• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.300-306
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• 2000

This paper introduces a new concept of automation for bio-production with tele-operative system. The proposed system showed practical and feasible way of automation for the volatile bio-production process. Based on the proposition, recognition of the job environment with object identification was performed using computer vision system. A man-machine interactive hybrid decision-making, which utilized a concept of tele-operation was proposed to overcome limitations of the capability of computer in image processing and feature extraction from the complex environment image. Identifying watermelons from the outdoor scene of the cultivation field was selected to realize the proposed concept. Identifying watermelon from the camera image of the outdoor cultivation field is very difficult because of the ambiguity among stems, leaves, shades, and especially fruits covered partly by leaves or stems. The analog signal of the outdoor image was captured and transmitted wireless to the host computer by R.F module. The localized window was formed from the outdoor image by pointing to the touch screen. And then a sequence of algorithms to identify the location and size of the watermelon was performed with the local window image. The effect of the light reflectance of fruits, stems, ground, and leaves were also investigated.

• The Journal of Korean Physical Therapy
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• v.14 no.4
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• pp.423-440
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• 2002

The purpose of this study is to investigate the conception and developmental process of stretching in sports physical therapy. This study is to find conception of stretching, feature and effect, principles and fundamental rule, consideration of enforcement and developmental process in order to use the basic material which is very helpful in the every field and the scene of sports needing stretching. Flexibility is the ability to move muscles and joints through their full ranges of motion. Flexibility is developed by stretching. About player who insufficiency of flexibility, patient and disabled person who restrict of range of motion, older adult who reduce of flexibility, promote of flexibility for upgrading stability and efficiency of body on the based of scientific principles is completed by stretching. The method of stretching has been developed with passive stretching, CR, PNF stretching, PIC stretching, MET stretching in the order. The effects that we can get through stretching are as follows : 1. Enhance physical fitness. 2. Optimize learning, practice and performance of many types of skilled movement. 3. Increase mental and physical relaxation. 4. Promote development of body awareness. 5. Reduce risk of joint sprain or muscle strain. 6. Reduce risk of back problem. 7 Reduce muscular soreness. 8. Reduce the severity of painful menstruation for female athletes. 9. Reduce muscular tension. 10. Advance recognition of body.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.490-498
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• 2011

In this paper, we present a two-stage vision-based approach to detect multi views of pedestrian in road scene images. The first stage is HG (Hypothesis Generation), in which potential pedestrian are hypothesized. During the hypothesis generation step, we use a vertical, horizontal edge map, and different colors between road background and pedestrian's clothes to determine the leg position of pedestrian, then a novel symmetry peaks processing is performed to define how many pedestrians is covered in one potential candidate region. Finally, the real candidate region where pedestrian exists will be constructed. The second stage is HV (Hypothesis Verification). In this stage, all hypotheses are verified by Support Vector Machine for classification, which is robust for multi views of pedestrian detection and recognition problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1167-1174
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• 2006

Text region detection from a natural scene is useful in many applications such as vehicle license plate recognition. Therefore, in this paper, we propose a text region extraction method using pattern histogram of character-edge maps. We create 16 kinds of edge maps from the extracted edges and then, we create the 8 kinds of edge maps which compound 16 kinds of edge maps, and have a character feature. We extract a candidate of text regions using the 8 kinds of character-edge maps. The verification about candidate of text region used pattern histogram of character-edge maps and structural features of text region. Experimental results show that the proposed method extracts a text regions composed of complex background, various font sizes and font colors effectively.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1225-1235
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• 2016

This paper presents a method for computer-assisted slide presentation using vision-based gesture recognition. The proposed method consists of a sequence of steps, first detecting a hand in the scene of projector beam, then estimating the smooth trajectory of a hand or a pointing finger using Kalman Filter, and finally interfacing to an application system. Additional slide navigation control includes moving back and forth the pages of the presentation. The proposed method is to help speakers for an effective presentation with natural improved interaction with the computer. In particular, the proposed method of using finger pointing is believed to be more effective than using a laser pointer since the hand, the pointing or finger are more visible and thus can better grab the attention of the audience.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.319-334
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• 2001

Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.73-78
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• 2022

