In the intelligent video surveillance, recognizing the moving objects is important issue. However, the conventional moving object recognition methods have some problems, that is, the influence of light, the distinguishing between similar colors, and so on. The recognition methods for the moving objects using depth information have been also studied, but these methods have limit of accuracy because the depth camera cannot measure the depth value accurately. In this paper, we propose a recognition method for the moving objects by using both the depth and the color information. The depth information is used for extracting areas of moving object and then the color information for correcting the extracted areas. Through tests with typical videos including moving objects, we confirmed that the proposed method could extract areas of moving objects more accurately than a method using only one of two information. The proposed method can be not only used in CCTV field, but also used in other fields of recognizing moving objects.

This paper proposed an realtime total monitoring platform for various kind of multi weather radars to analyze and predict weather phenomenons and prevent meteorological disasters. Our platform is designed to process each weather radar data on each radar site to minimize overloads from conversion and transmission of large volumed radar data, and to set observers up the definitive radar data via public framework server separately. By proposed method, weather radar data having different spatial or temporal resolutions can be automatically synchronized with there own spatio-temporal domains on public GIS platform having only one spatio-temporal criterion. Simulation result shows that our method facilitates the realtime weather monitoring from weather radars having various spatio-temporal resolutions without other data synchronization or assimilation processes. Moreover, since this platform doesn't require some additional computer equipments or high-technical mechanisms it has economic efficiency for it's systemic constructions.

Each year, significant amounts of Stereoscopic 3D(S3D) contents have been introduced. However, viewers who enjoy the contents readily experience a sense of fatigue on account of various factors. Consequently, many improvement studies have been conducted with the domain of disparity by, for example, simply controlling the disparity or optimizing the reaction speed of viewers' eyes to vergence. However, such studies are limited to the disparity domain and therefore are restricted to a limited number of applications. In this study, we attempted to transcend this limitation and analyzed how a reconstruction in color and brightness, as well as disparity and other important features, affects eyes in terms of vergence adaptation. As a result, we found that, the higher the color similarity is, the better it positively affects vergence adaptation during viewing. Based on this analysis, we propose in this paper a similar color extraction method between takes that are applicable to real-life situations. In an evaluation, the algorithm was applied to publicly available S3D contents and produced a converted color optimized image. The vergence adaptation time of this applied contents was significantly decreased. Also it was minimized through color reconstruction, thereby, being resulted in enhancing viewer concentration.

Paintings can evoke emotions in viewers. In this paper, we propose a method for extracting emotion from paintings by using the colors that comprise the paintings. For this, we generate color spectrum from input painting and compare the color spectrum and color combination for finding most similarity color combination. The found color combinations are mapped with emotional keywords. Thus, we extract emotional keyword as the emotion evoked by the painting. Also, we vary the form of algorithms for matching color spectrum and color combinations and extract and compare results by using each algorithm.

High-resolution satellite images are used in the fields of mapping, natural disaster forecasting, agriculture, ocean-based industries, infrastructure, and environment, and there is a progressive increase in the development and demand for the applications of high-resolution satellite images. Users of the satellite images desire accurate quality of the provided satellite images. Moreover, the distinguishability of each image captured by an actual satellite varies according to the atmospheric environment and solar angle at the captured region, the satellite velocity and capture angle, and the system noise. Hence , NIIRS must be measured for all captured images. There is a significant deficiency in professional human resources and time resources available to measure the NIIRS of few hundred images that are transmitted daily. Currently, NIIRS is measured every few months or even few years to assess the aging of the satellite as well as to verify and calibrate it [3]. Therefore, we develop an algorithm that can measure the national image interpretability rating scales (NIIRS) of a typical satellite image rather than an artificial target satellite image, in order to automatically assess its quality. In this study, the criteria for automatic edge region extraction are derived based on the previous works on manual edge region extraction [4][5], and consequently, we propose an algorithm that can extract the edge region. Moreover, RER and H are calculated from the extracted edge region for automatic edge region extraction. The average NIIRS value was measured to be 3.6342±0.15321 (2 standard deviations) from the automatic measurement experiment on a typical satellite image, which is similar to the result extracted from the artificial target.

