• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.177-186
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• 2012

In this paper, we propose a real-time approach for detecting and tracking a hand region by analyzing depth images. We build a hand model in advance. The model has the shape information of a hand. The detecting process extracts out moving areas in an image, which are possibly caused by moving a hand in front of a camera. The moving areas can be identified by analyzing accumulated difference images and applying the region growing technique. The extracted moving areas are compared against a hand model to get justified as a hand region. The tracking process keeps the track of center points of hand regions of successive frames. For this purpose, it involves three steps. The first step is to determine a seed point that is the closest point to the center point of a previous frame. The second step is to perform region growing to form a candidate region of a hand. The third step is to determine the center point of a hand to be tracked. This point is searched by the mean-shift algorithm within a confined area whose size varies adaptively according to the depth information. To verify the effectiveness of our approach, we have evaluated the performance of our approach while changing the shape and position of a hand as well as the velocity of hand movement.

• Journal of Biosystems Engineering
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• v.42 no.2
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• pp.117-125
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• 2017

Purpose: Damage to pulse crops by wild birds is a serious problem. The damage is to such an extent that the rate of damage during the period between seeding and cotyledon stages reaches 54.6% on an average. In this study, a crop-position detection method was developed wherein infrared (IR) sensors were used to determine the cotyledon position under a vinyl mulch. Methods: IR sensors that helped measure the temperature were used to locate the cotyledons below the vinyl mulch. A single IR sensor module was installed at three locations of the crops (peanut, red lettuce, and crown daisy) in the cotyledon stage. The representative thermal response of a $16{\times}4$ pixel area was detected using this sensor in the case where the distance from the target was 25 cm. A spatial image was applied to the two-dimensional temperature distribution using a non-integral moving-average method. The collected data were first processed by taking the moving average via interpolation to determine the frame where the variance was the lowest for a resolution unit of 1.02 cm. Results: The temperature distribution was plotted corresponding to a distance of 10 cm between the crops. A clear leaf pattern of the crop was visually confirmed. However, the temperature distribution after the normalization was unclear. The image conversion and frequency-conversion graphs were obtained based on the moving average by averaging the points corresponding to a frequency of 40 Hz for 8 pixels. The most optimized resolutions at locations 1, 2, and 3 were found on 3.4, 4.1, and 5.6 Pixels, respectively. Conclusions: In this study, to solve the problem of damage caused by birds to crops in the cotyledon stage after seeding, the vinyl mulch is punched after seeding. The crops in the cotyledon stage could be accurately located using the proposed method. By conducting the experiments using the single IR sensor and a sliding mechanical device with the help of a non-integral interpolation method, the crops in the cotyledon stage could be precisely located.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.111-121
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• 2011

Intelligent video analysis systems require techniques which can predict accidents and provide alarms to the monitoring personnel. In this paper, we present an abnormal behavior analysis technique based on adaptive background generation. More specifically, abnormal behaviors include fence climbing, abandoned objects, fainting persons, and loitering persons. The proposed video analysis system consists of (i) background generation and (ii) abnormal behavior analysis modules. For robust background generation, the proposed system updates static regions by detecting motion changes at each frame. In addition, noise and shadow removal steps are also were added to improve the accuracy of the object detection. The abnormal behavior analysis module extracts object information, such as centroid, silhouette, size, and trajectory. As the result of the behavior analysis function objects' behavior is configured and analyzed based on the a priori specified scenarios, such as fence climbing, abandoning objects, fainting, and loitering. In the experimental results, the proposed system was able to detect the moving object and analyze the abnormal behavior in complex environments.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.39-46
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• 2007

Research on human identification in ubiquitous environment has recently attracted a lot of attention. As one of those research, gait recognition is an efficient method of human identification using physical features of a walking person at a distance. In this paper, we present a human shape extraction and tracking for gait recognition using geodesic active contour models(GACMs) combined with mean shift algorithm The active contour models (ACMs) are very effective to deal with the non-rigid object because of its elastic property. However, they have the limitation that their performance is mainly dependent on the initial curve. To overcome this problem, we combine the mean shift algorithm with the traditional GACMs. The main idea is very simple. Before evolving using level set method, the initial curve in each frame is re-localized near the human region and is resized enough to include the targe region. This mechanism allows for reducing the number of iterations and for handling the large object motion. The proposed system is composed of human region detection and human shape tracking modules. In the human region detection module, the silhouette of a walking person is extracted by background subtraction and morphologic operation. Then human shape are correctly obtained by the GACMs with mean shift algorithm. In experimental results, the proposed method show that it is extracted and tracked efficiently accurate shape for gait recognition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2427-2432
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• 2014

Color-$X^2$ is used as a method for scene change detection. It extracts a violent scene in an elevator and then could be used for real-time surveillance of criminal acts. The scene could be also used to secure after-discovered evidences and to prove analysis processes. Video Forensic is defined as a research on various methods to efficiently analyze evidences upon crime-related visual images in the field of digital forensic. The method to use differences of color-histogram detects the difference values of histogram for RGB color from two frames respectively. Our paper uses Color-$X^2$ histogram that is composed of merits of color histogram and ones of $X^2$ histogram, in order to efficiently extract violent scenes in elevator. Also, we use a threshold so as to find out key frame, by use of existing Color-$X^2$ histogram. To increase the probability that discerns whether a real violent scene or not, we take advantage of statistical judgments with 20 sample visual images.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.205-218
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• 2022

