An image segmentation result depends on pre-processing steps such as contrast enhancement, edge detection, and smooth filtering etc. Especially medical images are low contrast and contain some noises. Therefore, the contrast enhancement and noise removal techniques are required in the pre-processing. In this study, we present an extension by a novel histogram equalization in which both local and global contrast is enhanced using neighborhood metrics. When checking neighborhood information, filters can simultaneously improve image quality. Most important is that original image information can be used for both global brightness preserving and local contrast enhancement, and image quality improvement filtering. Our experiments confirmed that the proposed method is more effective than other similar techniques reported previously.

In neuroscientific research, image segmentation is one of the most important processes. The morphology of axons plays an important role for researchers seeking to understand axonal functions and connectivity. In this study, we evaluated the level set segmentation method for neuronal axons in a Brainbow confocal microscopy image. We first obtained a reconstructed image on an x-z plane. Then, for preprocessing, we also applied two methods: anisotropic diffusion filtering and bilateral filtering. Finally, we performed image segmentation using the level set method with three different approaches. The accuracy of segmentation for each case was evaluated in diverse ways. In our experiment, the combination of bilateral filtering with the level set method provided the best result. Consequently, we confirmed reasonable results with our approach; we believe that our method has great potential if successfully combined with other research findings.

In this paper, we present an algorithm that quickly and effectively estimates orthogonal vanishing points in equirectangular images of urban environment. Our algorithm is based on the RANSAC (RANdom SAmple Consensus) algorithm and on the characteristics of the line segment in the spherical panorama image of the $360^{\circ}$ longitude and $180^{\circ}$ latitude field of view. These characteristics can be used to reduce the geometric ambiguity in the line segment classification as well as to improve the robustness of vanishing point estimation. The proposed algorithm is validated experimentally on a wide set of images. The results show that our algorithm provides excellent levels of accuracy for the vanishing point estimation as well as line segment classification.

The problem of Metal Area Segmentation (MAS) in X-ray CT images is a very hard task because of metal artifacts. This research features a practical yet effective method for MAS in X-ray CT images that exploits both projection image and reconstructed image spaces. We employ the Relevant Neighbor Area (RNA) idea [1] originally developed for projection image inpainting in order to create a novel feature in the projection image space that distinctively represents metal and near-metal pixels with opposite signs. In the reconstructed result of the feature image, application of a simple thresholding technique provides accurate segmentation of metal areas due to nice separation of near-metal areas from metal areas in its histogram.

This paper has developed a system for early diagnosis of senile dementia and mild cognitive impairment (MCI) by developing software to measure the volume of hippocampus. This software consists of two parts; segmentation and analysis. The segmentation part uses ROI and region growing to segment hippocampus region. On the other hand, the analysis part creates a volume rendering of hippocampus. This software is expected contribute in these research fields for dementia diagnosis and its medication planning.

In this paper, we study the ON/OFF control policy of base stations in two-tier heterogeneous cellular networks to minimize the total power consumption of the system. Using heterogeneous cellular networks is a potential approach of providing higher throughput and coverage compared to conventional networks with only macrocell deployment, but in fact heterogeneous cellular networks often operates regardless of total power consumption, which is a very important issue of modern cellular networks. We propose a policy that controls the activation/deactivation of base stations in heterogeneous cellular networks to minimize total power consumption. Under this policy, the total power consumed can be significantly reduced when the traffic is low while the QoS requirement is satisfied.

In this paper, we propose a QoS (Quality of Service)-aware and cooperative resource reservation scheme using cross-layer link adaptation for wireless high definition video transmission through UWB (Ultra Wide Band) network with D-MAC (Distributed Medium Access Control). A wireless high definition video transmission system usually requires stable high throughput even without line-of-sight, e.g., a destination device in another room separated by a wall. Since the WiMedia D-MAC supporting DRP (Distributed Reservation Protocol) scheme causes lots of DRP resource reservation conflicts due to failure of beacon detection in wireless channel environment, overall performances of the WiMedia D-MAC can be deteriorated. And the current WiMedia MAC standard has not considered QoS provisioning even though QoS parameters such as a range of service rates are provided to each traffic stream. Therefore, we propose Relay DRP protocol with QoS-based relay node selection criterion, which makes a relay path to avoid DRP resource reservation conflicts and guarantee QoS more stably through cross-layer link adaptation of cooperative relay transmission scheme and is compliant with the current WiMedia D-MAC protocol. Simulation results demonstrate performance improvements of the proposed method for throughput and QoS provisioning.

Today many companies introduce new mobile office environments evolved from the recent rapid development in mobile device technologies. Most of the recent mobile office systems use a simple authentication scheme such as ID/Password. This method is easy to use, but it does not consider the user's context. Thus it cannot provide appropriate security service required by the user's proper contexts. Therefore, this paper proposes a context based authentication system which applies security level verification and uses fuzzy algorithm based on the importance of access authority control.

In this paper, we address the problem of fast handover support for future internet networks. The current mobility support protocols, for example Proxy Mobile IPv6, follow a centralized architecture in which a mobility controller is used to manage intra-network handovers that gives rise to high handover latency. To handle this problem, we propose a novel distributed mobility control architecture in which gateways in the network can exchange user information with neighbour gateways to support intra-network handovers, the mobility controller is only needed in case of inter-network handovers. Simulation results show that our architecture reduce approximately 20% intra-network handover latency than Proxy Mobile IPv6.

One of the major issues in current internet architecture is that it was not designed to support the user mobility. In order to overcome this restriction, in this paper, we propose an identifier/locator separation architecture which contain the overlay mapping system to store the identifier-to-locator mapping record. In addition, we design the mobility management scheme base on Identifier/Locator separation above for Furture Internet architecture. We then devise the analysis model to evaluate the signaling cost of our scheme. By conducting the simulation. we show that our scheme can operate with lower signaling cost than other schemes.

Recently, the distributed processing system for big data has been actively investigated owing to the development of high speed network and storage technologies. In addition, virtual system that can provide efficient use of system resources through the consolidation of servers has been increasingly recognized. But, when we configure distributed processing system for big data in virtual machine environments, many problems occur. In this paper, we did an experiment on the optimization of I/O bandwidth according to the creation and placement of VMs and tasks with composing Hadoop cluster in virtual environments and evaluated the results of an experiment. These results conducted by this paper will be used in the study on the development of Hadoop Scheduler supporting I/O bandwidth balancing in virtual environments.

In a ship block logistics application, acquisition of locations is required in order to identify location of the ship blocks. A Smart device equipped with a GPS sensor can be used as a mobile client for a ship block logistics application. However the precision of GPS components on a commercial smart device is not high enough. Therefore, using the GPS for localization may produce significant positioning errors in a ship block logistics system. This paper proposes a method to reduce errors in measuring locations using a smart device. Based on the knowledge of how the location information is used in a ship block logistics application, and the predictability of the client's moving line based on geographical layout of a shipyard area, our proposed technique enables a better prediction of the ship blocks location. Performance evaluation shows that the proposed technique can significantly reduce the positional error.