• Transactions of the Society of Information Storage Systems
• /
• v.6 no.1
• /
• pp.1-5
• /
• 2010

Holographic data storage system(HDSS) has many noise sources - crosstalk, scattering and inter pixel interference, etc. Generally the intensity of a light generated from the laser source has Gaussian distribution and this ununiformity of light also can make the data page to have a low SNR. A beam apodizer is used to make the laser as a flat-top beam but the intensity distribution is not strictly uniform. The intensity of light can be controlled using image mask. In this paper the intensity distribution of light used for HDSS is controlled by a digital image mask. The digital image mask is changed arbitrarily in real-time with suggested algorithm for the HDSS.

• Journal of Broadcast Engineering
• /
• v.20 no.5
• /
• pp.676-686
• /
• 2015

A 4D light field image is represented in traditional 2D spatial domain and additional 2D angular domain. The 4D light field has a resolution limitation both in spatial and angular domains since 4D signals are captured by 2D CMOS sensor with limited resolution. In this paper, we propose a dictionary learning-based superresolution algorithm in 4D light field domain to overcome the resolution limitation. The proposed algorithm performs dictionary learning using a large number of extracted 4D light field patches. Then, a high resolution light field image is reconstructed from a low resolution input using the learned dictionary. In this paper, we reconstruct a 4D light field image to have double resolution both in spatial and angular domains. Experimental result shows that the proposed method outperforms the traditional method for the test images captured by a commercial light field camera, i.e. Lytro.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.8
• /
• pp.2875-2893
• /
• 2015

Existing coding aware routing algorithms focused on novel routing metric design that captures the characteristics of network coding. However, in packet coding algorithm, they use opportunistic coding scheme which didn't consider the queue state of the coding node and are equivalent to the conventional store-and-forward method in light traffic load condition because they never delay packets and there are no packets in the output queue of coding node, which results in no coding opportunity. In addition, most of the existing algorithms assume that all flows participating in the network have equal rate. This is unrealistic since multi-rate environments are often appeared. To overcome above problem and expand network coding to light traffic load scenarios, we present an enhanced coding-aware routing algorithm based on queue state and local topology (OQMCAR), which consider the queue state of coding node in packet coding algorithm where the control policy is of threshold-type. OQMCAR is a unified framework to merge single rate case and multiple rate case, including the light traffic load scenarios. Simulations results show that our scheme can achieve higher throughput and lower end-to-end delay than the current mechanisms using COPE-type opportunistic coding policy in different cases.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.11
• /
• pp.5491-5505
• /
• 2017

Use of the Gaussian inverse Wishart PHD (GIW-PHD) filter has demonstrated promise as an approach to track an unknown number of extended targets. However, the partitioning approaches used in the GIW-PHD filter, such as distance partition with sub-partition (DP-SP), prediction partition (PP) and expectation maximization partition (EMP), fails to provided accurate partition results when targets are spaced closely together and performing maneuvers. In order to improve the performance of a GIW-PHD filter, this paper presents a cooperation partitioning (CP) algorithm to solve the partitioning issue when targets are spaced closely together. In the GIW-PHD filter, the DP-SP is insensitive to target maneuvers but sensitive to the differences in target sizes, while EMP is the opposite. The proposed CP algorithm is a fusion approach of DP-SP and EMP, which employs EMP as a sub-partition approach after DP. Therefore, the CP algorithm will be sensitive to neither target maneuvers nor differences in target sizes. The simulation results show that the use of the proposed CP algorithm will improve the performance of the GIW-PHD filter when targets are spaced closely together.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.5A
• /
• pp.358-366
• /
• 2012

