• Journal of the Korean Society of Industry Convergence
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• v.18 no.2
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• pp.129-138
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• 2015

This study describe a new method to control posture and velocity for a wheeled mobile robot using visual feedback control method with a position based visual feedback. To slove the problem of vibration phenomena which were shown in the previous researches using a simple switching function based on a threshold, the proposed visual servo control law introduces the fusion function based on a blending function. The chattering problem and rapid motion of the mobile robot can be eliminated. And we consider the nonlinearity of the wheeled mobile robot unlike the previous visual servo control laws using linear control methods to improve the performances of the visual servo control law. The proposed posture control law using visual servoing is verified by a theoretical analysis and simulation and experimental results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.2
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• pp.165-172
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• 2020

There is growing interest in Vision-based video image matching owing to the constantly developing technology of unmanned-based systems. The purpose of this paper is the development of a fast and effective matching technique for the UAV oblique video image. We first extracted initial matching points using NCC (Normalized Cross-Correlation) algorithm and improved the computational efficiency of NCC algorithm using integral image. Furthermore, we developed a triangulation-based outlier removal algorithm to extract more robust matching points among the initial matching points. In order to evaluate the performance of the propose method, our method was quantitatively compared with existing image matching approaches. Experimental results demonstrated that the proposed method can process 2.57 frames per second for video image matching and is up to 4 times faster than existing methods. The proposed method therefore has a good potential for the various video-based applications that requires image matching as a pre-processing.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.47 no.3
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• pp.214-221
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• 2011

This study was performed to develop a video based system which can be used to measure the averaged fish size in a non-intrusive fashion. The design was based on principles of simple stereo geometry, incorporated fish dimensions weight relationships and took into consideration fish movement to lower system costs. As the fish size is an important factor that impacts the economy of an aquaculture enterprise. Size measurements, including fork length, width or height, girth, thickness and mass, can be used to determine fish condition in the fish farm, so the averaged fish size of fish cage needs to consistently monitor in open ocean aquaculture cage. A precision of ${\pm}3%$ for replicate length measurements of a 60cm bar is obtained at distances between 2.0 and 6.0m, and the mean fork length and mean swimming speed of bluefin tuna were estimated to 48.8cm and 0.78FL/s, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6098-6104
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• 2012

Currently, dozens of CCTVs are widely used in railway station for monitoring passengers in danger and security areas. The most frequent accidents occur at the platform area where passengers boarding the train. However, It is almost impossible that station operator monitors dozens of CCTV screens and recognizes immediately accidents and handle them. Therefore, railway platform monitoring system using image processing technology which automatically detects platform accidents is needed, and in order to that, preferentially, accurate determination of train state in the platform is required. In the paper, we propose train state detection algorithm for vision based railway platform monitoring system. the proposed algorithm determines four different states i.e. trains approach(IN), departure(OUT), stop(ON), and empty(OFF) of the train, in the platform. To evaluate the proposed algorithm, we present the train detection results for the Seoul Metro Line 4 Dongjak and Namtaeryeong Station.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.20-25
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• 2021

The target-object classification method was implemented using a deep-learning-based detection model in real-time images. The object detection model was a deep-learning-based detection model that allowed extensive data collection and machine learning processes to classify similar target-objects. The recognition model was implemented by changing the processing structure of the detection model and combining developed the vision-processing module. To classify the target-objects, the identity and similarity were defined and applied to the detection model. The use of the recognition model in industry was also considered by verifying the effectiveness of the recognition model using the real-time images of an actual soccer game. The detection model and the newly constructed recognition model were compared and verified using real-time images. Furthermore, research was conducted to optimize the recognition model in a real-time environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.463-465
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• 2021

Currently, the inspection method printed on food packages and boxes is to sample only a few products and inspect them with human eyes. Such a sampling inspection has the limitation that only a small number of products can be inspected. Therefore, accurate inspection using a camera is required. This paper proposes a deep learning object recognition technology model, which is an artificial intelligence technology, as a method for detecting the defects of expiration date printed on the product packaging. Using the Faster R-CNN (region convolution neural network) model, the color images, converted gray images, and converted binary images of the printed expiration date are trained and then tested, and each detection rates are compared. The detection performance of expiration date printed on the package by the proposed method showed the same detection performance as that of conventional vision-based inspection system.

