• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권8호
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• pp.1843-1859
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• 2013

The continuous increase of the spatial resolution of remote sensing images brings great challenge to image analysis and processing. Traditional prior knowledge-based region detection and target recognition algorithms for processing high resolution remote sensing images generally employ a global searching solution, which results in prohibitive computational complexity. In this paper, a more efficient region of interest (ROI) detection algorithm based on visual attention and threshold segmentation (VA-TS) is proposed, wherein a visual attention mechanism is used to eliminate image segmentation and feature detection to the entire image. The input image is subsampled to decrease the amount of data and the discrete moment transform (DMT) feature is extracted to provide a finer description of the edges. The feature maps are combined with weights according to the amount of the "strong points" and the "salient points". A threshold segmentation strategy is employed to obtain more accurate region of interest shape information with the very low computational complexity. Experimental statistics have shown that the proposed algorithm is computational efficient and provide more visually accurate detection results. The calculation time is only about 0.7% of the traditional Itti's model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권6호
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• pp.3037-3054
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• 2019

Public bicycle system (PBS) is a new emerging and popular mode of public transportation. PBS data can be adopted to analyze human movement patterns. Previous work usually focused on specific scales, and the relationships between different levels of hierarchies are ignored. In this paper, we introduce a multi-scale and interactive visual analytics system to investigate human cycling movement and PBS usage condition. The system supports level-of-detail explorative analysis of spatio-temporal characteristics in PBS. Visual views are designed from global, regional and microcosmic scales. For the regional scale, a bicycle network is constructed to model PBS data, and an flow-based community detection algorithm is applied on the bicycle network to determine station clusters. In contrast to the previous used Louvain algorithm, our method avoids producing super-communities and generates better results. We provide two cases to demonstrate how our system can help analysts explore the overall cycling condition in the city and spatio-temporal aggregation of stations.

• Journal of Information Processing Systems
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• 제18권6호
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• pp.813-821
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• 2022

Intelligent monitoring, life entertainment, medical rehabilitation, and other fields are only a few examples where visual image technology is becoming increasingly sophisticated and playing a significant role. Recognizing Wushu, or martial arts, movements through the use of visual image technology helps promote and develop Wushu. In order to segment and extract the signals of Wushu movements, this study analyzes the denoising of the original data using the wavelet transform and provides a sliding window data segmentation technique. Wushu movement The Wushu movement recognition model is built based on the hidden Markov model (HMM). The HMM model is trained and taught with the help of the Baum-Welch algorithm, which is then enhanced using the frequency weighted training approach and the mean training method. To identify the dynamic Wushu movement, the Viterbi algorithm is used to determine the probability of the optimal state sequence for each Wushu movement model. In light of the foregoing, an HMM-based martial arts movements recognition model is developed. The recognition accuracy of the HMM model increases to 99.60% when the number of samples is 4,000, which is greater than the accuracy of the SVM (by 0.94%), the CNN (by 1.12%), and the BP (by 1.14%). From what has been discussed, it appears that the suggested system for detecting martial arts acts is trustworthy and effective, and that it may contribute to the growth of martial arts.

• 한국조경학회지
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• 제32권1호
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• pp.57-68
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• 2004

The purpose of this paper is to discover the Image and Visual Preference of the Environmental Sculpture in Urban Streetscape. For this, the analysis was preformed by the data obtained from questionnaires and from the photos of the environmental sculptures scene. The landscape image was analyzed by the factor analysis algorithm. The level of visual preference was measured by a slide simulation test, and this data was analyzed by multiple regression. The results of this study can be summarized as follows: The visual preference of the environmental sculpture has been evaluated to average 4.03 on a scale of 7 Landscape slides No. 11 and No.5 were ranked more highly for visual preference. Factors formulating the landscape image were found to be 'beauty', 'orderliness', 'emotion', and 'formation'. By using the control method for the number of factors, T.V., were obtained as 63.0%. For all experimental landscape slides, the factor of orderliness was found to be the main factor determining the visual preference. The 4 factors for visual preference were analyzed by regression as follows: Visual Preference = 3.996 + 0.341(FS1) + 0.595(FS2) + 0.222(FS3) + 0.011(FS4), R-Square = 0.520.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.101.6-101
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the product(bad pallets). An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labeling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets ...

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2019년도 추계학술대회
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• pp.180-181
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• 2019

This paper proposes a rate control algorithm for intra coding frame in HEVC encoder using a deep learning approach. The proposed algorithm is designed for CTU level bit allocation in intra frame by considering visual features spatially and temporally. Our features are generated using visual geometry group (VGG-16) with deep convolutional layers, then it is used for bit allocation per each CTU within an intra frame. According to our experiments, the proposed algorithm can achieve -2.04% Luma component BD-rate gain with minimal bit accuracy loss against the HM-16.20 rate control model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권3호
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• pp.211-216
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• 2011

The detection of defective parts in a factory is usually performed by the human eye. Therefore, heavy manpower is in demand for minor enterprises. An image processing system is desired to solve this drawback. However, due to the variety of the products characteristics, an general algorithm is needed that can adapt to these characteristics. Therefore, in this paper, the key pad parts' characteristics which need to be dealt with are analyzed in order to embody the image processing algorithm that is suggested. The experimental results show the probability of detecting a defective part is 95% with a detection time of 0.203 seconds, on the average.

• 한국멀티미디어학회논문지
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• 제4권3호
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• pp.222-229
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• 2001

하나의 정지영상 내에서 공간적으로 인접한 화소들을 사용하여 디지털 영상을 확대하기 위한 많은 방법들이 제안되고 있다. 본 논문에서는 보간 화소점에 인접한 화소들의 상관도에 따라 상대적으로 우수한 성능을 보여주고 있는 pseudomedian 필터의 부위도우 설정을 가변적으로 변화하여 윤곽 정보의 재현성을 개선한 디지털 영상 확대방법을 제안하였다. 제안한 알고리즘은 Visual C++을 이용하여 시뮬레이션하였고, PSNR을 통하여 보간 알고리즘의 성능을 검증하였다. 최종적으로, 제안한 알고리즘인 적응형 pseudomedian 필터는 synopsys VHDL을 사용하여 설계하였다

• 전기학회논문지
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• 제59권1호
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• pp.134-137
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• 2010

An LED sensor luminaire for visual function improvement necessitates the control algorithm for light level adjustment and the appropriate lens design. The control algorithm adapts to surround lighting condition, and thus has the advantages of energy saving and glare reduction. The multi-cell lens design improves color temperature uniformity and spatial light distribution of the luminaire. Experimental and simulated results show that this approach contributes noticeably to energy saving and color temperature uniformity of the LED sensor luminaire.

• 한국멀티미디어학회논문지
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• 제23권1호
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• pp.58-66
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• 2020

5G-based HMD technology grew rapidly in the context of the environment change of convergence technology media and mobile networks in the fourth industrial era. It has also grown into a core technology that transforms our digital visual system. However, there is no research or system that can understand and verify radical visual system changes. Therefore, it is necessary to have an engineering understanding and verification of the diffusion of HMD media imaging devices. Beyond the distinction between virtual and real, research is urgently needed on the new three-dimensional interface of the 21st century through viewer participation. For this reason, research on the algorithm structure of interactive video media using L-System is an essential process and will be a guide to understanding the virtual reality interactive environment.