• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.12
• /
• pp.1122-1129
• /
• 2015

This paper suggests a method of detecting traffic lights for vehicles by combining the HSV(hue saturation value) color model, morphometric characteristics, and location information appearing on consecutive images in daytime. In order to detect the traffic light, the color corresponding to the signal lights should be explored. It is difficult to detect traffic lights among colors of lights from buildings, taillight of cars, leaves, placards, etc. The proposed algorithm searches for the traffic lights from many candidates using morphometric characteristics and location information in consecutive images. The recognition process is divided into three steps. The first step is to detect candidates after converting RGB channel into HSV color model. The second step is to extract the boundaries between the housing of traffic lights and background by exploiting the assumption that the housing has lower brightness than the surrounding background. The last step is to recognize the signal light after eliminating the false candidates using morphometric characteristics and location information appearing on consecutive images. This paper demonstrates successful detection results of traffic lights from various images captured on the city roads.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• autumn
• /
• pp.91-96
• /
• 2002

Research and case study on implementing Knowledge Management (KM) in various fields have been published. However, KM could be misunderstood as developed Information Technology (IT) rather than a managerial tool to support knowledge creation in an organization unless the theoretical background on the evolution of KM is rigorously considered. This paper aims to review philosophy of science and managerial trends that can explain the reasons for introducing KM into the industry. Based on this theoretical background, Soft Systems Method (SSM), one of method to facilitate knowledge flows, are explained. SSM has been developed to cope with the characteristics of knowledge distinguished from data and information. Further research topics relevant to SSM in construction management as a practical application and educational tool are presented.

• Proceedings of the KOSOMBE Conference
• /
• v.1998 no.11
• /
• pp.96-97
• /
• 1998

3D TOF MR Angiography is able to obtain thinner slice thickness, higher SNR, therefore higher spatial resolution than 2D TOF MR Angiography. Since it uses longer TR than 2D TOF MRA to allow stronger in-flow effect, the background tissue may not be fully saturated. Thus background tissue signal can be further suppressed by MTS(Magnetization Transfer Saturation). Flow-compensation was accomplished by GMN(Gradient Moment Nulling), and tracking saturation was used to suppress vein signal. The different flow signal at the entry of the slab and output of the slab can be compensated by TONE(Tilted Optimized Non-saturating Excitation) RF pulse.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.8
• /
• pp.21-28
• /
• 2016

In this paper, we propose a fast small target detection method using multiple filters, and describe system implementation using IPP libraries. To detect small targets in Infra-Red images, it is mandatory that you should apply a filter to eliminate a background and identify the target information. Moreover, by using a suitable algorithm for the environments and characteristics of the target, the filter must remove the background information while maintaining the target information as possible. For this reason, in the proposed method we have detected small targets by applying multi area(spatial) filters in a low luminous environment. In order to apply the multi spatial filters, the computation time can be increased exponentially in case of the sequential operation. To build this algorithm in real-time systems, we have applied IPP library to secure a software optimization and reduce the computation time. As a result of applying real environments, we have confirmed a detection rate more than 90%, also the computation time of the proposed algorithm have been improved about 90% than a typical sequential computation time.

• Archives of design research
• /
• v.16 no.3
• /
• pp.273-280
• /
• 2003

Priming Effect, as a part of "Contextual Effect" is the phenomenon that pre-searched product information influences consecutive product evaluation. "Priming Effect" is different from other types of "Contextual Effects" in that pre-searched information doesn't have an direct effect on product evaluation, but an indirect effect which means that pre-searched information influences interpretation of consecutive product evaluation. On the previous theoretical background, this study investigated that how visual images can influence consumer preference and product choice, introducing concept of priming effects into the design of on-line shopping malls. This experiment adopted the digital cameras as the experimental stimulus target products and designed the individual web pages by priming the attributes of price and size. In result of analysis, the difference of product preference by priming attributes was proved to be statistically significant. In this reason, suggesting the background of commercial web page can be the significant factor in choosing products, the priming effects introduced into the design can be positively employed in online advertising.mployed in online advertising.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.5
• /
• pp.1080-1088
• /
• 2004

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera against variance of intensity, shape and background is proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are segmented to 24 levels from $0^{\circ}$ to $360^{\circ}$. It is used to the feature parameter of the moving objects that are three segmented hue levels with the highest distribution and difference among three segmented hue levels. To examine propriety of the proposed method, human images with variance of intensity and shape and human images with variance of intensity, shape and background are targeted for moving objects. As surveillance results of the interesting human, hue distribution level variation of the detected interesting human at each camera is under 2 level, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at cameras, automatically.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.3
• /
• pp.552-557
• /
• 2015

IT technology development and smart appliances due to the increased use of a lot of data on production and consumption has become in the internet. Because this is why importance of information retrieval technology although the growing becoming aware of the difficult techniques to access the required of lot a background knowledge on information retrieval technology. However, the Lucene due to emerge provide to background can implement on search engine by using the Lucene of lack background knowledge for search technology. In this paper, suggest to implement on search engine by using the developed a framework on Lucene-based. Suggest a frameworks are use in the search engines on have guarantee in server environment support on distributed processing and distributed storage, and high availability by using the Hadoop and Nutch, Solr, Zookeeper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.05a
• /
• pp.571-575
• /
• 2015

This paper propose a temporal histogram -based behavior pattern analysis algorithm to analyze the movement features of moving objects from the image inputted in real-time. For the purpose of tracking and analysis of moving objects, it needs to be performed background learning which separated moving objects from the background. Moving object is extracted as a background learning after identifying the object by using the center of gravity and the coordinate correlation is performed by the object tracking. The start frame of each of the tracked object, the end frame, the coordinates information and size information are stored and managed by the linked list. Temporal histogram defines movement features pattern using x, y coordinates based on time axis, it compares each coordinates of objects for understanding its movement features and behavior pattern. Behavior pattern analysis system based on temporal histogram confirmed high tracking rate over 95% with sustaining high processing speed 45~50fps through the demo experiment.

• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.3
• /
• pp.159-164
• /
• 2019

Detecting wildfire using only color in image information is a very difficult issue. This paper proposes an algorithm to detect forest fire area by analyzing color and motion of the area in the video including forest fire. The proposed algorithm removes the background region using the Gaussian Mixture based background segmentation algorithm, which does not depend on the lighting conditions. In addition, the RGB channel is changed to an HSV channel to extract flame candidates based on color. The extracted flame candidates judge that it is not a flame if the area moves while labeling and tracking. If the flame candidate areas extracted in this way are in the same position for more than 2 minutes, it is regarded as flame. Experimental results using the implemented algorithm confirmed the validity.

• Journal of the Korea Convergence Society
• /
• v.9 no.12
• /
• pp.33-38
• /
• 2018

Recently, we are trying to predict the emotion from various information and to convey the emotion information that the supervisor wants to inform the audience. In addition, audiences intend to understand the flow of emotions through various information of non-dialogue parts, such as cinematography, scene background, background sound and so on. In this paper, we propose to extract emotions by mixing not only the context of scripts but also the cinematography information such as color, background sound, composition, arrangement and so on. In other words, we propose an emotional prediction system that learns and distinguishes various emotional expression techniques into dialogue and non-dialogue regions, contributes to the completeness of the movie, and quickly applies them to new changes. The precision of the proposed system is improved by about 5.1% and 0.4%, and the recall is improved by about 4.3% and 1.6%, respectively, when compared with the modified n-gram and morphological analysis.