• Computers and Concrete
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• v.33 no.5
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• pp.535-544
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• 2024

In the rapidly advancing landscape of computer vision (CV) technology, there is a burgeoning interest in its integration with the construction industry. Camera calibration is the process of deriving intrinsic and extrinsic parameters that affect when the coordinates of the 3D real world are projected onto the 2D plane, where the intrinsic parameters are internal factors of the camera, and extrinsic parameters are external factors such as the position and rotation of the camera. Camera pose estimation or extrinsic calibration, which estimates extrinsic parameters, is essential information for CV application at construction since it can be used for indoor navigation of construction robots and field monitoring by restoring depth information. Traditionally, camera pose estimation methods for cameras relied on target objects such as markers or patterns. However, these methods, which are marker- or pattern-based, are often time-consuming due to the requirement of installing a target object for estimation. As a solution to this challenge, this study introduces a novel framework that facilitates camera pose estimation using standardized materials found commonly in construction sites, such as concrete forms. The proposed framework obtains 3D real-world coordinates by referring to construction materials with certain specifications, extracts the 2D coordinates of the corresponding image plane through keypoint detection, and derives the camera's coordinate through the perspective-n-point (PnP) method which derives the extrinsic parameters by matching 3D and 2D coordinate pairs. This framework presents a substantial advancement as it streamlines the extrinsic calibration process, thereby potentially enhancing the efficiency of CV technology application and data collection at construction sites. This approach holds promise for expediting and optimizing various construction-related tasks by automating and simplifying the calibration procedure.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.1
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• pp.33-38
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• 2024

The importance of connected technology that connects products or systems is increasing. Connected technology is a concept that can communicate with surrounding objects and connect to each other through a network to operate as one system. In particular, it can be implemented using wireless communication, and various conditions are required depending on the application system, such as communication distance and speed. In this study, we analyzed trends in communication technology for the implementation of connectivity between mobility devices such as self-driving cars, drones, UAVs, and shared mobility devices. The communication distance, speed, wired and wireless status, etc. of the latest communication methods currently commercialized or under development were investigated, with a particular focus on low-power operation. We identified the element technologies needed to build a low-power long-distance communication (LPWAN) system, and initially developed a plan for constructing a connected drone. The analysis results showed that it was possible to implement a connected system using the LoRa system, and an example configuration method was presented.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.411-425
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• 2023

Today, AI (Artificial Intelligence) technology is widely used in various fields, performing classification and regression tasks according to the purpose of use, and research is also actively progressing. Especially in the field of security, unexpected threats need to be detected, and unsupervised learning-based anomaly detection techniques that can detect threats without adding known threat information to the model training process are promising methods. However, most of the preceding studies that provide interpretability for AI judgments are designed for supervised learning, so it is difficult to apply them to unsupervised learning models with fundamentally different learning methods. In addition, previously researched vision-centered AI mechanism interpretation studies are not suitable for application to the security field that is not expressed in images. Therefore, In this paper, we use a technique that provides interpretability for detected anomalies by searching for and comparing optimization references, which are the source of intrusion attacks. In this paper, based on reference, we propose additional logic to search for data closest to real data. Based on real data, it aims to provide a more intuitive interpretation of anomalies and to promote effective use of an anomaly detection model in the security field.

• Journal of Information Technology Services
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• v.5 no.1
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• pp.111-128
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• 2006

It was on the rise importantly to provide the efficient management process of the organization for dealing with the change about information and business management quickly and consistently. It was suggested with the architectural model on information technology to provide it in theoretically. The Federal Government and budget organization of the USA used it on actual business and the terms of EA (Enterprise Architecture) and are raising the efficiency of management. NCA (National Computerization Agency) of Korea published the book - "The Research about establishing ITA (Information Technology Architecture) and appling the standards". After being applied the model on MOGAHA (Ministry of Government Administration and Home Affairs) and MIC(Minisstry of Information and Communication), the concrete case was made. MOMAF (Ministry of Maritime Affairs and Fisheries) drove the leading model. The report ascertained the basic contents of ITA and researched the case of USA, MOGAHA, MIC, and tried to analyze the contents of appling maritime and fisheries area. The report contained the definition of purpose through analyzing environment and establishing the vision and the principles based on them. The report also contained the contents of architecture based on the standard of NCA - "The Government Standard Meta Model version 2.0" - and researched the MOMAF's Reference model using Government Reference model. The report established the investment architecture and the process of information technology asset management. It ascertained the characteristic of maritime & fisheries area and the subject of developing the MOMAF's ITA sustainably.