• Journal of Magnetics
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• v.18 no.3
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• pp.311-316
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• 2013

Digital image processing has increasingly been implemented in nanostructural analysis and would be an ideal tool to characterize the morphology and position of self-assembled magnetic nanoparticles for high density recording. In this work, magnetic nanoparticles were synthesized by the modified polyol process using $Fe(acac)_3$ and $Pt(acac)_2$ as starting materials. Transmission electron microscope (TEM) images of as-synthesized products were inspected using an image processing procedure. Grayscale images ($800{\times}800$ pixels, 72 dot per inch) were converted to binary images by using Otsu's thresholding. Each particle was then detected by using the closing algorithm with disk structuring elements of 2 pixels, the Canny edge detection, and edge linking algorithm. Their centroid, diameter and area were subsequently evaluated. The degree of polydispersity of magnetic nanoparticles can then be compared using the size distribution from this image processing procedure.

• Journal of Computing Science and Engineering
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• v.11 no.1
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• pp.24-31
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• 2017

Face-based video retrieval has become an active and important branch of intelligent video analysis. Face profiling and matching is a fundamental step and is crucial to the effectiveness of video retrieval. Although many algorithms have been developed for processing static face images, their effectiveness in face-based video retrieval is still unknown, simply because videos have different resolutions, faces vary in scale, and different lighting conditions and angles are used. In this paper, we combined content-based and semantic-based image analysis techniques, and systematically evaluated four mainstream local features to represent face images in the video retrieval task: Harris operators, SIFT and SURF descriptors, and eigenfaces. Results of ten independent runs of 10-fold cross-validation on datasets consisting of TED (Technology Entertainment Design) talk videos showed the effectiveness of our approach, where the SIFT descriptors achieved an average F-score of 0.725 in video retrieval and thus were the most effective, while the SURF descriptors were computed in 0.3 seconds per image on average and were the most efficient in most cases.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.660-677
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• 2013

The blending of defective texture with the ambience texture results in camouflage. The gray value or color distribution pattern of the camouflaged images fails to reflect considerable deviations between the camouflaged object and the sublimating background demands improved strategies for texture analysis. In this research, we propose the implementation of an initial enhancement of the image that employs line masks, which could result in a better discrimination of the camouflaged portion. Finally, the gray value distribution patterns are analyzed in the enhanced image, to fix the camouflaged portions.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.5
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• pp.53-58
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• 2003

Wear debris can be collected from the lubricants of operating machinery and its morphology is directly related to the fiction condition of the interacting materials from which the wear particles originated in lubricated machinery. But in order to predict and estimate working conditions, it is need to analyze the shape characteristics of wear debris and to identify. Therefore, if the shape characteristics of wear debris is identified by computer image analysis and the neural network, The four parameter (50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction. It is shown that identification results depend on the ranges of these shape parameters learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by neural network. We resented how the neural network recognize wear debris on driving condition.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.223-224
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• 2019

본 논문에서는 카메라의 실시간 영상에서 얻을 수 있는 데이터를 수집 및 분석하여 일반인들에게 스마트폰의 실제 사용량, 최적화면 표현, 그리고 건조증 위험도의 정보를 제공하는 "i-eye" 응용 앱을 제안하여 눈 건강관리를 가능하게 한다. 제안하는 앱은 발전된 스마트 폰을 기반으로 동작되며 아이트래킹(eye-gaze tracking), 영상거리측정(image distance measurement), 눈 데이터분석(eye data analysis)의 3가지 핵심기술을 제안한다.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.58-64
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• 2022

