• Korean Journal of Applied Biomechanics
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• v.31 no.2
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• pp.87-94
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• 2021

Objective: Identification of meaningful patterns and trends in large volumes of unstructured data is an important task in various research areas. In the present study, we gathered golf swing image data and did quantitative analysis of swing image. Method: We collected golf swing images of 30 novice players and 30 professional players in this study. Results: We selected important features of swing posture and employed data mining algorithm to classify whether a player is an expert or a novice. Moreover, our proposed method could offer quantitative advices for golf beginners for correcting their swing. Conclusion: Finally, we found a possibility that our proposed method can be expanded to golf swing correction system

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.323-333
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• 2023

Facial expression recognition can aid in the development of fatigue driving detection, teaching quality evaluation, and other fields. In this study, a facial expression recognition method was proposed with a residual masking reconstruction network as its backbone to achieve more efficient expression recognition and classification. The residual layer was used to acquire and capture the information features of the input image, and the masking layer was used for the weight coefficients corresponding to different information features to achieve accurate and effective image analysis for images of different sizes. To further improve the performance of expression analysis, the loss function of the model is optimized from two aspects, feature dimension and data dimension, to enhance the accurate mapping relationship between facial features and emotional labels. The simulation results show that the ROC of the proposed method was maintained above 0.9995, which can accurately distinguish different expressions. The precision was 75.98%, indicating excellent performance of the facial expression recognition model.

• Progress in Medical Physics
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• v.24 no.2
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• pp.99-107
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• 2013

The surgical resection was occurred mainly in liver metastasis before the development of radiation therapy techniques. Recently, Radiation therapy is increased gradually due to the development of radiation dose delivery techniques. 18F-FDG PET image showed better sensitivity and specificity in liver metastasis detection. This image modality is important in the radiation treatment with planning CT for tumor delineation. In this study, we applied automatic image segmentation methods on PET image of liver metastasis and examined the impact of image factors on these methods. We selected the patients who were received the radiation therapy and 18F-FDG PET/CT in Korea Cancer Center Hospital from 2009 to 2012. Then, three kinds of image segmentation methods had been applied; The relative threshold method, the Gradient method and the region growing method. Based on these results, we performed statistical analysis in two directions. 1. comparison of GTV and image segmentation results. 2. performance of regression analysis for relation between image factor affecting image segmentation techniques. The mean volume of GTV was $60.9{\pm}65.9$ cc and the $GTV_{40%}$ was $22.43{\pm}35.27$ cc, and the $GTV_{50%}$ was $10.11{\pm}17.92$ cc, the $GTV_{RG}$ was $32.89{\pm}36.8$4 cc, the $GTV_{GD}$ was $30.34{\pm}35.77$ cc, respectively. The most similar segmentation method with the GTV result was the region growing method. For the quantitative analysis of the image factors which influenced on the region growing method, we used the standardized coefficient ${\beta}$, factors affecting the region growing method show GTV, $TumorSUV_{MAX/MIN}$, $SUV_{max}$, TBR in order. The result of the region growing (automatic segmentation) method showed the most similar result with the CT based GTV and the region growing method was affected by image factors. If we define the tumor volume by the auto image segmentation method which reflect the PET image parameters, more accurate and consistent tumor contouring can be done. And we can irradiate the optimized radiation dose to the cancer, ultimately.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.553-558
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• 2002

Physical sensor model in pushbroom satellite images can be made from sensor modeling by rotation parameters and attitude parameters on the satellite track. These parameters are determined by the information obtained from GPS, INS, or star tracker. Provided from satellite image, an auxiliary data error is connected directly with an error of rotation parameters and attitude parameters. This paper analyzed how obtaining satellite images influenced errors of rotation parameters and attitude parameters. furthermore, for detailed analysis, this paper generated simulated satellite image, which was changed variously by rotation parameters and attitude parameters of satellite sensor model. Simulated satellite image is generated by using high-resolution digital aerial image and DEM (Digital Elevation Model) data. Moreover, this paper determined correlation of rotation parameter and attitude parameters through error analysis of simulated satellite image that was generated by various rotation parameters and attitude parameters.

