and analyzing the behavior. But, as to the detection of moving object in real time image through a camera, it is difficult to detect movement correctly according to the change of unnecessary noises, lighting conditions and screened phenomenon. This paper proposes real time security system by dual camera and ultrasonic sensor, a method of advanced detection in order to detect correct movement of specific object. That is, we could improve the tracing characteristics by using ultrasonic sensor as measurement factor of changed position and verify through experiments that the information interchanged between camera upwards and in front of it have effect on tracing a specific object continuously. The results of the experiment show that recognition rate of object was 97.4% and the correct tracing could be done lastingly in a phenomena of screening object.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.96-105
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• 2015

Recently, the Department has utilized the media facade as a means to attract new customers and promotional tools. In particular, we checked the rate of customer's gender who visited a large department store. The ratio of women's visit is 4.6 times more than men. This can confirm the need to produce a differentiated content of LED media facade by gender. This study are subject to an empirical analysis of differences of perception of evaluation factors of media facade in gender. At first we specified four factors which can evaluate the media facade according to gender by previous studies. There are aesthetics, artistry, comfort and harmony. And the hypothesis was set as "Each factor might be differences between the recognition of their gender" In order to verify a hypothesis the country's large department store was selected and experiment was performed. In the result of the experiment, among the four factors, aesthetics, creativity, and harmony were chosen, while comfort was dismissed. This results confirm that the following factors are needed to attract more women's customer at the department such as combination of space and media facade, combination of shape and color, appropriateness of the information and beautiful place, and directing way of content.

• The Journal of the Acoustical Society of Korea
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• v.32 no.5
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• pp.438-445
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• 2013

In this paper, we propose an enhancement of Japanese acoustic model which is trained with Korean speech database by using several combination strategies. We describe the strategies for training more than two language combination, which are Cross-Language Transfer, Cross-Language Adaptation, and Data Pooling Approach. We simulated those strategies and found a proper method for our current Japanese database. Existing combination strategies are generally verified for under-resourced Language environments, but when the speech database is not fully under-resourced, those strategies have been confirmed inappropriate. We made tyied-list with only object-language on Data Pooling Approach training process. As the result, we found the ERR of the acoustic model to be 12.8 %.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.667-674
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• 2007

Facial expressions provide significant clues about one's emotional state; however, it always has been a great challenge for machine to recognize facial expressions effectively and reliably. In this paper, we report a method of feature-based adaptive motion energy analysis for recognizing facial expression. Our method optimizes the information gain heuristics of ID3 tree and introduces new approaches on (1) facial feature representation, (2) facial feature extraction, and (3) facial feature classification. We use minimal reasonable facial features, suggested by the information gain heuristics of ID3 tree, to represent the geometric face model. For the feature extraction, our method proceeds as follows. Features are first detected and then carefully "selected." Feature "selection" is finding the features with high variability for differentiating features with high variability from the ones with low variability, to effectively estimate the feature's motion pattern. For each facial feature, motion analysis is performed adaptively. That is, each facial feature's motion pattern (from the neutral face to the expressed face) is estimated based on its variability. After the feature extraction is done, the facial expression is classified using the ID3 tree (which is built from the 1728 possible facial expressions) and the test images from the JAFFE database. The proposed method excels and overcomes the problems aroused by previous methods. First of all, it is simple but effective. Our method effectively and reliably estimates the expressive facial features by differentiating features with high variability from the ones with low variability. Second, it is fast by avoiding complicated or time-consuming computations. Rather, it exploits few selected expressive features' motion energy values (acquired from intensity-based threshold). Lastly, our method gives reliable recognition rates with overall recognition rate of 77%. The effectiveness of the proposed method will be demonstrated from the experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.12-17
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• 2005

The segment matching method shows better performance than the global and points-based methods to compare reference signature with an input signature. However, the segment-to-segment matching method has the problem of decreasing recognition rate according to the variation of partitioning points. This paper proposes a fusion model based on the segment matching and HMM to construct a more reliable authentic system. First, a segment matching classifier is designed by conventional technique to calculate matching values lot dynamic information of signatures. And also, a novel HMM classifier is constructed by using the principal component analysis to calculate matching values for static information of signatures. Finally, SVM classifier is adopted to effectively combine two independent classifiers. From the various experiments, we find that the proposed method shows better performance than the conventional segment matching method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.109-116
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation for the identification of a face shape. Also it satisfies both efficiency of calculation and the function of detection. The algorithm proposed segmented the face area through pre-processing using a face shape as input information in an environment with a single camera and then identified the shape using a Self Organized Feature Map(SOFM). However, as it is not easy to exactly recognize a face area which is sensitive to light, it has a large degree of freedom, and there is a large error bound, to enhance the identification rate, rotation information on the face shape was made into a database and then a principal component analysis was conducted. Also, as there were fewer calculations due to the fewer dimensions, the time for real-time identification could be decreased.

• Convergence Security Journal
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• v.20 no.2
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• pp.111-121
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• 2020

Deep neural networks (DNNs) provide good performance for machine learning tasks such as image recognition and object recognition. However, DNNs are vulnerable to an adversarial example. An adversarial example is an attack sample that causes the neural network to recognize it incorrectly by adding minimal noise to the original sample. However, the disadvantage is that it takes a long time to generate such an adversarial example. Therefore, in some cases, an attack may be necessary that quickly causes the neural network to recognize it incorrectly. In this paper, we propose a fast misclassification sample that can rapidly attack neural networks. The proposed method does not consider the distortion of the original sample when adding noise. We used MNIST and CIFAR10 as experimental data and Tensorflow as a machine learning library. Experimental results show that the fast misclassification sample generated by the proposed method can be generated with 50% and 80% reduced number of iterations for MNIST and CIFAR10, respectively, compared to the conventional Carlini method, and has 100% attack rate.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.561-564
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• 2004

Crack sealing automation machines' have been continually developed since the early 1990's because of the effectiveness of crack sealing that would be able to improve safety, quality and productivity. It has been considered challenging problem to detect crack network in pavement which includes noise (oil marks, skid marks, previously sealed cracks and inherent noise). It is required to develop crack network mapping and modeling algorithm in order to accurately inject sealant along to the middle of cut crack network. The primary objective of this study is to propose a crack network mapping and modeling algorithm using neural network for improving the accuracy of the algorithm used in the APCS. It is anticipated that the effective use of the proposed algorithms would be able to reduce error rate in image processing for detecting, mapping and modeling crack network as well as improving quality and productivity compared to existing vision algorithms.

• Journal of IKEEE
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• v.23 no.4
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• pp.1423-1429
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• 2019

Recently, a system that supports efficient interaction, a human machine interface (HMI), has become a hot topic. In this paper, we propose a new real time low-cost hand gesture control system as one of vehicle interaction methods. In order to reduce computation time, depth information was acquired using a time-of-flight (TOF) camera because it requires a large amount of computation when detecting hand regions using an RGB camera. In addition, fourier descriptor were used to reduce the learning model. Since the Fourier descriptor uses only a small number of points in the whole image, it is possible to miniaturize the learning model. In order to evaluate the performance of the proposed technique, we compared the speeds of desktop and raspberry pi2. Experimental results show that performance difference between small embedded and desktop is not significant. In the gesture recognition experiment, the recognition rate of 95.16% is confirmed.