The aim of this paper is to investigate the prevalence of Deep Learning in the literature on Fire & Rescue Service. It is found that deep learning techniques are only beginning to benefit the firefighters. The popular areas where deep learning techniques are making an impact are situational awareness, decision making, mental stress, injuries, well-being of the firefighter such as his sudden fall, inability to move and breathlessness, path planning by the firefighters while getting to an fire scene, wayfinding, tracking firefighters, firefighter physical fitness, employment, prediction of firefighter intervention, firefighter operations such as object recognition in smoky areas, firefighter efficacy, smart firefighting using edge computing, firefighting in teams, and firefighter clothing and safety. The techniques that were found applied in firefighting were Deep learning, Traditional K-Means clustering with engineered time and frequency domain features, Convolutional autoencoders, Long Short-Term Memory (LSTM), Deep Neural Networks, Simulation, VR, ANN, Deep Q Learning, Deep learning based on conditional generative adversarial networks, Decision Trees, Kalman Filters, Computational models, Partial Least Squares, Logistic Regression, Random Forest, Edge computing, C5 Decision Tree, Restricted Boltzmann Machine, Reinforcement Learning, and Recurrent LSTM. The literature review is centered on Firefighters/firemen not involved in wildland fires. The focus was also not on the fire itself. It must also be noted that several deep learning techniques such as CNN were mostly used in fire behavior, fire imaging and identification as well. Those papers that deal with fire behavior were also not part of this literature review.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_1
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• pp.217-223
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• 2023

With the rapid advancement of technologies, need for different research fields where this technology can be used is also increasing. One of the most researched topic in computer vision is object detection, which has widely been implemented in various fields which include healthcare, video surveillance and education. The main goal of object detection is to identify and categorize all the objects in a target environment. Specifically, methods of object detection consist of a variety of significant techniq ues, such as image processing and patterns recognition. Anomaly detection is a part of object detection, anomalies can be found various scenarios for example crowded places such as subway stations. An abnormal event can be assumed as a variation from the conventional scene. Since the abnormal event does not occur frequently, the distribution of normal and abnormal events is thoroughly imbalanced. In terms of public safety, abnormal events should be avoided and therefore immediate action need to be taken. When abnormal events occur in certain places, real time detection is required to prevent and protect the safety of the people. To solve the above problems, we propose a modified YOLOv5 object detection algorithm by implementing dilated convolutional layers which achieved 97% mAP50 compared to other five different models of YOLOv5. In addition to this, we also created a simple mobile application to avail the abnormal event detection on mobile phones.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.201-211
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• 2013

In this paper, we propose a hand tracking and gesture recognition system. Our system employs a depth capture device to obtain 3D geometric information of user's bare hand. In particular, we build a flexible tracking volume and restrict the hand tracking area, so that we can avoid diverse problems caused by conventional object detection/tracking systems. The proposed system computes running average of the hand position, and tracking volume is actively adjusted according to the statistical information that is computed on the basis of uncertainty of the user's hand motion in the 3D space. Once the position of user's hand is obtained, then the system attempts to detect stretched fingers to recognize finger gesture of the user's hand. In order to test the proposed framework, we built a NUI system using the proposed technique, and verified that our system presents very stable performance even in the case that multiple objects exist simultaneously in the crowded environment, as well as in the situation that the scene is occluded temporarily. We also verified that our system ensures running speed of 24-30 frames per second throughout the experiments.

• Cartoon and Animation Studies
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• s.26
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• pp.31-56
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• 2012

This is a scientific study of subjectivity on recognition types and preferences of animation audience. Therefore, Q-methodology was used as a methodology of this study. As a result, it was possible to find the various characteristics according to the preferences of audience on animation genres. The features of each type were classified into 3 types. First was an artistic and literary value-oriented type that explored storytelling and descriptive value. Second was a pictorial and aesthetic value-oriented type that explored visual beauty such as characters and Mise en scene. Third was a visual and entertainment value-oriented type that explored entertainment factors and attractions. Thus, according to the classification of preference types, it was inferred that digital image generation audience with an active preference that can create and consume images have developed a tendency that independently consumed their preferences based on thoroughly personal or subjective preferences rather than classified and accepted their preferred culture as their symbolic expressions of hierarchical position. In this aspect, Q-methodological consideration that is useful to analyze the subjectivity of audience could be a significant work. Nevertheless, this study alone could not reveal various generative contexts of specific preferences. It seems to have more significant results by applying various qualitative or quantitative methodologies together with this study and analyzing recognition types and preferences of audience.