• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.565-578
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• 2018

In this paper, we investigate the feasibility of modelling image strips, instead of individual scenes, that have been acquired from the same orbital pass through the process of bundle adjustments. Under this approach, First, a rational function model (RFM) of the strip image is generated from the RFMs of individual images, such that the entire strip of images can be treated as a single image. Correction parameters are calculated through bundle adjustments between strip images. For the experiment, we used two stereo strips. Each strip image consists of three KOMPSAT-3A scenes. Experimental results show that it was possible to improve the initial model by using the control points located in a specific region of the strip. We showed that absolute orientation with moderate accuracy of 2 m errors were achieved from 12 ground control points for the three-image strips. The test results indicate that bundle adjustment of strip images could be more efficient than bundle adjustments of the individual scenes.

• Journal of IKEEE
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• v.27 no.4
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• pp.610-616
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• 2023

In this paper, we implement an unmanned delivery robot system with Robot Operating System(ROS)-based mobile manipulator, and introduce the technologies employed for the system implementation. The robot consists of a mobile robot capable of autonomous navigation inside the building using an elevator and a Selective Compliance Assembly Robot Arm(SCARA)-Type manipulator equipped with a vacuum pump. The robot can determines the position and orientation for picking up a package through image segmentation and corner detection using the camera on the manipulator. The proposed system has a user interface implemented to check the delivery status and determine the real-time location of the robot through a web server linked to the application and ROS, and recognizes the shipment and address at the delivery station through You Only Look Once(YOLO) and Optical Character Recognition(OCR). The effectiveness of the system is validated through delivery experiments conducted within a 4-story building.

• Journal of the Korea Computer Graphics Society
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• v.7 no.2
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• pp.11-19
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• 2001

This paper proposes a colored paper mosaic rendering technique based on image segmentation that can automatically generate torn and tagged colored paper mosaic effect. and 3D effect that come about in human-made mosaic work can be represented by generating shadow using difference of paper thickness. Previous method did not produce satisfactory results due to the ineffectiveness of having to use pieces of the same size. The proposed two methods for determination of paper shape and location that are based on segmentation can subdivide image area by considering characteristics of image. The first method is to generate Voronoi polygon after subdividing the segmented image again using quad tree. And the second method is to apply the Voronoi diagram on each segmentation layer. Through these methods, the characteristic of the image is expressed in more detail than previous colored paper mosaic rendering method and these methods enable to produce image that is closer to human-made mosaic work.

• Journal of the Korea Computer Graphics Society
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• v.6 no.4
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• pp.1-7
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• 2000

Traditionally, three dimension model s have been used for building virtual worlds, and a data structure called the "scene graph" is often employed to organize these 3D objects in the virtual space. On the other hand, image-based rendering has recently been suggested as a probable alternative VR platform for its photo-realism, however, due to limited interactivity. it has only been used for simple navigation systems. To combine the merits of these two approaches to object/scene representations, this paper proposes for a scene graph structure in which both 3D models and various image-based scenes/objects can be defined. traversed, and rendered together. In fact, as suggested by Shade et al. [1]. these different representations can be used as different LOD's for a given object. For in stance, an object might be rendered using a 3D model at close range, a billboard at an intermediate range. and as part of an environment map at far range. The ultimate objective of this mixed platform is to breath more interactivity into the image based rendered VE's by employing 3D models as well. There are several technical challenges in devising such a platform : designing scene graph nodes for various types of image based techniques, establishing criteria for LOD/representation selection. handling their transition s. implementing appropriate interaction schemes. and correctly rendering the overall scene. Currently, we have extended the scene graph structure of the Sense8's WorldToolKit. to accommodate new node types for environment maps. billboards, moving textures and sprites, "Tour-into-the-Picture" structure, and view interpolated objects. As for choosing the right LOD level, the usual viewing distance and image space criteria are used, however, the switching between the image and 3D model occurs at a distance from the user where the user starts to perceive the object's internal depth. Also. during interaction, regardless of the viewing distance. a 3D representation would be used, if it exists. Finally. we carried out experiments to verify the theoretical derivation of the switching rule and obtained positive results.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.3
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• pp.220-228
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• 2001

