• Smart Media Journal
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• v.11 no.1
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• pp.17-30
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• 2022

Like other computer vision research trends, research using satellite images was able to achieve rapid growth with the development of GPU-based computer computing capabilities and deep learning methodologies related to image processing. As a result, satellite images are being used in various fields, and the number of studies on how to use satellite images is increasing. Therefore, in this paper, we will introduce the field of research and utilization of satellite images and datasets that can be used for research using satellite images. First, studies using satellite images were collected and classified according to the research method. It was largely classified into a Regression-based Approach and a Classification-based Approach, and the papers used by other methods were summarized. Next, the datasets used in studies using satellite images were summarized. This study proposes information on datasets and methods of use in research. In addition, it introduces how to organize and utilize domestic satellite image datasets that were recently opened by AI hub. In addition, I would like to briefly examine the limitations of satellite image-related research and future trends.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.580-586
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• 2023

AESA radar is able to instantaneously and adaptively position and control the beam, and this enables to greatly improve multi-target tracking capability with high accuracy in comparison to traditional mechanically-scanned radar system. This paper is primarily concerned with the development of an efficient methodology for multi-target managenent with the context of multi-target environment employing AESA radar. In this paper, targets are stratified into two principal categories: currently displayed targets and non-display targets, predicated upon their relative priority. Displayed targets are subsequently stratified into TOI (target of interest), HPT (high priority target), and SAT (situational awareness target), based on the requisite levels of tracking accuracy. It also suggests rules for determining target priority management, especially in air-to-air mode including interleaved mode. This proposed approach was tested and validated in a SIL (system integration lab) environment, applying it to AESA radars mounted on aircraft.

• Transactions on Semiconductor Engineering
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• v.2 no.1
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• pp.17-20
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• 2024

This paper presents a novel lightweight object detection model tailored for low-powered edge devices, addressing the limitations of traditional resource-intensive computer vision models. Our proposed detector, inspired by the Single Shot Detector (SSD), employs a compact yet robust network design. Crucially, it integrates an 'enhancer block' that significantly boosts its efficiency in detecting smaller objects. The model comprises two primary components: the Light_Block for efficient feature extraction using Depth-wise and Pointwise Convolution layers, and the Enhancer_Block for enhanced detection of tiny objects. Trained from scratch on the Udacity Annotated Dataset with image dimensions of 300x480, our model eschews the need for pre-trained classification weights. Weighing only 5.5MB with approximately 0.43M parameters, our detector achieved a mean average precision (mAP) of 27.7% and processed at 140 FPS, outperforming conventional models in both precision and efficiency. This research underscores the potential of lightweight designs in advancing object detection for edge devices without compromising accuracy.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.36-44
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• 2024

This paper presents the application of Convolutional Neural Networks (CNNs) and Region of Interest (ROI) techniques for concrete crack analysis. Surfaces of concrete structures, such as beams, etc., are exposed to fatigue stress and cyclic loads, typically resulting in the initiation of cracks at a microscopic level on the structure's surface. Early detection enables preventative measures to mitigate potential damage and failures. Conventional manual inspections often yield subpar results, especially for large-scale infrastructure where access is challenging and detecting cracks can be difficult. This paper presents data collection, edge segmentation and ROI techniques application, and analysis of concrete cracks using Convolutional Neural Networks. This paper aims to achieve the following objectives: Firstly, achieving improved accuracy in crack detection using image-based technology compared to traditional manual inspection methods. Secondly, developing an algorithm that utilizes enhanced Sobel edge segmentation and ROI techniques. The algorithm provides automated crack detection capabilities for non-destructive testing.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.144-159
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• 2014

Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.

• Journal of the Korean Applied Science and Technology
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• v.33 no.3
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• pp.549-559
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• 2016

Korean Black body fowl (Gallus gallus domesticus; Ogae) designated as a natural monument (registration number 265) has been known as a superb traditional Korean medicine. In this study, The production of peptide from the Viscera Waste of Yeonsan Ogae was optimized using commercial protease (bromelain) by response surface methodology under high pressure process. The range of processes was pressure (30 to 100 MPa), reaction time (1 to 5 h), and substrate concentration (10 to 30%, w/v). After reaction, the degree of hydrolysis, distribution of amino acids, and molecular weight of peptides were investigated. As a results, the optimization conditions were pressure 90 MPa, reaction time 3 to 4 h, and the amount of viscera meat 20% (w/v), respectively. The molecular weight of protein hydrolysates was distributed 400 to 1,000 Da. Accordingly we presumed that most products were peptides. Of those peptides, nonpolar or hydrophobic, polar but uncharged, positively charged, and negatively charged amino acids were 42.03, 26.0, 13.3, and 18.6%, respectively. Because higher amount of hydrophobic amino acids, we expected that those products would be able to utilize as the functional food ingredients.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.495-503
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• 2014