• The KIPS Transactions:PartB
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• v.13B no.6 s.109
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• pp.591-600
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• 2006

This paper describes the development and implementation of a algorithm to decompose word images from image regions mixed text/graphics in document images using statistical analyses. To decompose word images from image regions, the character components need to be separated from graphic components. For this process, we propose a method to separate them with an analysis of box-plot using a statistics of structural components. An accuracy of this method is not sensitive to the changes of images because the criterion of separation is defined by the statistics of components. And then the character regions are determined by analyzing a local crowdedness of the separated character components. finally, we devide the character regions into text lines and word images using projection profile analysis, gap clustering, special symbol detection, etc. The proposed system could reduce the influence resulted from the changes of images because it uses the criterion based on the statistics of image regions. Also, we made an experiment with the proposed method in document image processing system for keyword spotting and showed the necessity of studying for the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.129.1-129
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• 2001

In this paper, we present an approach for matching images from finding interesting points and applying new image interpolation algorithm. New algorithms are developed that automatically align the input images match them and reconstruct 3-D surfaces. The interpolation algorithm is designed to cope with simple shapes. The proposed image interpolation algorithm generate a rotation image about vertical axes by an any angle from 4 base images. Each base image that was obtained from CCD camera has an angle difference of 90$^{\circ}$ The proposed image interpolation algorithm use the geometric analysis of image and depth information.

• Fashion & Textile Research Journal
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• v.3 no.3
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• pp.204-210
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• 2001

The purpose of the study is to clarify red image in the modem fashion. 40 kinds of costume samples being visual power in red have been selected from photographs in fashion magazines and divided into tones: pale (Vp, Lgr, L), bright (P, B), vivid (S, B, Dp), dark (Gr, Dl, Dgr, Dk). The study was measured by using Semantic Differential method. The subjects were 50 students majoring in clothing and textile. The data were analyzed by factor analysis, ANOVA, discrimminant analysis, MDS and regression analysis. The results of analysis are as follow; 1. Factor analysis has extracted 5 factors of red image in the fashion. These factor are Attractiveness, Hardness and Softness, Emotion, Attention, Simplicity. 2. There were significant difference in visual evaluation of red tones. 3. The discrimination among 4 red tones was related to attention and weight of red. 4. Evaluative dimensions of red was classified as Soft-Hard, Lively-Decent. 5. The image effect on Preference, Buying needs, Pleasant and Riches was consist of complicated sensibility.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.10
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• pp.48-58
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• 1998

We present a method that can recognize face images using independent component analysis that is used mainly for blind sources separation in signal processing. We assumed that a face image can be expressed as the sum of a set of statistically independent feature images, which was obtained by using independent component analysis. Face recognition was peformed by projecting the input image to the feature image space and then by comparing its projection components with those of stored reference images. We carried out face recognition experiments with a database that consists of various varied face images (total 400 varied facial images collected from 10 per person) and compared the performance of our method with that of the eigenface method based on principal component analysis. The presented method gave better results of recognition rate than the eigenface method did, and showed robustness to the random noise added in the input facial images.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.11
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• pp.1572-1578
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• 2003

Particle Image Thermometry(PIT) with liquid crystal tracers is used for visualizing and analysis of the bubbly flow in a vertical temperature gradient. Quantitative data of the temperature were obtained by applying the color-image processing to a visualized image, and neural-network was applied to the color-to-temperature calibration. This paper describes the method, and presents the transient mixing temperature patterns of the bubbly flow.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.1
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• pp.69-75
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• 2016

Polydimethylsiloxane (PDMS) is used as a scaffold for cell culture. Because both the stress and strain acting on the substrate and the hemodynamic environment are important for studying mechano-transduction of cellular function, the traction force of the surface of a substrate has been measured using fluorescence images of particle distribution. In this study, deformation of the cross-sectional plane of a PDMS block was measured by correlating particle image distributions to validate the particle image strain measurement technique. Deformation was induced by a cone indentor and a shearing parallel plate. Measured deformations from particle image distributions were in agreement with the results of a computational structure analysis using the finite-element method. This study demonstrates that the particle image correlation method facilitates measurement of deformation of a polymer scaffold in the cross-sectional plane.