• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.8
• /
• pp.3551-3567
• /
• 2016

The Low Earth Orbit satellite network has the unique characteristics of the non-uniform and time-variant traffic load distribution, which often causes severe link congestion and thus results in poor performance for delay-sensitive flows, especially when the network is heavily loaded. To solve this problem, a novel adaptive routing algorithm, referred to as the delay-oriented adaptive routing algorithm (DOAR), is proposed. Different from current reactive schemes, DOAR employs Destination-Sequenced Distance-Vector (DSDV) routing algorithm, which is a proactive scheme. DSDV is extended to a multipath QoS version to generate alternative routes in active with real-time delay metric, which leads to two significant advantages. First, the flows can be timely and accurately detected for route adjustment. Second, it enables fast, flexible, and optimized QoS matching between the alternative routes and adjustment requiring flows and meanwhile avoids delay growth caused by increased hop number and diffused congestion range. In addition, a retrospective route adjustment requesting scheme is designed in DOAR to enlarge the alternative routes set in the severe congestion state in a large area. Simulation result suggests that DOAR performs better than typical adaptive routing algorithms in terms of the throughput and the delay in a variety of traffic intensity.

• Journal of KIISE
• /
• v.44 no.2
• /
• pp.186-194
• /
• 2017

Depth-image-based rendering is a technique that can be applied in a variety of 3D-display systems. It generates the images that have been captured from virtual viewpoints by using a depth map. However, disoccluded hole-filling problems remain a challenging issue, as a newly exposed area appears in the virtual view. Image inpainting is a popular approach for the filling of the hole region. This paper presents a robust hole-filling method that reduces the error and generates a high quality-virtual view. First, the adaptive-patch size is decided using the color and depth information. Also, a partial filling method for which the patch similarity is used is proposed. These efforts reduce the error occurrence and the propagation. The experiment results show that the proposed method synthesizes the virtual view with a higher visual comfort compared with the existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.7
• /
• pp.1583-1590
• /
• 2011

As the existing radiation scanning systems use 2-dimensional radiation scanned images, the low accuracy has been pointed out as a problem of it. This research analyzes the applicability of the stereo image processing technique to X-ray scanned images. Two 2-dimensional radiation images which have different disparity values are acquired from a newly designed stereo image acquisition system which has one additional line sensor to the conventional system. Using a matching algorithm the 3D reconstruction process which find the correspondence between the images is progressed. As the radiation image is just a density information of the scanned object, the direct application of the general stereo image processing techniques to it is inefficient. To overcome this limitation of a stereo image processing in radiation area, we reconstruct 3-D shapes of the edges of the objects. Also, we proposed a new volume based 3D reconstruction algorithm. Experimental results show the proposed new volume based reconstruction technique can provide more efficient visualization for cargo inspection. The proposed technique can be used for such objects which CT or MRI cannot inspect due to restricted scan environment.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.11 no.3
• /
• pp.136-150
• /
• 2008

Many studies have been carried out for automatic extraction of building by LiDAR data or airphoto. Combining the benefits of 3D location information data and shape information data of image can improve the accuracy. So, in this research building recognition algorithm based on contour was used to improve accuracy of building recognition by LiDAR data and elaborate building boundary recognition by airphoto. Building recognition algorithm based on contour can generate building boundary and roof structure information. Also it shows better accuracy of building detection than the existing recognition methods based on TIN or NDSM. Out of creating buffers in regular size on the building boundary which is presumed by contour, this research limits the boundary area of airphoto and elaborate building boundary to fit into edge of airphoto by double active contour. From the result of this research, 3D building boundary will be able to be detected by optimal matching on the constant range of extracted boundary in the future.

• International journal of advanced smart convergence
• /
• v.4 no.2
• /
• pp.109-119
• /
• 2015

The interaction between wireless sensors such as Internet of Things (IoT) and Cloud is a new paradigm of communication virtualization to overcome resource and efficiency restriction. Cloud computing provides unlimited platform, resources, services and also covers almost every area of computing. On the other hand, Wireless Sensor Networks (WSN) has gained attention for their potential supports and attractive solutions such as IoT, environment monitoring, healthcare, military, critical infrastructure monitoring, home and industrial automation, transportation, business, etc. Besides, our virtual groups and social networks are in main role of information sharing. However, this sensor network lacks resource, storage capacity and computational power along with extensibility, fault-tolerance, reliability and openness. These data are not available to community groups or cloud environment for general purpose research or utilization yet. If we reduce the gap between real and virtual world by adding this WSN driven data to cloud environment and virtual communities, then it can gain a remarkable attention from all over, along with giving us the benefit in various sectors. We have proposed a Pub/Sub-based sensor virtualization framework Cloud environment. This integration provides resource, service, and storage with sensor driven data to the community. We have virtualized physical sensors as virtual sensors on cloud computing, while this middleware and virtual sensors are provisioned automatically to end users whenever they required. Our architecture provides service to end users without being concerned about its implementation details. Furthermore, we have proposed an efficient content-based event matching algorithm to analyze subscriptions and to publish proper contents in a cost-effective manner. We have evaluated our algorithm which shows better performance while comparing to that of previously proposed algorithms.

