• Cartoon and Animation Studies
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• s.12
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• pp.87-102
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• 2007

Animation techniques that can freely create any movement of color and shape produce strong attraction by visualizing fantasy. Like animation, fantasy is often misunderstood that it has nothing to do with reality, but it is not the case. Fantasy introduces a little confusion in our symbolic order by reorganizing elements from reality and commonness. This confusion, which becomes desire, induces attraction. However, the confusion beyond our comprehension creates total chaos in which we cannot be interested. Attraction happens only when the introduced confusion is far less than the total symbolic order which has already been established. The images of animation are neither completely mundane to us nor beyond our comprehension; thus, animation produces attraction by offering us images that stimulate our unconscious desire.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.59-65
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• 2003

The merging of different scales or multi-sensor image data is becoming a widely used procedure of the complementary nature of various data sets. Ideally, the merging method should not distort the characteristics of the high-spatial and high-spectral resolution data used. To present an effective merging method for survey of reclaimed land using the high-resolution (6.6 m) Electro-Optical Camera (EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1 (KOMPSA T-l) and the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) image data, this paper compares the results of Intensity Hue Saturation (IHS) and Principal Component Analysis (PCA) methods. The comparison is made by statistical and visual evaluation of three-color combination images of IHS and PCA results based on spatial and spectral characteristics. The use of MODIS bands 1, 2, and 3 with a contrast stretched EOC panchromatic image as a substitute for intensity was found to be particularly effective in this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1424-1440
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• 2015

It is a challenging problem to search the intended images from a large number of candidates. Content based image retrieval (CBIR) is the most promising way to tackle this problem, where the most important topic is to measure the similarity of images so as to cover the variance of shape, color, pose, illumination etc. While previous works made significant progresses, their adaption ability to dataset is not fully explored. In this paper, we propose a similarity learning method on the basis of probabilistic generative model, i.e., probabilistic latent semantic analysis (PLSA). It first derives Fisher kernel, a function over the parameters and variables, based on PLSA. Then, the parameters are determined through simultaneously maximizing the log likelihood function of PLSA and the retrieval performance over the training dataset. The main advantages of this work are twofold: (1) deriving similarity measure based on PLSA which fully exploits the data distribution and Bayes inference; (2) learning model parameters by maximizing the fitting of model to data and the retrieval performance simultaneously. The proposed method (PLSA-FK) is empirically evaluated over three datasets, and the results exhibit promising performance.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1024-1033
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• 2016

In this study, a system is proposed for analyzing whether driver's eyes are open or closed on the basis of images to determine driver's drowsiness. The proposed system converts eye areas detected by a camera to a color space area to effectively detect eyes in a dark situation, for example, tunnels, and a bright situation due to a backlight. In addition, the system used a thickness distribution of a detected eye area as a feature value to analyze whether eyes are open or closed through the Support Vector Machine(SVM), representing 90.09% of accuracy. In the experiment for the images of driver wearing glasses, 83.83% of accuracy was obtained. In addition, in a comparative experiment with the existing PCA method by using Eigen-eye and Pupil Measuring System the detection rate is shown improved. After the experiment, driver's drowsiness was identified accurately by using the method of summing up the state of driver's eyes open and closes over time and the method of detecting driver's eyes that continue to be closed to examine drowsy driving.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1197-1204
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• 2015

Smoke detection plays an important role for the early detection of fire. In this paper, we suggest a newly developed method that generated LBPV(Local Binary Pattern Variance)s as special feature vectors from RGB contrast images can be applied to detect smoke using SVM(Support Vector Machine). The proposed method rearranges mean value of the block from each R, G, B channel and its intensity of the mean value. Additionally, it generates RGB contrast image which indicates each RGB channel’s contrast via smoke’s achromatic color. Uniform LBPV, Rotation-Invariance LBPV, Rotation-Invariance Uniform LBPV are applied to RGB Contrast images so that it could generate feature vector from the form of LBP. It helps to distinguish between smoke and non smoke area through SVM. Experimental results show that true positive detection rate is similar but false positive detection rate has been improved, although the proposed method reduced numbers of feature vector in half comparing with the existing method with LBP and LBPV.

