• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.3_4
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• pp.402-411
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• 2002

The objective of this study was to investigate sensibility images of Korean traditional motifs cognized by college students in U.S.A. The subjects consisted of 217 male and 351 female undergraduate students. The experimental materials used in this study were 48 stimuli and questionnaires, composed of 7-point semantic differential scales of 15 bipolar adjectives. Twelve motifs selected from 3 groups of Korean motifs were used as motif stimuli. Twelve repeated patterns were constructed from them to be applied on a CAD-simulated dress. The data were analyzed by factor analysis, ANOVA, Duncan's multiple range test. The major finding were as follows: 1. Four dimensions were emerged accounting for the dimensional structure of the images of Korean traditional motifs. These dimensions were ‘quality’, ‘simplicity’, ‘cheerfulnees’, and ‘modernity’. Among them, ‘quality’and ‘simplicity’were the major dimensions. 2. Category, interpretation type, composition type, and application object had significant effects on the images of above-mentioned dimensions. The interpretation type had a significant effect on ‘quality’image, the composition type on ‘cheerful’image, and the application object on ‘modernity’image.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.79-84
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• 2023

Image generation models have been applied in various fields to overcome data sparsity, time and cost issues. However, it has limitations in generating images from regular pattern images and detecting defects in such data. In this paper, we verified the feasibility of the image generation model to generate pattern images and applied it to data augmentation for defect detection of OLED panels. The data required to train an OLED defect detection model is difficult to obtain due to the high cost of OLED panels. Therefore, even if the data set is obtained, it is necessary to define and classify various defect types. This paper introduces an OLED panel defect data acquisition system that acquires a hypothetical data set and augments the data with an image generation model. In addition, the difficulty of generating pattern images in the diffusion model is identified and a possibility is proposed, and the limitations of data augmentation and defect detection data augmentation using the image generation model are improved.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1186-1191
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• 1991

This paper represents a new edge relaxation algorithm that enhances the noisy boundary informations in images. The proposed algorithm employes relaxation process that reduces or eliminates ambiguities of derivative operator response via contextual informations. The contextual informations are the neighborhood patterns of a central edge which are estimated using fuzzy pattern matching technique. The algorithm is developed on crack edges. Experimental results show that the proposed scheme is effective even for noisy images or low contrast images.

• Journal of Integrative Natural Science
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• v.2 no.3
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• pp.202-206
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• 2009

Optical images based on the porous silicon exhibiting photoluminescence have been prepared from an electrochemical etching of n-type silicon wafer (boron-doped,<100> orientation, resistivity $1{\sim}10{\Omega}-cm$) by using a beam projector. The images remained in the substrate displayed an optical images correlating to the optical pattern and could be useful for optical data storage. This provides the ability to fabricate complex optical encoding in the surface of silicon.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.883-898
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• 1996

In this paper, we propose improved method to recognize the shape for enhancing the quality of the pattern recognition system by compressing the source images. In the proposed method, we reduced the data amount by skeletonizing the source images using mathematical morphology, and then matched patterns after accomplishing the translation and scale normalization, and rotation invariance on the transformed images. Through the scale normalization, it was possible for the shape recognition at minimum amount of the pixel by giving the weight to the skeleton pixel. As the source images was replaced by the skeleton images, it was possible to reduce the amount of data and computational loads dramatically, and so become much faster even with a smaller memory capacity. Through the experiment, we investigated the optimum scale factor and good result was proved when realizing the pattern recognition system.

• The Journal of Korean Medicine
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• v.27 no.2 s.66
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• pp.134-144
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• 2006

Tongue diagnosis is an important diagnostic method in traditional Oriental medicine. It has been especially accepted that quantitative analysis of tongue images allows the accurate diagnosis of the exterior-interior and cold-heat patterns of a patient. However, to ensure stable and reliable results, the color reproduction of such images must first be error-tree. Moreover, tongue diagnosis is much influenced by the surrounding illumination and subjective color recognition, so it has to be performed objectively and quantitatively using a digital diagnostic machine. In this study, 457 tongue images of outpatients were collected using the Digital Tongue Inspection System. Through statistical analysis, the result shows that the heat and cold patterns can be distinguished clearly based on the hue value of the tongue images. The average hue value (1.00) of the tongue's image in the cold pattern is higher than that in the heat pattern (0.99).

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.132-144
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• 1997

The rotation-invariant pattern recognition filter using circular harmonic function of the wavelet transforme dsreference image by morlet, mexican-hat, and haar wavelt function is proposed. The rotated reference images, the images sililar to the reference image, and the images which are added by random noise are used for the inpt images, and in case of the input images with random noise, they are applied to the recognition after removing the random noise by the transformed moving average method with proper thresholding value and window size. The proposed optical wavelet circular harmonic matched filter (WCHMF) is a type of the matche dfilter, so that it can be applied to the 4f vander lugt optical correlation system. SNR and discrimination capability of the proposed filter are compared with those of the conventional HF, the POCHF, and the BPOCHF. The proper wavelet function for the reference image used in this paper is achieved by applying morlet, mexican-hat, and harr wavelet function ot the proposed filter, and the proposed filter has good SNR and discrimination capability with rotation-invariance in case of the morlet wavelet function.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.8
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• pp.1194-1198
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• 2005

A computer vision system was designed and validated to recognize an individual Holstein cattle by processing images of their body patterns. This system involves image capture, image pre-processing, algorithm processing, and an artificial neural network recognition algorithm. Optimum management of individuals is one of the most important factors in keeping cattle healthy and productive. In this study, an image-processing system was used to recognize individual Holstein cattle by identifying the body-pattern images captured by a charge-coupled device (CCD). A recognition system was developed and applied to acquire images of 49 cattles. The pixel values of the body images were transformed into input data comprising binary signals for the neural network. Images of the 49 cattle were analyzed to learn input layer elements, and ten cattles were used to verify the output layer elements in the neural network by using an individual recognition program. The system proved to be reliable for the individual recognition of cattles in natural light.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.2
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• pp.200-205
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• 2006

Abstract This paper presents a personal identification method based on BMME and LDA for images acquired at anterior and posterior occlusion expression of teeth. The method consists of teeth region extraction, BMME, and pattern recognition forthe images acquired at the anterior and posterior occlusion state of teeth. Two occlusions can provide consistent teeth appearance in images and BMME can reduce matching error in pattern recognition. Using teeth images can be beneficial in recognition because teeth, rigid objects, cannot be deformed at the moment of image acquisition. In the experiments, the algorithm was successful in teeth recognition for personal identification for 20 people, which encouraged our method to be able to contribute to multi-modal authentication systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.120-127
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• 2016

In order to acquire digital x-ray images, developing radiography detectors have been recently conducted based on the DR (digital radiography) technology. The noise property of the radiography detector can be observed from measuring the NNPS (normalized noise power spectrum) using uniform exposure images. Here, the image difference of two images is used to remove the fixed pattern noise in measuring the detector NNPS. In this paper, two average images are first calculated using several images and then their difference is used to calculate an NNPS value. Here, the obtained NNPS value is usually lower than the true detector NNPS due to the average. Hence, a compensation constant, which is a function of the number of used images, is also proposed to compensate the NNPS value to obtain the true detector NNPS. Furthermore, another measurement method, in which the ratio of the average images is used, is proposed. Through NNPS measuring experiments using real x-ray images, it is observed that the proposed method can provide further accurate NNPS measurements.