• Hwankyungkyoyuk
• /
• v.23 no.2
• /
• pp.97-112
• /
• 2010

The study aims to comprehend the effect of the wetland ecology education on the elementary school students' changes of recognition about wetland through the wetland ecology map program. In this study, the literary research, the experimental research and the survey methods were operated. Through the literary research, the environmental factors were extracted, and the writing item of ecology map was reconstructed based on the literary research, so the experimental research was operated with the wetland ecology map program. Through four areas of test items such as the information and knowledge, values and attitudes, development and conservation, behavior and participation, and the analysis of children's study results, the effect of the wetland ecology map program on changes of recognition about wetland was verified quantitatively and qualitatively. Wetland ecology map program would be able to be an educational approach which can achieve the 'personalization of environment' setting up predictable environmental improvement goals and satisfying the needs of spatial information of the appropriate regions from the holistic perspective that students themselves plan and participate beyond a one-time experience program. Production of ecological map through continuous monitoring is expected to improve the possibility of subjective environmental actions by operating self-directed learning. Based on the conclusion of this study, we would suggest the following. For wetland ecology map program to be supplemented and utilized, the basic education of wetland should be organized in regular school curriculum, ecology map program including various teaching learning methods be prepared actively, and in future studies, studies of ecosystem-wide wetland ecology map program including animals like birds and fish are necessary.

• Journal of Advanced Navigation Technology
• /
• v.11 no.3
• /
• pp.343-349
• /
• 2007

This paper addressed a recognition method of land registration map based on fuzzy inference scheme, which is able to solve the time complexity problem of typical method [Fig. 2]. Not only line color, thickness but also number, character are used as a fuzzy input parameter. It concentrated on generation of fuzzy association map, and useful informations are extracted result from fuzzy inference. These results are precedent process for estimating the construction space and restoring 3D automatic modeling. It can also utilize to the internet service acceleration propulsion business such as u-Gov based land registration service.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.22 no.6
• /
• pp.14-22
• /
• 2014

An autonomous vehicle requires a technology of generating maps by recognizing surrounding environment. The recognition of the vehicle's environment can be achieved by using distance information from a 2D laser scanner and color information from a camera. Such sensor information is used to generate 2D or 3D maps. A 2D map is used mostly for generating routs, because it contains information only about a section. In contrast, a 3D map involves height values also, and therefore can be used not only for generating routs but also for finding out vehicle accessible space. Nevertheless, an autonomous vehicle using 3D maps has difficulty in recognizing environment in real time. Accordingly, this paper proposes the technology for generating 2D maps that guarantee real-time recognition. The proposed technology uses only the color information obtained by removing height values from 3D maps generated based on the fusion of 2D laser scanner and camera data.

• Korean Journal of Human Ecology
• /
• v.7 no.1
• /
• pp.69-80
• /
• 2004

The purpose of this study is to suggest methods for the community design through users' behavior study in apartment housing. This study was approached by using both theoretical investigation and empirical research. The theoretical investigation actualized the concept of community design in apartment housing through a literature survey. The empirical survey focused on seeking out a user-oriented design criteria based on the analysis of residents' usage behavior and mental map. The results of this study are as follow: First. regarding the analysis of the residents' attitude toward the share community space(SCS), it was found that the SCS made a sense as community facilities in apartment housing. Second, regarding the SCS through the metal map, it was shown that the sketch map analysis was a useful research method for the community design by actualizing the residents' behavior characteristics. Third. as to the results of analyzing the metal map, it was found that the considered characteristics in recognition of the SCS were related to the liking with the main paths, cross nodes of the moving line, the location of center. and the complexity. In conclusion, the SCS is the main of community design in apartment housing and the above characteristics in recognition are useful as the guidelines in the SCS planning.

• The Journal of the Korea Contents Association
• /
• v.12 no.12
• /
• pp.63-70
• /
• 2012

In medical image processing field, object recognition is usually processed based on region segmentation algorithm. Region segmentation in the computing field is carried out by computerized processing of various input information such as brightness, shape, and pattern analysis. If the information mentioned does not make sense, however, many limitations could occur with region segmentation during computer processing. Therefore, this paper suggests effective region segmentation method based on R2-map information within the magnetic resonance (MR) theory. In this study, the experiment had been conducted using images including the liver region and by setting up feature points of R2-map as seed points for 2D region growing and final boundary correction to enable region segmentation even when the border line was not clear. As a result, an average area difference of 7.5%, which was higher than the accuracy of conventional exist region segmentation algorithm, was obtained.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.9C
• /
• pp.884-890
• /
• 2003

In this paper, we studied the speaker adaptation methods that improve the speaker independent recognition system. For the independent speakers, we compared the results between bigram and back-off bigram, MAP and MLLR. Cause back-off bigram applys unigram and back-off weighted value as bigram probability value, it has the effect adding little weighted value to bigram probability value. We did an experiment using total 39-feature vectors as featuring voice parameter with 12-MFCC, log energy and their delta and delta-delta parameter. For this recognition experiment, We constructed a system made by CHMM and tri-phones recognition unit and bigram and back-off bigrams language model.

• ETRI Journal
• /
• v.29 no.2
• /
• pp.243-245
• /
• 2007

This letter presents a new feature extraction method based on the private energy map (PEM) technique to utilize the energy characteristics of a facial image. Compared with a non-facial image, a facial image shows large energy congestion in special regions of discrete cosine transform (DCT) coefficients. The PEM is generated by energy probability of the DCT coefficients of facial images. In experiments, higher face recognition performance figures of 100% for the ORL database and 98.8% for the ETRI database have been achieved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.171-172
• /
• 2019

In this paper, we consider the dynamic method for the searching development of Web map to the monitoring object in the risk environments. It is to recognize the real-time detection to the risk situation based on the location monitoring mechanism of management to the object movement.

• International journal of advanced smart convergence
• /
• v.8 no.4
• /
• pp.104-112
• /
• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation forthe identification of a face shape. The proposed algorithm uses face shape asinput information in a single camera environment and divides only face area through preprocessing process. However, it is not easy to accurately recognize the face area that is sensitive to lighting changes and has a large degree of freedom, and the error range is large. In this paper, we separated the background and face area using the brightness difference of the two images to increase the recognition rate. The brightness difference between the two images means the difference between the images taken under the bright light and the images taken under the dark light. After separating only the face region, the face shape is recognized by using the self-organization feature map (SOFM) algorithm. SOFM first selects the first top neuron through the learning process. Second, the highest neuron is renewed by competing again between the highest neuron and neighboring neurons through the competition process. Third, the final top neuron is selected by repeating the learning process and the competition process. In addition, the competition will go through a three-step learning process to ensure that the top neurons are updated well among neurons. By using these SOFM neural network algorithms, we intend to implement a stable and robust real-time face shape recognition system in face shape recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.5
• /
• pp.1856-1869
• /
• 2015

This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.