• Korean Journal of Optics and Photonics
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• v.8 no.2
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• pp.165-168
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• 1997

We have constructed a scanning confocal microscope using a 780 nm semiconductor laser, an actuator of a compact disk player and a quad-detector. This device detects heights and characteristics of a surface. The laser focus was located at the surface of a sample by using the error signal obtained by a quad-dector, and the current supplied to the actuator for lens was displayed as a height. The materials of a surface were classified according to reflected total intensities and was displayed by different color in a monitor. The device has very samll dimensions of 30 mm$\times$20 mm$\times$20 mm and scan field is 1.6 mm$\times$1.6mm. We obtained two images, one using only reflected light and the other using an error signal from a quad-detector and compared these two images.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1077-1081
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• 2004

In this Paper we discuss an algorithm for a real-time transmission of moving color image on the TCP/IP network using wavelet transform and neural network. The Image frames received from the camera are two-level wavelet-transformed in the server, and are transmitted to the client on the network. Then, the client performs the inverse wavelet-transform using only the received pieces of each image frame within the prescribed time limit to display the moving images. When the TCP/IP network is busy, only a fraction of each image frame will be delivered. When the line is free, the whole frame of each image will be transferred to the client. The receiver warns the sender of the condition of traffic congestion in the network by sending a special short frame for this specific purpose. The sender can respond to this information of warning by simply reducing the data rate which is adjusted with a neural network or fuzzy logic. In this way we can send a stream of moving images adaptively adjusting to the network traffic condition.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.7
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• pp.125-131
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• 1989

This paper proposes a new ABTC (Adaptive Block Truncation Coding) algorithm which improves the BTC algorithm for image data compression. A new adaptive block truncation coding which adopts a selective coding scheme depending on the local characteristics of an image has been described. The characteristics of the ABTC algorithm can be summarized as high compression ratio and the algorithm simplicity. Using this algorithm, color images can be coded at a variable bit rate from 1.0 (bit/pel) to 2.56 (bit/pel) and high compression rate (1.3-105 bit/pel) can be achieved without conspicuous image degradation compared with original images.

• Imaging Science in Dentistry
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• v.47 no.4
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• pp.247-254
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• 2017

Purpose: Dual-energy X-ray imaging is widely used today in various areas of medicine and in other applications. However, no similar technique exists for dental applications. In this study, we propose a dual-energy technique for dental diagnoses based on voltage-switching. Materials and Methods: The method presented in this study allowed different groups of materials to be classified based on atomic number, thereby enabling two-dimensional images to be colorized. Computer simulations showed the feasibility of this approach. Using a number of different samples with typical biologic and synthetic dental materials, the technique was applied to radiographs acquired with a commercially available dental X-ray unit. Results: This technique provided a novel visual representation of the intraoral environment in three colors, and is of diagnostic value when compared to state-of-the-art grayscale images, since the oral cavity often contains multiple permanent foreign materials. Conclusion: This work developed a technique for two-dimensional dual-energy imaging in the context of dental applications and showed its feasibility with a commercial dental X-ray unit in simulation and experimental studies.

• Journal of Ocean Engineering and Technology
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• v.34 no.1
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• pp.46-54
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• 2020

Oil spill accidents at sea result in a wide range of damages, including the destruction of ocean environments and ecosystems, as well as human illnesses by the generation of harmful gases caused by phase changes in crude oil. When an oil spill occurs, an immediate initial action should be performed to minimize the potential damage. Existing studies have attempted to identify crude oil spillage by calculating the crude oil spill range using synthetic aperture radar (SAR) satellite images. However, SAR cannot capture rapidly evolving events because of its low acquisition frequency. Herein, an algorithm for estimating an oil spill area from an image obtained using a digital camera is proposed. Noise that may occur in the image when it is captured is first eliminated by preprocessing, and then the image is analyzed. After analyzing the characteristics of the digital image, a strategy to binarize an image using the color, saturation, or lightness contained in it is adopted. It is found that the oil spill area can be readily estimated from a digital image, allowing for a faster analysis than any conventional method. The usefulness of the oil spill area measurement was confirmed by applying the developed algorithm to various oil spill images.