• Korean Journal of Optics and Photonics
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• v.20 no.1
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• pp.16-22
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• 2009

We propose a method to convert a two-dimensional movie to a three-dimensional movie using normalized cut and optical flow. In this paper, we segment an image of a two-dimensional movie to objects first, and then estimate the depth of each object. Normalized cut is one of the image segmentation algorithms. For improving speed and accuracy of normalized cut, we used a watershed algorithm and a weight function using optical flow. We estimate the depth of objects which are segmented by improved normalized cut using optical flow. Ordinal depth is estimated by the change of the segmented object label in an occluded region which is the difference of absolute values of optical flow. For compensating ordinal depth, we generate the relational depth which is the absolute value of optical flow as motion parallax. A final depth map is determined by multiplying ordinal depth by relational depth, then dividing by average optical flow. In this research, we propose the two-dimensional/three-dimensional movie conversion method which is applicable to all three-dimensional display devices and all two-dimensional movie formats. We present experimental results using sample two-dimensional movies.

• Journal of Korean Tunnelling and Underground Space Association
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• v.10 no.1
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• pp.69-79
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• 2008

Prediction of ground condition ahead of tunnel face might be the most important factor to prevent collapse during tunnel excavation. In this study, a non-destructive method to evaluate the phase velocity in model rock mass using wavelet transform of surface wave was proposed aiming at ground condition assessment ahead of tunnel face. Model tests using gypsum as a rocklike material composed of two layers were performed. A Piezoelectric actuator with frequencies ranging from 150 Hz to 5 kHz was selected as a harmonic source. The acceleration history was measured with two accelerometers. Wavelet transform analysis was used to obtain the dispersion curves from the measured data. The experimental results showed that the near-field effects can be neglected if the distance between two receivers is chosen to be three times the wavelength. A simple inversion method using weighted factor based on the normal distribution was proposed. The inversion results showed that the predicted phase velocity agreed reasonably well with the measured one when the wavelength influence factor was 0.2. The depth of propagation of surface wave was from 0.42 to 0.63 times the wavelength. The range of wavelength varying with phase velocity in dispersion curve matched well with that estimated by inversion technique.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.876-884
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• 2003

It is essential to identify both the pupil and iris boundaries for iris recognition. The circular edge detector proposed by Daugman is the most common and powerful method for the iris region extraction. The method is accurate but requires lots of computational time since it is based on the exhaustive search. Some heuristic methods have been proposed to reduce the computational time, but they are not as accurate as that of Daugman. In this paper, we propose a pupil and iris boundary finding algorithm which is faster than and as accurate as that of Daugman. The proposed algorithm searches the boundaries using the Daugman's circular edge detector, but reduces the search region using the problem domain knowledge. In order to find the pupil boundary, the search region is restricted in the maximum and minimum bounding circles in which the pupil resides. The bounding circles are obtained from the binarized pupil image. Two iris boundary points are obtained from the horizontal line passing through the center of the pupil region obtained above. These initial boundary points, together with the pupil point comprise two bounding circles. The iris boundary is searched in this bounding circles. Experiments show that the proposed algorithm is faster than that of Daugman and more accurate than the conventional heuristic methods.

• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.403-413
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• 2011

In this paper, we proposed a digital image watermarking technique using scrambled binary phase computer generated hologram in the discrete cosine transform(DCT) domain. For the embedding process of watermark. Using simulated annealing algorithm, we would generate a binary phase computer generated hologram(BPCGH) which can reconstruct hidden image perfectly instead of hidden image and encrypt it through the scramble operation. We multiply the encrypted watermark by the weight function and embed it into the DC coefficients in the DCT domain of host image and an inverse DCT is performed. For the extracting process of watermark, we compare the DC coefficients of watermarked image and original host image in the DCT domain and dividing it by the weight function and decrypt it using descramble operation. And we recover the hidden image by inverse Fourier transforming the decrypted watermark. Finally, we compute the correlation between the original hidden image and recovered hidden image to determine if a watermark exits in the host image. The proposed watermarking technique use the hologram information of hidden image which consist of binary values and scramble encryption technique so it is very secure and robust to the various external attacks such as compression, noises and cropping. We confirmed the advantages of the proposed watermarking technique through the computer simulations.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.89-98
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• 2016

In this paper, we proposed an automated areal feature matching method based on geometric similarity without user intervention and is applied into areal features of many-to-many relation, for confusion of spatial data-sets of different scale and updating cycle. Firstly, areal feature(node) that a value of inclusion function is more than 0.4 was connected as an edge in adjacency matrix and candidate corresponding areal features included many-to-many relation was identified by multiplication of adjacency matrix. For geometrical matching, these multiple candidates corresponding areal features were transformed into an aggregated polygon as a convex hull generated by a curve-fitting algorithm. Secondly, we defined matching criteria to measure geometrical quality, and these criteria were changed into normalized values, similarity, by similarity function. Next, shape similarity is defined as a weighted linear combination of these similarities and weights which are calculated by Criteria Importance Through Intercriteria Correlation(CRITIC) method. Finally, in training data, we identified Equal Error Rate(EER) which is trade-off value in a plot of precision versus recall for all threshold values(PR curve) as a threshold and decided if these candidate pairs are corresponding pairs or not. To the result of applying the proposed method in a digital topographic map and a base map of address system(KAIS), we confirmed that some many-to-many areal features were mis-detected in visual evaluation and precision, recall and F-Measure was highly 0.951, 0.906, 0.928, respectively in statistical evaluation. These means that accuracy of the automated matching between different spatial data-sets by the proposed method is highly. However, we should do a research on an inclusion function and a detail matching criterion to exactly quantify many-to-many areal features in future.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.35-44
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• 2014