Digital watermarking is a technique for the purpose of protecting the ownership of the image by embedding invisible watermarks in a digital imnge. To guarantee the security of the digital watermarking scheme for copyright protection, it is required to satisfy some requirements robustness and perceptual invisibility which provided by the location of embedded bits, the public watermarking algorithm, and the hidden use of the key, which can protect unauthorized accesses from illegal users. For this, in this paper we propose a new copyright watermarking scheme, which is based on one-way hash functions using RSA functions and modular operations. RSA functions are widely used in cryptographic systems. Our watermarking scheme is robust against LSB(Jeast significant bit) attacks and gamma corresction attack, and is also perceptually invisible. We demonstrate the characteristics of our proposed watermarking scheme through experiments.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.331-339
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• 2016

Chronic diseases are increasing nowadays as daily habits changed due to economic growth. Among chronic diseases, heart cerebrovascular disease is one of the major causes of death in South Korea that accounts for approximately 20% of mortality. Tests to measure anomaly of the heart is ECG tests, which measures and analyzes the electrical heart activity. Any mistakes in lead attachment location critically affects ECG testings, and statistical facts showed that only 2.8% of the nurses properly located leads to patients. As a solution, this paper proposes a system based on a projection-based augmented reality technology to generate X-ray images to the patient's chest to point out exact attachment locations of ECG leads. Evaluation comparison results showed a 2.6 cm difference between the conventional system and the proposed system. ECG test results also showed significant signal differences between the systems in leads V1, V2, and V3. The ECG measured accurately by the proposed system would help greatly in patient management and clinical decisions of clinicians.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.141-153
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• 2016

Reliable assessment of Land Use and Land Cover (LULC) changes greatly improves many practical issues in hydrography, socio-geographical research such as the observation of erosion and accretion, coastal monitoring, ecological effects evaluation. Remote sensing imageries can offer the outstanding capability to monitor nature and extent of land and associated changes over time. Nowadays accurate analysis using remote sensing imageries with high spatio-temporal resolution is required for environmental monitoring. This study develops a methodology of mapping and change detection in LULC by using classified Korea Multi-Purpose Satellite-2 (KOMPSAT-2) multispectral imageries at Jeonbuk and Jeonnam provinces including protected tidal flats located in the west coasts of Korean peninsula from 2008 to 2015. The LULC maps generated from unsupervised classification were analyzed and evaluated by post-classification change detection methods. The LULC assessment in Jeonbuk and Jeonnam areas had not showed significant changes over time although developed area was gradually increased only by 1.97% and 4.34% at both areas respectively. Overall, the results of this study quantify the land cover change patterns through pixel based analysis which demonstrate the potential of multispectral KOMPSAT-2 images to provide effective and economical LULC maps in the coastal zone over time. This LULC information would be of great interest to the environmental and policy mangers for the better coastal management and political decisions.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.

• Spatial Information Research
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• v.18 no.3
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• pp.73-83
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• 2010

This study presents a method to segment an image, employing the statistics observed at each pixel location across sequential frame images. In the acquisition and analysis of spatial information, utilization of digital image processing technique has very important implications. Various image segmentation techniques have been presented to distinguish the area of digital images. In this study, based on the analysis of the spectroscopic characteristics of sequential frame images that had been previously researched, an image segmentation method was proposed by using the randomness occurring among a sequence of frame images for a same scene. First of all, we computed the mean and standard deviation values at each pixel and found reliable pixels to determine seed points using their standard deviation value. For segmenting an image into individual regions, we conducted region growing based on a T-test between reference and candidate sample sets. A comparative analysis was conducted to assure the performance of the proposed method with reference to a previous method. From a set of experimental results, it is confirmed that the proposed method using a sequence of frame images segments a scene better than a method using a single frame image.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.173-182
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• 2021

In this paper, we analyzed driver's and passenger's motions that cause driver's distraction, and recognized 10 driver's behaviors related to mobile phones. First, distraction-inducing behaviors were classified into environments and factors, and related recent papers were analyzed. Based on the analyzed papers, 10 driver's behaviors related to cell phones, which are the main causes of distraction, were recognized. The experiment was conducted based on about 100,000 image data. Features were extracted through SURF and tested with three models (CNN, ResNet-101, and improved ResNet-101). The improved ResNet-101 model reduced training and validation errors by 8.2 times and 44.6 times compared to CNN, and the average precision and f1-score were maintained at a high level of 0.98. In addition, using CAM (class activation maps), it was reviewed whether the deep learning model used the cell phone object and location as the decisive cause when judging the driver's distraction behavior.