LED-ID (Light Emitting Diode - Identification) is one of the key technologies for identification, data transmission, and illumination simultaneously. This is the new paradigm in the identification technology environment. There are many issues are still now challenging to achieve high performance in LED-ID system. Collision issue is one of them. Actually this is the most significant issue in all identification system. LED-ID system also suffers from collision problem. In our system, collision occurs when two or more readers transmit data to tag at the same time or vice versa. There are many anti-collision protocols to resolve this problem; such as: Slotted ALOHA, Basic Frame Slotted ALOHA, Query Tree, Tree Splitting, and Q-Algorithm etc. In this paper, we propose modified Q-Algorithm to resolve collision at tag. The proposed protocol is based on Q-Algorithm and used the information of arrived readers to a tag from neighbor. The information includes transmitting slot number of readers and the number of readers that can be arrived in next slot. Our proposed protocol can reduce the numbers of collision slot and the successful time to identify all readers. In this paper our simulation and theoretical results are presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.3
• /
• pp.129-136
• /
• 2020

In this paper, we propose a thermal imagery-based object detection algorithm for low-light level nighttime surveillance system. Many features selected by Haar-like feature selection algorithm and existing Adaboost algorithm are often vulnerable to noise and problems with similar or overlapping feature set for learning samples. It also removes noise from the feature set from the surveillance image of the low-light night environment, and implements it using the lightweight extended Haar feature and adaboost learning algorithm to enable fast and efficient real-time feature selection. Experiments use extended Haar feature points to recognize non-predictive objects with motion in nighttime low-light environments. The Adaboost learning algorithm with video frame 800*600 thermal image as input is implemented with CUDA 9.0 platform for simulation. As a result, the results of object detection confirmed that the success rate was about 90% or more, and the processing speed was about 30% faster than the computational results obtained through histogram equalization operations in general images.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.1
• /
• pp.134-137
• /
• 2010

An LED sensor luminaire for visual function improvement necessitates the control algorithm for light level adjustment and the appropriate lens design. The control algorithm adapts to surround lighting condition, and thus has the advantages of energy saving and glare reduction. The multi-cell lens design improves color temperature uniformity and spatial light distribution of the luminaire. Experimental and simulated results show that this approach contributes noticeably to energy saving and color temperature uniformity of the LED sensor luminaire.

• International Journal of Internet, Broadcasting and Communication
• /
• v.10 no.4
• /
• pp.70-74
• /
• 2018

In order to ensure the flow of goods available and more flexible, reduce labor costs, many factories and industrial zones around the world are gradually moving to use automated solutions. One of them is to use Automated guided vehicles (AGV). Currently, there are a line tracing method as an AGV operating method, and a method of estimating the current position of the AGV and matching with a factory map and knowing the moving direction of the AGV. In this paper, we propose ceiling Light and guided line based moving direction estimation algorithm using multi-camera on the AGV in smart factory that can operate stable AGV by compensating the disadvantages of existing AGV operation method. The proposed algorithm is able to estimate its position and direction using a general - purpose camera instead of a sensor. Based on this, it can correct its movement error and estimate its own movement path.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2005.07b
• /
• pp.1269-1272
• /
• 2005

We propose a simple and efficient driving algorithm to reduce Dynamic False Contour(DFC) in Plasma Display Panels(PDPs) by using both accumulation and combination of light emission periods. Although the accumulative way of light emission in sustain period is regarded as more effective than combinational way to reduce DFC, it takes much addressing time to express high gray-scale. Therefore, we combine accumulative and combinational light emission methods to reduce DFC. In the proposed method, one TV field (16.7ms) is composed of four combinational subfields for expressing small gray scales and fifteen accumulative subfields for large gray scales. In addition, we use some Graphic Signal Processing(GSP) algorithm to get more natural images by reducing DFC.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.5
• /
• pp.483-488
• /
• 2008

An active omni-directional raging system using an omni-directional vision with structured light has many advantages compared to the conventional ranging systems: robustness against external illumination noise because of the laser structured light and computational efficiency because of one shot image containing $360^{\circ}$ environment information from the omni-directional vision. The omni-directional range data represents a local distance map at a certain position in the workspace. In this paper, we propose a matching algorithm for the local distance map with the given global map database, thereby to localize a mobile robot in the global workspace. Since the global map database consists of line segments representing edges of environment object in general, the matching algorithm is based on relative position and orientation of line segments in the local map and the global map. The effectiveness of the proposed omni-directional ranging system and the matching are verified through experiments.