• Science of Emotion and Sensibility
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• v.24 no.2
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• pp.57-64
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• 2021

It has long been speculated that the visual system should use a coding strategy that takes advantage of statistical redundancies in images. But how such a coding strategy should manifest in neural responses has been less clear. Low-level image structure related to the power spectrum of natural images appears to be captured by a hard-wired efficient code in the retina of the fly and precortical structures like the LGN of cats that maximizes information content through the limited capacity channel of the optic nerve. But visual images are typically filled with higher-order structure beyond that captured by the power spectrum and visual cortex is not constrained by the same capacity limits as the optic nerve. Whether and how visual cortex can flexibly code for higher order redundancies is unknown. Here we show using psychophysical techniques that the neural response in early human visual cortex may be modulated by orientation redundancies in images such that a visual feature that is contained within a predictive pattern results in slower reaction times than a feature that deviates from a pattern, suggesting lower neural responses to predictable stimuli in the visual cortex. Our results point to a neural response in early visual cortex that is sensitive to global patterns and redundancies in visual images and is in marked contrast to standard models of cortical visual processing.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.599-602
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• 2002

A new approach of error concealment using a digital watermarking technique for interframe video coding is presented in this paper. In the proposed method, the most important feature of the reference frame is extracted. Then, this feature is embedded into the prediction error of current frame prior to transmission. Error concealment is achieved by means of recovering the erroneous reference frame using the embedded data before the reconstruction of current frame is performed. Simulation results demonstrated the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3149-3165
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• 2013

Content based image retrieval is increasingly gaining popularity among image repository systems as images are a big source of digital communication and information sharing. Identification of image content is done through feature extraction which is the key operation for a successful content based image retrieval system. In this paper content based image retrieval system has been developed by adopting a strategy of combining multiple features of shape, color and relevance feedback. Shape is served as a primary operation to identify images whereas color and relevance feedback have been used as supporting features to make the system more efficient and accurate. Shape features are estimated through second derivative, least square polynomial and shapes coding methods. Color is estimated through max-min mean of neighborhood intensities. A new technique has been introduced for relevance feedback without bothering the user.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3E
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• pp.26-29
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• 1999

In this paper, we propose a new voice coding using only the features of the face image such as mouth height(H), width(W), rate(R=W/H), area(S), and ellipse's feature(P). It provides high security and is not affected by acoustic noise because we use only the features of face image for speech. In the proposed algorithm, the mean recognition rate for the vowels approximately rises between 70% and 96% after many tests.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.129-136
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• 2011

This paper presents the coding method that have multi-mode and efficiency of audio codecs using the feature of audio signal. Recently, the developed extension super-wideband codec based on G.718 wideband divides two mode between Generic and Sinusiodal. So codec efficently encode audio signal exist in super-wideband. But the codec is not as efficent coding for harmonic component of wind instrument and string instrument and individual-Line component of percussion instrument. The proposed method are modeling and encoding multiple pitch and individual-line feature using multi mode coding. For the performance evaluation, we used SNR in MDCT domain for objective test and MUSHRA test for subjective test. As a result, the performance of SNR and MUSHRA test of the proposed method have better performance than the G.718 super-wideband codec.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.214-217
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• 2000

Many researches have been performed for human recognition and coding schemes recently. For this situation, we propose an automatic facial feature extraction algorithm. There are two main steps: the face region evaluation from original background image such as office, and the facial feature extraction from the evaluated face region. In the face evaluation, Genetic Algorithm is adopted to search face region in background easily such as office and household in the first step, and Template Matching Method is used to extract the facial feature in the second step. We can extract facial feature more fast and exact by using over the proposed Algorithm.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.140-151
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• 2012

In Wyner-Ziv coding, key picture is encoded by conventional H.264/AVC intra coding which has low complexity. Although inter coding is more efficient than intra coding, its complexity is much higher than intra coding due to its motion estimation. Since the main feature of Wyner-Ziv coding is low complexity of encoder, inter coding is not suitable to encode key picture in Wyner-Ziv coding. However, inter picture coding with zero motion vector can be usable for Wyner-Ziv key picture coding instead of intra coding. Moreover, while current transform-domain Wyner-Ziv residual coding only utilizes temporal correlation of WZ picture, if zero motion coding is jointly used to encode key picture in transform-domain Wyner-Ziv residual coding, there will be a significant improvement in R-D performance. Experimental results show that the complexity of Wyner-Ziv coding with the proposed zero motion key picture coding is higher than conventional Wyner-Ziv coding with intra key picture coding by about 9%, however, there are BDBR gains up to 54%. Additionally, if the proposed zero motion key coding is implemented on top of the transform-domain Wyner-Ziv residual coding, the result shows rate gains up to 70% in BDBR compared to conventional Wyner-Ziv coding with intra key picture coding.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1353-1355
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• 1996

This paper presents classification of high impedance fault pattern using linear prediction coefficients. A feature of neutral phase current is extracted by the linear predictive coding. This feature is classified into faults by a multilayer perceptron neural network. Neural network successfully classifies test data into three faults and one normal state.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.136-141
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• 2012

One of the main reasons for serious road accidents is driving while drowsy. For this reason, drowsiness detection and warning system for drivers has recently become a very important issue. Monitoring physiological signals provides the possibility of detecting features of drowsiness and fatigue of drivers. One of the effective signals is to measure electroencephalogram (EEG) signals and electrooculogram (EOG) signals. The aim of this study is to extract drowsiness-related features from a set of EEG signals and to classify the features into three states: alertness, drowsiness, sleepiness. This paper proposes a neural-network-based drowsiness detection system using Linear Predictive Coding (LPC) coefficients as feature vectors and Multi-Layer Perceptron (MLP) as a classifier. Samples of EEG data from each predefined state were used to train the MLP program by using the proposed feature extraction algorithms. The trained MLP program was tested on unclassified EEG data and subsequently reviewed according to manual classification. The classification rate of the proposed system is over 96.5% for only very small number of samples (250ms, 64 samples). Therefore, it can be applied to real driving incident situation that can occur for a split second.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.69-78
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• 2018

When it comes to the value of modern education, teachers are required to perform the role of a helper to promote interaction between learners, the role of a manager to facilitate smooth learning, and the role of a guide who has expert knowledge in the learning contents. Therefore, this study investigated what kind of learner-centered teaching methods there are, which require teachers to perform the roles of helper, manager, and guide, and conducted a pedagogical research on coding education to explore class models for self-directed learning. Subsequently, a class model was proposed by applying the flipped learning and havruta learning to a coding class. In this study, the learner-centered education methods of flipped learning and havruta method were applied to constructing a coding class as a university general education course. The feature of this class is that it enables dynamic interaction between teachers and learners as well as active interaction between leaners in a classroom instruction. After applying the proposed method to the actual class and analyzing it, the students taught using suggested method were more positively assessed in learning interest than those taught using a traditional method. And that in academic achievement as well, suggested method was more effective.