Breast ultrasonic reading is critical as a primary screening test for the early diagnosis of breast cancer. However, breast ultrasound examinations show significant differences in diagnosis based on the difference in image quality according to the ultrasonic equipment, experience, and proficiency of the examiner. Accordingly, studies are being actively conducted to analyze the texture characteristics of normal breast tissue, positive tumors, and malignant tumors using breast ultrasonography and to use them for computer-assisted diagnosis. In this study, breast ultrasonography was conducted to select 247 ultrasound images of 71 normal breast tissues, 87 fibroadenomas among benign tumors, and 89 malignant tumors. The selected images were calculated using a statistical method with 21 feature parameters extracted using the gray level co-occurrence matrix algorithm, and classified as normal breast tissue, benign tumor, and malignancy. In addition, we proposed five feature parameters that are available for computer-aided diagnosis of breast cancer classification. The average classification rate for normal breast tissue, benign tumors, and malignant tumors, using this feature parameter, was 82.8%.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.197-198
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• 2021

반려동물에 대한 인식변화와 고령화, 저출산 문제로 반려동물을 키우는 사람이 계속해서 증가하고 있다. 하지만 반려동물을 유기하는 경우도 많아져 정부에서는 반려동물 등록제를 시행하여 동물 유기를 예방하고 있다. 그럼에도 불구하고 동물 등록 절차의 번거로움과 부작용 우려로 인해 많은 사람이 등록을 하고 있지 않는 실태이다. 본 논문에서는 딥러닝 이미지 분석을 활용한 동물 외형분석 기술을 제안한다. 제안하는 기술은 동물 이미지에서 특징점 추출을 위해 CNN과 구글에서 제공하는 딥러닝 프레임워크인 텐서플로우(TensorFlow)를 활용하며 동물의 외형을 분석해 동물의 고유한 외형 정보를 얻을 수 있다. 이를 통해 각 개체를 특정할 수 있어 현재 시행되고 있는 동물 등록방법을 대체하여 동물 유기문제 해결에 기여할 것으로 기대한다.

• Nonlinear Functional Analysis and Applications
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• v.29 no.3
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• pp.841-865
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• 2024

In this research, we propose a new efficient iterative method for fixed point problems of generalized α-nonexpansive mappings. We show the weak and strong convergence analysis of the proposed method under some mild assumptions on the control parameters. We consider the application of the new method to some real world problems such as convex minimization problems, image restoration problems and impulsive fractional differential equations. We carryout a numerical experiment to show the computational advantage of our method over some well known existing methods.

• The Journal of the Acoustical Society of Korea
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• v.15 no.6
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• pp.90-98
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• 1996

In this paper we have proposed the sign language transformation system for deaf based on a morpheme analysis. The proposed system extracts phoneme components and connection informations of the input character sequence by using a morpheme analysis. And then the sign image obtained by component analysis is correctly and automatically generated through the sign image database. For the effective sign language transformation, the language description dictionary which consists of a morpheme analysis part for analysis of input character sequence and sign language description part for reference of sign language pattern is costructed. To avoid the duplicating sign language pattern, the pattern is classified a basic, a compound and a similar sign word. The computer simulation shows the usefulness of the proposed system.

• Korean Journal of Community Nutrition
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• v.4 no.4
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• pp.561-567
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• 1999

This study was conducted to provide information about weight control behavior in adolescent females. To explain the behavior intention of dieting, conceptual framework based on "Social Support, Control and the Stress Process Model" and "Theory of Reasoned Action" was used. The survey was carried out by self-questionnaires with 463 female high school and college students in Daegu. Analysis of data was done using mean, correlation and multiple regression analysis with the SAS computer program. A society preoccupied with thinness gives a burden to women, and this burden may stress dissatisfaction with body image. Social perception of ideal body image except parents' perception, and salient others'perception, and salient others' expectation of subjects' body image except parents' expectation, were much thinner than normal figures in this study. The influencing factors for behavior intention of dieting of the subjects were perceived stress and attitude toward diet behavior, especially beliefs of behavioral outcome. Influencing factors related to perceived stress-that is dissatisfaction of body image-were current figure, social perception of body image, effect of mass communication and others' estimation of subjects' body image with self-comparison with others, in order.th others, in order.