As the number of vehicles has been sharply increases, the significance of safety and effective operation issues in the parking lot is being emphasized, which takes a part of the transportation system. Recently, there have been several studies for the parking management by detecting moving object, however, recognizing numbers of fast-moving vehicles simultaneously in the picture is still a challenging problem. The parking lot in public area, or large-sized buildings has clear parking section, whereas the sensor system is configured to monitor a plurality of parking spaces. Therefore, by considering those parking lots, we suggested to develop the real-time parking availability information system by applying the real-time image processing techniques. with the help of template matching. Following the study, we wanted to provide the alternative method for parking management system through the reference template makers by recognizing movements of parked vehicles with the size and shape, regardless of direct detecting of driving movements. In addition, we evaluated the applicability and performances of the information system, presented in this study, and implemented a prototype system to simulate the parking statuses of each floor. In fat, it was possible to manage and analyze statistics about the total number of parking spaces and the number of vehicles parked through real-time video flames. We expected that the result of the study will be advanced, following the user-friendliness and cost reduction in operating parking management system and giving information by efficient analysis of parking situation.

• Journal of the Korean Society of Radiology
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• v.13 no.7
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• pp.955-960
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• 2019

The Computed tomography (CT) scan can have high radiation in a few tests, and this risk is significant given that it is often repeated in one patient. In children, the incidence of radiation-induced cancer is reported because organs are growing, are more sensitive to radiation. 3D printing has recently been studied to be applied to various applications as a research field for 3D printing applications, research on fabrication of radiation shields and materials has been conducted. The purpose of the 3D printer is to replace the existing panel-type shields and to make customized designs according to the shape of the human body. Therefore, research on 3D information processing to be input to the 3D printer is also necessary. In this study, 3D data of the human body surface, which is the preliminary step of the manufacture of patient-specific eye shield using stereo vision depth map technology, was studied. This study aims to increase the possibility of three-dimensional output. As a result of experimenting with this method, which is relatively simple compared with other methods of 3D information processing, the minimum coordinates for 3D information are extracted. The results of this study provided the advantages and limitations of stereo images using natural light and will be the basic data for the manufacture of eye shields in the future.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.245-254
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• 2002

IC package marking inspection system using machine vision locates and identifies the target elements from input image, and decides the quality of marking by comparing the extracted target elements with the standard patterns. This paper proposes an adaptive multi-level thresholding (AMLT) method which is suitable for a series of operations such as locating the target IC package, extracting the characters, and detecting the Pinl dimple. It also proposes a dynamic matching unit selection (DMUS) method which is robust to noises as well as effective to catch out the local marking errors. The main idea of the AMLT method is to restrict the inputs of Otsu's thresholding algorithm within a specified area and a partial range of gray values. Doing so, it can adapt to the specific domain. The DMUS method dynamically selects the matching unit according to the result of character extraction and layout analysis. Therefore, in spite of the various erroneous situation occurred in the process of character extraction and layout analysis, it can select minimal matching unit in any environment. In an experiment with 280 IC package images of eight types, the correct extracting rate of IC package and Pinl dimple was 100% and the correct decision rate of marking quality was 98.8%. This result shows that the proposed methods are effective to IC package marking inspection.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.101-109
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• 2014

It is an essential element for the establishment of image processing related systems to find the exact contour from the image of an arbitrary object. In particular, if a vision system is established to inspect the products in the automated production process, it is very important to detect the contours for standardized shapes such lines and curves. In this paper, we propose a prototype adaptive dynamic contour model, p-Snake with improved contour extraction algorithms by adding the prototype energy. The proposed method is to find the initial contour by applying the existing Snake algorithm after Sobel operation is performed for prototype analysis. Next, the final contour of the object is detected by analyzing prototypes such as lines and circles, defining prototype energy and using it as an additional energy item in the existing Snake function on the basis of information on initial contour. We performed experiments on 340 images obtained by using an environment that duplicated the background of an industrial site. It was found that even if objects are not clearly distinguished from the background due to noise and lighting or the edges being insufficiently visible in the images, the contour can be extracted. In addition, in the case of similarity which is the measure representing how much it matches the prototype, the prototype similarity of contour extracted from the proposed p-ACM is superior to that of ACM by 9.85%.