• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1464-1468
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• 2004

The color conversion and color enhancement on gray image is presented in this paper. The pseudocoloring for RCB color components extraction from gray image is used the 2D U(Fast Wavelet Transform) for fille. bank and re-array. The each post processing is used the median filtering for noise reduction and the discrete color histogram equalization for CIT(Color Intensity Transformation). The experiment result has enhanced pseudocoloring image as PSNR 30dB over compared the processing of normal wavelet transform.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.351-356
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• 2012

This paper presents the 2D/3D conversion technique using depth map which is generated based on the haze and relative height cue. In cases that only the conventional haze information is used, errors in image without haze could be generated. To reduce this kind of errors, a new approach is proposed combining the haze information with depth map which is constructed based on the relative height cue. Also the gray scale image from Mean Shift Segmentation is combined with depth map of haze information to sharpen the object's contour lines, upgrading the quality of 3D image. Left and right view images are generated by DIBR(Depth Image Based Rendering) using input image and final depth map. The left and right images are used to generate red-cyan 3D image and the result is verified by measuring PSNR between the depth maps.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.125-132
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• 2024

Optical satellite images are being used for national security and collection of information, and their utilization is increasing. However, it acquires low-quality images that are not suitable for the user's requirement due to weather conditions and time constraints. In this paper, a deep learning-based conversion of image and colorization model referring to high-resolution SAR images was created to simulate the occluded area with clouds of optical satellite images. The model was experimented according to the type of algorithm applied and input data, and each simulated images was compared and analyzed. In particular, the amount of pixel value information between the input black-and-white image and the SAR image was similarly constructed to overcome the problem caused by the relatively lack of color information. As a result of the experiment, the histogram distribution of the simulated image learned with the Gray-scale image and the high-resolution SAR image was relatively similar to the original image. In addition, the RMSE value was about 6.9827 and the PSNR value was about 31.3960 calculated for quantitative analysis.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.8-13
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• 2017

In this paper, the measurement of the inner diameter dimension of the circular hole by using a machine vision system was studied. This paper was focused on the theory and key technologies of machine vision inspection technology for the improvement of measurement accuracy and speed of the micro circular holes. A new method was proposed and was verified through the experiments on Gray conversion, binarization, edge extraction and Hough transform in machine vision system processes. Firstly, the Hough transform was proposed in order to improve the speed increase and implementation ease, it demonstrated the superiority of Hough transform and improvement through a comparative experiment. Secondly, we propose a calibration method of the system in order to obtain exactly the inner diameter of the circular hole. Finally, we demonstrate the reliability of the entire system as a MATLAB-based implementation of the GUI program, measuring the inner diameter of the circular hole through the circular holes of different dimensions measuring experiment.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.130-137
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• 2018

Recently, human life is getting longer due to change of living environment and development of medical technology, and silver medical technology has been in the limelight. Geriatric skin disease is difficult to detect early, and when it is missed, it becomes a malignant disease and is difficult to treatment. Melanoma is one of the most common diseases of geriatric skin disease and initially has a similar modality with the nevus. In order to overcome this problem, we attempted to perform a feature analysis in order to attempt automatic detection of melanoma-like lesions. In this paper, one is first order analysis using information of pixels in radiomic feature. The other is a gray-level co-occurrence matrix and a gray level run length matrix, which are feature extraction methods for converting image information into a matrix. The features were extracted through these analyses. And classification is implemented by SVM.

• Journal of Radiation Industry
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• v.12 no.4
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• pp.267-276
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• 2018

A Hoffman 3D Brain Phantom was used to evaluate two PET/CT scanners, BIO_40 and D_690, according to the radiation dose of CT (low, medium and high) at a fixed kilo-voltage-peak (kVp) with the tube current(mA) varied in 17~20 stages(Bio_40 PET/CT scanner: the tube voltage was fixed to 120 kVp, the effective tube current(mAs) was increased from 33 mAs to 190 mAs in 10 mAs increments, D_690 PET/CT scanner: the tube voltage was fixed to 140 kVp, tube current(mA) was increased from 10 mAs to 200 mAs in 10 mAs increments). After obtaining the PET image, an attenuation correction was conducted based on the attenuation map, which led to an analysis of the difference in the image. First, the ratio of white to gray matter for each scanner was examined by comparing the coefficient of variation (CV) depending on the average ratio. In addition, a blind test was carried out to evaluate the image. According to the study results, the BIO_40 and D_690 scanners showed a <1% change in CV value due to the tube current conversion. The change in the coefficients of white and gray matter showed that the Z value was negative for both scanners, indicating that the coefficient of gray matter was higher than that of white matter. Moreover, no difference was observed when the images were compared in a blind test.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.814-818
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• 2004

Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic and timing information besides has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing For off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods which effectively extracts skeleton through conditional test mask considering running time and quality. of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Watershed image conversion uses prewitt operator for gradient image conversion, extracts local minima considering 8-neighborhood pixel. And methods by using difference of mean value is used in region merging step, Converted watershed image by means of this methods separates effectively character region and background region applying to segmentation function. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1938-1945
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• 2001

In this paper, a new scheme for image conversion of the 2D input images into the stereoscopic 3D images by using differential shifting method is proposed. First, the relative depth information is estimated by disparity and occlusion information from the input stereo images and then, each of image objects are segmented by gray-level using the estimated information. Finally, through the differential shifting of the segmented objects according to the horizontal parallax, a stereoscopic 3D image having optimal stereopsis is reconstructed. From some experimental results, it is found that the horizontal disparity can be improved about 1.6dB in PSNR for the reconstructed stereo image using the proposed scheme through comparing to that of the given input image. In the experiment of using the commercial stereo viewer, the reconstructed stereoscopic 3D images, in which each of the segmented objects are horizontally shifted in the range of 4 ∼5 pixels are also found to have the mast improved stereopsis.

• Journal of IKEEE
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• v.24 no.1
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• pp.254-259
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• 2020

This paper is the implementation of the conversion system from image to music based on intentional synesthesia. The input image based on color, texture, and shape was converted into melodies, harmonies and rhythms of music, respectively. Depending on the histogram of colors, the melody can be selected and obtained probabilistically to form the melody. The texture in the image expressed harmony and minor key with 7 characteristics of GLCM, a statistical texture feature extraction method. Finally, the shape of the image was extracted from the edge image, and using Hough Transform, a frequency component analysis, the line components were detected to produce music by selecting the rhythm according to the distribution of angles.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.1-13
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• 2007

We make image that accumulate two principal component after change picture to use GLCM(Gray Level Co-Occurrence Matrix)'s texture feature information. And then these images use preprocess to achieved corner detection and area detection. Experiment results, two principle component conversion accumulation images had most informations about six kind textures by Eigen value 94.6%. When compared with red tide area that uses sea color and red tide area of image that have all principle component, displayed the most superior result. Also, we creates Euclidian space using Euclidian distance measurement about red tide area and clear sea. We identify of red tide area by red tide area and clear sea about random sea area through Euclidian distance and spatial distribution.