• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.747-748
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• 2010

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.925-932
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• 2012

In this paper, we develop a pattern recognition algorithm applied to a humanoid robot which is exploited as a guide for visually handicapped persons to find a desired path to their destinations. Behavior primitives of a humanoid robot are defined, and Canny's edge detection algorithm is employed to extract the pattern and color of the paving blocks that especially devised for visually handicapped persons. Based on these, an efficient path finding algorithm is developed and implemented on a humanoid robot, running on an embedded linux operating system equipped with a video camera. The performance of our algorithm is experimentally examined in terms of the response time and the pattern recognition ratio. In order to validate our algorithm in various realistic environments, the experiments are repeatedly performed by changing the tilt of paving blocks and the brightness in surrounding area. The results show that our algorithm performs sufficiently well to be exploited as a path finding system for visually handicapped persons.

• Journal of Satellite, Information and Communications
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• v.11 no.1
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• pp.55-57
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• 2016

In this paper, we present an algorithm to determine the abnormal behavior through a CCTV-based behavioral recognition and a pattern of hand using ConvexHull. In the existing way that using CCTV for crime prevention, facial recognition is mainly used. Facial recognition is the way that compares the faces that are seen on the screen and faces of criminals for determining how dangerous targets are, however, this way is hard to predict future criminal behavior. Therefore, to predict more various situations, abnormal behaviours are determined with targets' incline of arms, legs and bodys and patterns of hand movements. it can forecast crimes when an acting has been getting within common normality out, comparing whose acting patterns with the crime patterns.

• Journal of Digital Contents Society
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• v.15 no.5
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• pp.579-586
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• 2014

This paper analyzes the recognition of driver's behavior in lane change using context-free grammar. In contrast to conventional pattern recognition techniques, context-free grammars are capable of describing features effectively that are not easily represented by finite symbols. Instead of coordinate data processing that should handle features in multiple concurrent events respectively, effective syntactic analysis was applied for patterning of symbolic sequence. The findings proposed the effective and intuitive method for drivers and researchers in driving safety field. Probabilistic parsing for the improving this research will be the future work to achieve a robust recognition.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.91-96
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• 2022

At the current camera-based technology level, sensor-based basic life pattern recognition technology has to suffer inconvenience to obtain accurate data, and commercial band products are difficult to collect accurate data, and cannot take into account the motive, cause, and psychological effect of behavior. the current situation. In this paper, radar technology for life pattern recognition is a technology that measures the distance, speed, and angle with an object by transmitting a waveform designed to detect nearby people or objects in daily life and processing the reflected received signal. It was designed to supplement issues such as privacy protection in the existing image-based service by applying it. For the implementation of the proposed system, based on TI IWR1642 chip, RF chipset control for 60GHz band millimeter wave FMCW transmission/reception, module development for distance/speed/angle detection, and technology including signal processing software were implemented. It is expected that analysis of individual life patterns will be possible by calculating self-management and behavior sequences by extracting personalized life patterns through quantitative analysis of life patterns as meta-analysis of living information in security and safe guards application.

• Science of Emotion and Sensibility
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• v.7 no.3
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• pp.37-50
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• 2004

This study attempted to explore how online game is endowed new meaning and function and changed into totally different product in result by recognition and consuming behavior(game activity) of game users. The subjects of this study are famous Internet based online games called 'Lineage' and 'EverQuest'. These two online games are physically similar games. Both are MMORPG and community-based games. While Lineage became a cyber world as a part of the real world, EverQuest was a game product. This study explored the recognition of garners about game world and different consuming behavior pattern(game activity pattern) in game world made by different recognition of online game. The result from exploring the differences in the recognition of game world showed Lineage garners regarded Lineage world as another living space or a part of real world they can explore and express psychological need and self-identity or self-image and live through diverse activities. But EverQuest garners regarded EverQuest as a product for experience of fantasy world. The result from comparing the game consuming behaviors showed that different recognition of game world made the differences in the game consuming behavior. The results of the present study supported that the recognition of consumers about digital images or content poducts like online game can be different by the value and experience of consumer, and the different recognition make the different consuming behavior of similar or same products. The results supported that the meaning and value of digital images or digital content are endowed by consumers.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.196-204
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• 2017

Behavior of intelligent video surveillance system is recognized by analyzing the pattern of the object of interest by using the frame information of video inputted from the camera and analyzes the behavior. Detection of object's certain behaviors in the crowd has become a critical problem because in the event of terror strikes. Recognition of object's certain behaviors is an important but difficult problem in the area of computer vision. As the realization of big data utilizing machine learning, data mining techniques, the amount of video through the CCTV, Smart-phone and Drone's video has increased dramatically. In this paper, we propose a multiple-sliding window method to recognize the cumulative change as one piece in order to improve the accuracy of the recognition. The experimental results demonstrated the method was robust and efficient learning units in the classification of certain behaviors.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1349-1350
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• 2013

• Bulletin of the Korean Chemical Society
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• v.30 no.1
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• pp.137-144
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• 2009

In this study, quantitative and pattern recognition analyses for the quality evaluation of Herba Epimedii using HPLC was developed. For quantitative analysis, five major bioactive constituents, hyperin, epimedin A, epimedin B, epimedin C, and icariin were determined. Analysis was carried out on Capcell pak $C_{18}$ column ($250{\time}4.6$ mm, 5 ${\mu}m$) with a mobile phase of mixture of acetonitrile and 0.1% formic acid, using UV detection at 270 nm. The linear behavior was observed over the investigated concentration range (2-50 ${\mu}g/mL;\;r_2\;>$ 0.99) for all analytes. The intraand inter-day precisions were lower than 4.3% (as a relative standard deviation, RSD) and accuracies between 95.1% and 104.4%. The HPLC analytical method for pattern recognition analysis was validated by repeated analysis of one reference sample. The RSD of intra- and inter-day variation of relative retention time (RRT) and relative peak area (RPA) of the 12 selected common peaks were below 0.8% and 4.7%, respectively. The developed methods were applied to analysis of twenty Herba Epimedii extract samples. Contents of hyperin, epimedin A, epimedin B, epimedin C, and icariin were calculated to be 0$\sim$0.79, 0.69$\sim$1.91, 0.93$\sim$9.58, 0.65$\sim$3.05, and 2.43$\sim$11.8 mg/g dried plant. Principal component analysis (PCA) showed that most samples were clustered together with the reference samples but several apart from the main cluster in the PC score plot, indicating differences in overall chemical composition between two clusters. The present study suggests that quantitative determination of marker compounds combined with pattern-recognition method can provide a comprehensive approach for the quality assessment of herbal medicines.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1491-1500
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• 2008

This paper proposes an intelligent surveillance system to recognize suspicious patterns of the human behavior by using the Hidden Markov Model. First, the method finds foot area of the human by motion detection algorithm from image sequence of the surveillance camera. Then, these foot locus form observation series of features to learn the HMM. The feature that is position of the human foot is changed to each code that corresponds to a specific label among 16 local partitions of image region. Therefore, specific moving patterns formed by the foot locus are the series of the label numbers. The Baum-Welch algorithm of the HMM learns each suspicious and specific pattern to classify the human behaviors. To recognize the inputted human behavior pattern in a test image, the probabilistic comparison between the learned pattern of the HMM and foot series to be tested decides the categorization of the test pattern. The experimental results show that the method can be applied to detect a suspicious person prowling in corridor.