Recently, digital transformation in manufacturing has been accelerating. It results in that the data collection technologies from the shop-floor is becoming important. These approaches focus primarily on obtaining specific manufacturing data using various sensors and communication technologies. In order to expand the channel of field data collection, this study proposes a method to automatically collect manufacturing data based on vision-based artificial intelligence. This is to analyze real-time image information with the object detection and tracking technologies and to obtain manufacturing data. The research team collects object motion information for each frame by applying YOLO (You Only Look Once) and DeepSORT as object detection and tracking algorithms. Thereafter, the motion information is converted into two pieces of manufacturing data (production performance and time) through post-processing. A dynamically moving factory model is created to obtain training data for deep learning. In addition, operating scenarios are proposed to reproduce the shop-floor situation in the real world. The operating scenario assumes a flow-shop consisting of six facilities. As a result of collecting manufacturing data according to the operating scenarios, the accuracy was 96.3%.

• Journal of the Korean housing association
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• v.26 no.2
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• pp.39-46
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• 2015

The 'pathways' in the Deteriorated Residential Area is the valuable place which represents the history of the community. The 'pathways' is the physical boundary which connects individual environment of private residential area to public environment and which has value as a medium for the definite site for regeneration of Deteriorated Residential Area. Thus, the 'pathways' is considered as the perfect material for the public design for spatial culture to regenerate the Deteriorated Residential Area. However, the most of the public design projects utilize the 'pathways' fragmentarily, there are few systematic studies based on the attribute of the Deteriorated Residential Area. The purpose of this study is the consideration on the attributes of the 'pathways', the detection of the spatial characteristics to find application of the 'pathways', and the cultivation of the baseline data for further research for the spatial nature of the Deteriorated Residential Area. For this study, theoretical consideration is practiced in advance to analyze the meaning of the 'pathways' and Deteriorated Residential Area, the case research is performed using design elements as the analytic frame, and the approach is inferred for systematic public design based on the above result. The objects of case research were chosen among the latest projects implemented in the Deteriorated Residential Area whose subject was 'pathways' and which showed successful result. The characteristics of them were investigated and the details were examined through the homepages of the projects, the reports related to the projects, research material, and interview with the people involved. And to conclude, 'pathways' represents the composition of contents, the space of movement, the formation of community, the landscape design, and the participatory design in the Deteriorated Residential Area. The 'pathways' also finds the proper secondary cultural material for the spatial characteristics and can create the space for the various movements, stay, and communication using the characteristics of movements. The narrow and closed space should be utilized actively to be altered into beautiful space and the Deteriorated Residential Area should be regenerated into coexistent design where people share their lives through sharing spaces.

• School Mathematics
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• v.17 no.2
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• pp.273-287
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• 2015

The purpose of this study was to obtain a deeper understanding of didactic processing in the class that unified with engineering by analyzing on the types of the teacher's instumental orchestration and schematizing it as an activity system. In order to do so, a qualitative study of a 5th grade class for math-gifted students in Y elementary school with ethnography was conducted. Interviews with the students were held and various document data were collected during the participational observation of the class. The collected qualitative data were gone through the analytical induction while the instrumental orchestration of Drijvers, Boon, Doorman, Reed, & Gravemeijer as well as the secondgeneration activity theory of Engestrom were using as the frame of conceptional reference. According to the result of this study, there exist 4 types, such as 'technical demo' 'link screen board', 'detection-exploring small group' and 'explain the screen and technical demo'.

• The Journal of the Acoustical Society of Korea
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• v.32 no.1
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• pp.71-78
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• 2013

This paper describes a multiple audio watermarking using Quantization Index Modulation (QIM) on frequency phase and magnitude response. Proposed embedding procedure is composed of two stage. At the first stage, the watermark is embedded on the frequency phase response using QIM. In the second stage, the watermark is embedded using adaptive QIM with the step-size that is adaptively determined using the maximum value of the frequency magnitude response of every frame. The watermark is extracted by calculating the Euclidean distance as the blind detection. The proposed method is robust against most of attacks of audio watermark benchmarking. For the Fourier attacks, the proposed method shows over 95% recovery rate.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.3
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• pp.193-199
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• 2020

This study examines a method for identifying stiffness reductions in structures subjected to seismic loads and retrofitting effects using a combination of the finite element method and an advanced genetic algorithm. The novelty of this study is the application of seismic loading and its response to anomalies in the tested structure. The technique described in this study may enable not only detection of damaged elements but also the identification of their locations and the extent of damage due to seismic loading. To demonstrate the feasibility of the method, the advanced genetic algorithm is applied to frame and truss bridge structures subjected to El Centro and Pohang seismic loads. The results reveal the excellent computational efficiency of the method and its ability to prevent severe damage from earthquakes.