• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.6
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• pp.164-172
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• 2023

The grain size distribution of sand provides crucial information for understanding coastal erosion and sediment deposition. The commonly used sieve analysis for grain size distribution analysis has limitations such as time-consuming processes and the inability to obtain information about individual particle shapes and colors. In this study, we propose a grain size distribution analysis method using smartphone digital images, which is simpler and more efficient than the sieve analysis method. During the image analysis process, we effectively detect particles from relatively low-resolution smartphone digital images by extracting particle boundaries through image gradient calculation. Using samples collected from four beaches in Gyeongsangbuk-do, we compare and validate the proposed boundary extraction image analysis method with the analysis method that does not extract boundaries, against sieve analysis results. The proposed method shows an average error rate of 8.21% at D₅₀, exhibiting a 65% lower error compared to the method without boundary extraction. Therefore, grain size distribution analysis using smartphone digital images is convenient, efficient, and demonstrated accuracy comparable to sieve analysis.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.571-582
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• 2018

Recently, development of deep learning has shown better image classification result than human. According to recent research, a hidden layer of deep learning is deeper, and a preservation of extracted features shows good results. However, in the case of general images, the extracted features are clear and easy to sort. This study aims to classify plant leaf images. This plant leaf image has high similarity in each image. Since plant leaf images have high similarity not only between images of different species but also within the same species, classification accuracy is not increased by simply extending the hidden layer or connecting the layers. Therefore, in this paper, we tried to improve the hidden layer of the algorithm called DenseNet which shows the recent excellent classification results, and compare the results of several different modified layers. The proposed method makes it possible to classify plant leaf images collected in a natural environment more easily and accurately than conventional methods. This results in good classification of plant leaf image data including unnecessary noise obtained in a natural environment.

• Journal of Oral Medicine and Pain
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• v.21 no.2
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• pp.255-264
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• 1996

This study was performed to demonstrate the method of image reformation for dental implants, using a personal computer with inexpensive softwares and to compare the images reformatted using the above method with those using Dentascan software. CT axial slices of 4 mandibles of 4 volunteers from GE Highspeed Advantage(GE Medical systems, U.S.A.) were used. personal computer used for image reformation was PowerWave 604/120 (Power computing Co, U.S.A. ) and softwares used were Osiris (Univ. Hospital of Geneva, Switzerland) and ImportACLESS Vl.1 (Designed Access Co., U.S.A.) for importing CT images and NIH image 1.58 (NIH, U.S.A.) for image processing. Seven image were selected among the serial reconstructed cross-sectional images produced by Dentascan. Seven resliced cross-sectional images at the same position were obtained at the personal computer. Regression analysis of the measurements of PC group was done against those of DS group. Measurements of the bone height and width at the reformer cross-sectional images using Mac-compatible computer was highly correlated with those using workstation with Dentascan software(height : r2= 0.999, p<0.001, width : r2= 0.993, p <0.001). So, it is considered that we can use a personal computer with inexpensive software for the dental implant planning, instead of the expensive software and workstation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3C
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• pp.387-397
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• 2004

The wavelet transform providing both of the frequency and spatial information of an image is proved to be very much effective for the compression of images, and recently lot of studies on coding algorithms for images decomposed by the wavelet transform together with the multi-resolution theory are going on. This paper proposes a quadtree decomposition method of image compression applied to the images decomposed by wavelet transform by using the correlations between pixels and '0'data grouping. Since the coefficients obtained by the wavelet transform have high correlations between scales and high concentrations, the quadtree method can reduce the data quantity effectively. the experimental infrared image with 256${\times}$256 size and 8〔bit〕, was used to compare the performances of the existing and the proposed compression methods.

• Journal of the Semiconductor & Display Technology
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• v.15 no.4
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• pp.97-102
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• 2016

Image stitching is a process of combining two or more images with overlapping area to create a panorama of input images, which is considered as an active research area in computer vision, especially in the field of augmented reality with 360 degree images. Image stitching techniques can be categorized into two general approaches: direct and feature based techniques. Direct techniques compare all the pixel intensities of the images with each other, while feature based approaches aim to determine a relationship between the images through distinct features extracted from the images. This paper proposes a novel image stitching method based on feature pixels with approximated clustering filter. When the features are extracted from input images, we calculate a meaning of the minutiae, and apply an effective feature extraction algorithm to improve the processing time. With the evaluation of the results, the proposed method is corresponding accurate and effective, compared to the previous approaches.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.6
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• pp.1382-1390
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• 1995

Electronic Speckle Pattern Interferometry (ESPI) with a CW laser, a video system and an image processor was utilized to measure the in-plane displacement. Unlike traditional strain gauges or Moire method. ESPI method measure the in-plane displacement on real time with out any surface preparation on surface attachment. The specimen has a crack of 10*0.1 mm in the middle of plate and strain gauge was also attached on that surface to compare with ESPI method. This study reveled the ESPI method to measure the displacement and distribution of strain in the specimen. It was shown in tensile tests that the measurement by ESPI method was comparable with strain gauge.

• Journal of the Korea Computer Industry Society
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• v.6 no.2
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• pp.265-270
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• 2005

Histogram is very sensitive in lighting because of feature between color space. When it has intensity of moved light, It may be possibility that similarity drop down, So In this paper, introduce new image retrieval method that calls HAC (Histogram Area Calculation). This method divides area of Histogram by a few area and calculate areas. The proposed method is to calculate area of Histogram and compare similarity based on feature that histogram has presently. Performance of our proposed method was verified more excellent than other Conventional method and Merged Color Histogram.

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.9-14
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• 2015

In this paper, we present an color quantization method by complementing the disadvantage of K-means color quantization that is one of the well-known color quantization. We named the proposed method "octree-means" color quantization. K-means color quantization does not use all of the clusters because it initializes the centroid of clusters with random value. The proposed method complements this disadvantage by using the octree color quantization which is fast and uses the distribution of colors in image. We compare the proposed method to six well-known color quantization methods on ten test images to evaluate the performance. The experimental results show 68.29 percent of mean square error(MSE) and processing time increased by 14.34 percent compared with K-means color quantization. Therefore, the proposed method improved the K-means color quantization and perform an effective color quantization.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.114-122
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• 1994

ESPE(Electonic-Speckle-Pattern-Interferometry) is very useful method for measuring In-plane displacement. Using the CW-Laser and Image processing system, it is possible to measure displacement and strain. Unlike traditional straingauge or moire' method, ESPI method requires no special surface preparation or attachments and can be measured In-plane displacement with no contact and real time. In this experimental specimen was loaded in paralled with loadcell, which provided loading step. The specimen was sheet plate, which was attached straingauge in x-y direction. In this study provides an example of how ESPI has been used to measure two dimensional displacement and strain distribution in this specimen. The results measured by ESPI compare with the data which was measured straingauge method in tensile testing at 1 ton range.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.105-108
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• 2002

This paper proposes a new watermarking algorithm to embed data in 1-bit images using edges for protecting illegal copies or modifications. This method is based on edge detection to decide the most invisible region. This paper also introduces a new shuffling method which embeds data in each blocks uniformly and finds Positions under the limited attacks. In experiment, we compare the proposed shuffling method with M. Wu's method.