Image hashing has been successfully applied for the problems associated with the protection of intellectual property, management of large database and indexation of content. For a reliable hashing system, improving hash matching accuracy is crucial. In order to improve the hash matching performance, we propose an asymmetric hash matching method using the psychovisual threshold, which is the maximum amount of distortion that still allows the human visual system to identity an image. A performance evaluation over sets of image distortions shows that the proposed asymmetric matching method effectively improves the hash matching performance as compared with the conventional Hamming distance.

Such as closed caption, ancillary data, electronic program guide(EPG), data broadcasting, and etc, increased data for service convenience cause to degrade video quality of high definition contents. This article propose a method to transfer the closed caption data of video contents without video quality degradation. Video quality degradation does not cause in video compression by the block image insertion of caption data in DTV essential hidden area. Additionally the proposed methods have advantage to synchronize video, audio, and caption from preinserted script without time delay.

Target/Nontarget classification can be divided into the study of shape estimation of the target analysing reflected echo signal and of type classification of the target using acoustical features. In active sonar system, the feature vectors are extracted from the signal reflected from the target, and an classification algorithm is applied to determine whether the received signal is a target or not. However, received sonar signals can be distorted in the underwater environments, and the spatio-temporal characteristics of active sonar signals change according to the aspect of the target. In addition, it is very difficult to collect real sea-trial data for research. In this paper, target/non-target classification were performed using real sea-trial data. Feature vectors are extracted using MFCC(Mel-Frequency Cepstral Coefficients), filterbank energy in the Fourier spectrum and wavelet domain. For the performance verification, classification experiments were performed using backpropagation neural network classifiers.

Pupil size variation can not be controlled intentionally by the user and includes various features such as the blinking frequency and the duration of a blink, so it is suitable for understanding the user's emotional state. In addition, an ocular feature based emotion classification method should be studied for virtual and augmented reality, which is expected to be applied to various fields. In this paper, we propose a novel emotion classification based on CNN with pupil size variation signals which include not only various ocular feature information but also time information. As a result, compared to previous studies using the same database, the proposed method showed improved results of 5.99% and 12.98% respectively from arousal and valence emotion classification.

A high-speed directional interpolation algorithm based on the pattern of a $2{\times}2$ pixel block is proposed in this paper. The basic concept of the proposed algorithm is started from UDWT(un-decimated discrete wavelet transform), but there are no transform operations. In order to detect the direction of the edge, 4-pixel differences of two pairs in the $2{\times}2$ block are compared. The $2{\times}2$ block patterns are grouped into total 8 classes, and thereafter the directional interpolation is executed according to the type of the pattern. Since the calculation of the proposed algorithm is very simple and needs a few additions on integer data type, the computation time is almost same as that of bilinear interpolation algorithm. However, experimental results show that the output quality of the proposed one is better than those of the conventional interpolation ones in the objective quality and the computation time.

A-Scan NDT equipment is widely used in the industrial field because it is inexpensive and easy to carry but it is necessary to have a skilled inspection specialist who is trained to analyze the waveform of ultrasonic signal. Since the welding quality is judged subjectively by the specialist, there is a problem in the reliability of the quality. In the C-Scan NDT which overcomes the shortcomings of the A-Scan, welding part can be represented in the form of two dimensional image by combining one dimensional ultrasonic waveform so that the quality of welding can be grasped without the help of specialist. In order to develop C-Scan NDT, it is necessary to develop an array type two dimensional transducer and an algorithm to composing image by combining ultrasonic signals generated from a two dimensional transducer. In addition, the noise component must be minimized in the ultrasonic signal in order to display the quality of welding in the form of images. Therefore we propose a method to remove noise component from the ultrasonic wave and construct a two dimensional ultrasonic image.

In this paper, we propose a machine learning method for random noise removal in image deblurring. The proposed method uses a logistic regression to select reliable data to use them, and, at the same time, to exclude data, which seem to be corrupted by random noise, in the deblurring process. The proposed method uses commonly available images as training data. Simulation results show an improved performance of the proposed method, as compared with the median filtering based reliable data selection method.

Infiltration is one of detrimental problems occurring in nursing or medical settings. Early detection of infiltration is essential to minimize the risk of injury from infiltration. To perform a preliminary study on the point of care and automated infiltration detection system, bioelectrical impedance was investigated using bioelectrical impedance analyzer. We would like to report experimental results that allow impedance parameters to effectively distinguish infiltration. Electrodes were attached to both sides of the transparent dressing on the fusion site where IV solution was being infused. Then, impedance parameters before and after infiltration were measured as a function of time and frequency. The experimental results are as follows. After infiltration was intentionally induced by puncturing the vein wall with a needle, the resistance gradually decreased with time. That is, when an alternating current having a frequency of 20 kHz was applied to the electrodes, the resistance gradually decreased with time, reflecting the accumulation of IV solution in the extracellular fluid since the current could not pass through the cell membrane. Impedance parameters and equivalent circuit model for human cell were used to examine the mechanism of current flow before and after infiltration, which could be used for early detection of infiltration.

The purpose of this study is to contribute to the development of a source of cultural contents by proposing extension possibility of cultural contents based on an original source. To this end, this article examined an aspect of Sherlock Holmes contents based on the novel "Sherlock Holmes" published in 1887. It has been produced as 217 different contents from 1899 to 2017 after publishing the novel Sherlock Holmes, and consequently, it has become the best material for the study of the expansion of contents. As a research method, we examined the concept of Transmedia with the change of media environment. Next, we examined the production method of "Sherlock Holmes" contents, analyzed the transformation factors according to each media, and presented the expansion of contents through "Sherlock Holmes" contents.

This paper aims to investigate the effect of anticipatory motion in Wall E (2008). For the purpose of the study, first of all, an overall discussion on the definition and role of anticipation presented through the related literature review. Based on this, the present study analyzed the functions of anticipatory movements of the main characters, Wall E and EVE in 29 scenes. As a result, this paper found that anticipation is involved in expressions of humanity, thought process, utterance and intonation, the degree of emotion and energy, reinforcement of the character's intention, and biological response within the film. Overall, these findings show that anticipation takes an important part in giving the illusion of life to the characters throughout the movie, which may imply that anticipation can be beneficial for characters with abstract form or limited modality. The ultimate goal of this study is to propose that the animation principles can be used as a tool to analyze character animation and can be applied academically or industrially to other fields such as artificial intelligence.