This paper proposes a 3D pointing interface that is designed for the efficient application of a hand mouse. The proposed method uses depth images to secure high-quality results even in response to changes in lighting and environmental conditions and uses the normal vector of the palm of the hand to perform 3D pointing. First, the hand region is detected and tracked using the existing conventional method; based on the information thus obtained, the region of the palm is predicted and the region of interest is obtained. Once the region of interest has been identified, this region is approximated by the plane equation and the normal vector is extracted. Next, to ensure stable control, interpolation is performed using the extracted normal vector and the intersection point is detected. For stability and efficiency, the dynamic weight using the sigmoid function is applied to the above detected intersection point, and finally, this is converted into the 2D coordinate system. This paper explains the methods of detecting the region of interest and the direction vector and proposes a method of interpolating and applying the dynamic weight in order to stabilize control. Lastly, qualitative and quantitative analyses are performed on the proposed 3D pointing method to verify its ability to deliver stable control.

• Journal of radiological science and technology
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• v.35 no.4
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• pp.321-326
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• 2012

Used as an ingredient in the hospital for orthopedic prosthetic stainless and titanium metal the same size as on the MRI diagnostic value of imaging were compared. Center of images, background high band portion of the video signal is converted into a weighted intensity values Normal images and compared. The area of normal slice and also the distortion of images and cross-sectional imaging of a range of quantitative and sagittal planes were compared. As a result, the periphery high band signal intensity values of Stainless video phantom 2, pig bone 1.8, Titanium imaging of phantom 1.7 has higher value than Normal video pig bone 1.3 times the signal strength rivers. MRI distortion of the shape and the distortions of the range, if the cross-sectional area compared to Normal Slice Stainless case of phantom 65.8 %, pig bone 61.5 %, Titanium distortion phantom 23.1 %, pig bone 38.5 % of the range of community found. In this experiment, as a result, MRI was found to be Titanium more diagnostic value than the specimen with respect to the signal intensity weighted value and low distortion range, Stainless.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.73-80
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• 2012

Recent research efforts have focused on combining high dynamic range imaging with super-resolution reconstruction to enhance both the intensity range and resolution of images. The processes developed to date start with a set of multiple-exposure input images with low dynamic range (LDR) and low resolution (LR), and require several procedural steps: conversion from LDR to HDR, SR reconstruction, and tone mapping. Input images captured with irregular exposure steps have an impact on the quality of the output images from this process. In this paper, we present a simplified framework to replace the separate procedures of previous methods that is also robust to different sets of input images. The proposed method first calculates weight maps to determine the best visible parts of the input images. The weight maps are then applied directly to SR reconstruction, and the best visible parts for the dark and highlighted areas of each input image are preserved without LDR-to-HDR conversion, resulting in high dynamic range. A new luminance control factor (LCF) is used during SR reconstruction to adjust the luminance of input images captured during irregular exposure steps and ensure acceptable luminance of the resulting output images. Experimental results show that the proposed method produces SR images of HDR quality with luminance compensation.

• Journal of the Korean association of regional geographers
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• v.13 no.2
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• pp.143-155
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• 2007

There are many conflicts or interests among various stakeholders on the development of the coastal area. The integrated methodology, which is reflective of physical conditions, socio-economic circumstances, and people's sense of values, is thus needed to solve the problems. In this study, geographical information systems(GIS) and analytic hierarchy process(AHP) that arc one of multi-criteria analysis methodologies are loosely coupled to develop better analytic procedures for coastal assessment. Socio-economic and environmental parameters of the study area, Hampyung Bay area, are converted to a GIS system-applicable format, while AHP is used to assess the relative importance level of each parameter by calculating weighting factors. After standardizing and rasterizing spatial data from various sources. the weighting factors are applied to produce the layers for each parameter. Map algebra and overlay analyses are used to create the final layer according to the decision making logic or model proposed here. Cell values of that layer could be considered as spatial alternatives. In addition to this finding, the flexibility with the weighing factors enable decision-makers to understand the procedures and alternatives in relevance with selective strategies for coastal management.

• Journal of IKEEE
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• v.22 no.4
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• pp.1140-1146
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• 2018

Recently, a methodology for analyzing complex bio-signals using a deep learning model has emerged among studies that recognize human emotions. At this time, the accuracy of emotion classification may be changed depending on the evaluation method and reliability depending on the kind of data to be learned. In the case of biological signals, the reliability of data is determined according to the noise ratio, so that the noise detection method is as important as that. Also, according to the methodology for defining emotions, appropriate emotional evaluation methods will be needed. In this paper, we propose a wavelet -based noise threshold setting algorithm for verifying the reliability of data for multimodal bio-signal data labeled Valence and Arousal and a method for improving the emotion recognition rate by weighting the evaluation data. After extracting the wavelet component of the signal using the wavelet transform, the distortion and kurtosis of the component are obtained, the noise is detected at the threshold calculated by the hampel identifier, and the training data is selected considering the noise ratio of the original signal. In addition, weighting is applied to the overall evaluation of the emotion recognition rate using the euclidean distance from the median value of the Valence-Arousal plane when classifying emotional data. To verify the proposed algorithm, we use ASCERTAIN data set to observe the degree of emotion recognition rate improvement.