• Journal of Korea Game Society
• /
• v.14 no.2
• /
• pp.55-66
• /
• 2014

Image warping is a technology to transform input images to be suitable for given conditions and has been recently utilized in changing face shape of characters in the field of movies or animation. Mesh warping which is one of warping methods that change shapes based on the features of face forms warping images by forming rectangular mesh groups around the eyes, nose, and mouth and matching them 1:1. This method has a problem in the resultant images are distorted in the segments of boundaries between meshes when there are errors in mesh control points or when meshes have been formed as many small area meshes. This study proposes a triangle based image interpolation technique to minimize the occurrence of errors in the process of forming natural warping images of face and process accurate results with a small amount of arithmetic operation and a short time. First, feature points that represent the face are found and these points are connected to form basic triangle meshes. The fact that the proposed method can reduce errors occurring in the process of warping while reducing the amount of arithmetic operation and time is shown through experiments.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.6
• /
• pp.117-126
• /
• 2010

In the case of failure images with controlling lighting like backlighting and excessive frontlinghting, the compensation scheme for a specific area in an image is required. The interested region is first selected by user in our method to compensate the first frame. Then we define the matching function of brightness and energy function is proposed with weight of matching function and the relationship among the neighbors. Finally, the energy is minimized by the graph-cut algorithm to compensate the brightness of the first frame. Other frames are straightforwardly compensated using the results of the first frame. The brightness variations of the previous frame is transmitted to the next frame via motion vectors. The reliability of the brightness variation is calculated based on the motion vector reliability. Video compensation result is achieved by the process of the image case. Simulation show that the proposed algorithm provides more natural results than the conventional algorithms.

• Korean Journal of Construction Engineering and Management
• /
• v.22 no.3
• /
• pp.40-51
• /
• 2021

MLS (Mobile Laser Scanning) which is a scanning method done by moving the LiDAR (Light Detection and Ranging) is widely employed to capture indoor PCD (Point Cloud Data) for floor plan generation in the AEC (Architecture, Engineering, and Construction) industry. The movement and rotation of LiDAR in the scanning phase cause deformation (i.e. skew) of PCD and impose a significant impact on quality of output. Thus, a de-skewing method is required to increase the accuracy of geometric representation. De-skewing methods which use position and pose information of LiDAR collected by IMU (Inertial Measurement Unit) have been mainly developed to refine the PCD. However, the existing methods have limitations on de-skewing PCD without IMU. In this study, a novel algorithm for de-skewing 2D PCD captured from MLS without IMU is presented. The algorithm de-skews PCD using scan matching between points captured from adjacent scan positions. Based on the comparison of the deskewed floor plan with the benchmark derived from TLS (Terrestrial Laser Scanning), the performance of proposed algorithm is verified by reducing the average mismatched area 49.82%. The result of this study shows that the accurate floor plan is generated by the de-skewing algorithm without IMU.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.6
• /
• pp.801-806
• /
• 2022

In the modern era, the necessity of color capability in the digital era is the demand of the era, and research on improving color practice on the subdivided digital four areas that are not in the existing practice is needed. For digital majors who are difficult to solve in existing paint color practice, classes in digital color practice in four more specialized areas are needed, and the use of efficient artificial intelligence was studied for classes in digitized color and color sense. In this paper, we tried to show the expansion of the color practice area by suggesting digital color practice and color matching method based on Photoshop artificial intelligence and big data technology that existing color and color matching were practice that only CMYK could do. In addition, based on the color quantification data of individual users provided by the latest Adobe Sceney program artificial intelligence, the purpose of the practice was to improve learners' predictions of actual color combinations and random colors using filter effects. In conclusion, it is a study on the use of programs that eliminate ambiguity in the mixing process of existing paint practice, secure digital color details, and propose a practical method that can provide effective learning methods for beginners and intermediates to develop their senses through artificial intelligence support. The Adobe program practice method necessary for coloration and main color through theoretical consideration and improvement of teaching skills that are better than existing paint practice were presented.

• Journal of the Korean Wood Science and Technology
• /
• v.37 no.1
• /
• pp.37-47
• /
• 2009

For the inspection of wood, machine vision is the most common automated inspection method used at present. It is required to sort wood products by grade and to locate surface defects prior to cut-up. Many different sensing methods have been applied to inspection of wood including optical, ultrasonic, X-ray sensing in the wood industry. Nowadays the scanning system mainly employs CCD line-scan camera to meet the needs of accurate detection of lumber defects and real-time image processing. But this system needs exact feeding system and low deviation of lumber thickness. In this study low cost CCD area sensor was used for the development of image processing system for lumber being fed. When domestic red pine being fed on the conveyer belt, lumber images of irregular term of captured area were acquired because belt conveyor slipped between belt and roller. To overcome incorrect image merging by the unstable feeding speed of belt conveyor, it was applied template matching algorithm which was a measure of the similarity between the pattern of current image and the next one. Feeding the lumber over 13.8 m/min, general area sensor generates unreadable image pattern by the motion blur. The red channel of RGB filter showed a good performance for removing background of the green conveyor belt from merged image. Threshold value reduction method that was a image-based thresholding algorithm performed well for knot detection.