In this paper, we propose an automatic prostate cancer detection method using position, signal intensity and texture feature based on SVM in multi-parametric MR images. First, to align the prostate on DWI and ADC map to T2wMR, the transformation parameters of DWI are estimated by normalized mutual information-based rigid registration. Then, to normalize the signal intensity range among inter-patient images, histogram stretching is performed. Second, to detect prostate cancer areas in T2wMR, SVM classification with position, signal intensity and texture features was performed on T2wMR, DWI and ADC map. Our feature classification using multi-parametric MR imaging can improve the prostate cancer detection rate on T2wMR.

Automated guided vehicles have been used for a long time to increase work efficiency in the logistics field, but it is difficult to apply to a variety of logistics sites due to either the restricted movement mechanism or expensive devices. In this paper, we present a flexible software architecture that is hardware-independent for a mobile power cart of the follow mode and implement it using a ROS software platform. Through the SCV analysis for the system functionalities, we design a package to track a user movement and a package to control a new hardware platform. It has an advantage to use a variety of movement algorithms and hardware platforms by applying the strategy pattern and the template method pattern for the design of a software architecture. Through the performance evaluation, we show that the proposed design is maintainable in terms of a software complexity and it detects a user's movement by obtaining a user skeleton information so that it can control a hardware platform to move at a certain distance.

In this paper, we present electroencephalography (EEG)-based power spectra analysis and auditory stimuli methods as coping mechanisms for disgust affection and phobia. Disgust affection is a negative emotion generated from trying to eliminate something harmful to one. It is usually related to mental illnesses such as obsessive-compulsive disorder, specifically phobia and depression. In our experiments, participants watched videos on horrible body mutilation and disgusting creatures, with either the original sound track or relaxing and exciting music as auditory stimulation. After watching the videos with original sound track, the participants watched the same video with a different audio background, such as soothing or cheerful music. We analyzed the EEG data utilizing relative power spectra and examined survey results of the participants. The results demonstrated that disgust affection is decreased when participants watched the video with relaxing or exciting music instead of the original soundtracks. Moreover, we confirmed that human's brainwave reacts according to types of audio and sources of disgust affection.

As multimedia content technology developed, there are many cases that service contents are being provided in many different ways in the cloud-based media service system. A DRM is a technology that can enhance the copyright of the digital content by providing right information. It is available on a single platform and has a problem that the additional cost when the platform is changing. In this paper, we propose a media service system based on cloud computing. It can be used on multiple platforms at the same time by applying a number of DRM for digital contents, and allows use of a new authentication for another platform without any additional cost.

The conventional methods using color signal for tracking the movement of the object require a lot of calculation and the performance is not accurate. In this paper, we propose a method to effectively track the moving objects using the depth information from a depth camera. First, it separates the background and the objects based on the depth difference in the depth of the screen. When an object is moved, the depth value of the object becomes blurred because of the phenomenon of Motion Blur. In order to solve the Motion Blur, we observe the changes in the characteristics of the object (the area of the object, the border length, the roundness, the actual size) by its velocity. The proposed algorithm was implemented in the simulation that was applied directly to the tracking of a golf ball. We can see that the estimated value of the proposed method is accurate enough to be very close to the actual measurement.

Development of information and communication technologies has given a lot of changes in the business processing methods including the school and class managements. However, many business processing systems are still based on desktop computer. In particular, most of the class management system only supports desktop computers; hence school teachers have difficulty in using their class managements systems on mobile environment. In this paper, we proposed and developed a mobile classroom management system for teachers, which will easily handle information such as personal records of students, student counseling records, student life record and so on. The implementation of the application of mobile-based class management can be managed by many school elements including student register information, student evaluation records and transcripts, counseling report, and so on.

Analyze the Android game framework that can be apply to the Application development of new areas and suggest Document-View pattern of a design pattern, design that this applies the Android framework(DVAGF) for novice Game programming learner. Case of Snake game development through DVAGF is supporting modularity of the code, reusability and expandability that seems that the learners can easily understand the game programming basic structure. In addition, the Android framework (DVAGF) seems to provide a basis that can be easily extended to 2D and 3D games.