• 복식
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• 제49권
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• pp.65-72
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• 1999

The purpose of this study was to investigate the relationships between body-calthexis and clothing image preferences in male college students. The sample included 28 male college students and an instrument was developed based on the previous studies. The statistical analyses used for this study were factor analysis cluster analysis and t-test. The result of factor analysis showed that body-cathexis consisted of four areas of body parts: face/head upper body middle body and lower/total body. Clothing image preferences consisted of 'strong vs weak' 'soft vs hard' 'young vs mature' 'mannis vs feminine' and 'distinguished vs undistinguished' images. Cluster analysis revealed that male college students are segmented into two groups. and the two groups differed in regard to clothing image preferences such as 'strong vs weak' 'young vs mature' and 'mannish vs feminine' images. In addition the two consumer segments were different concerning body-cathexis for middle body and all body areas combined. The consumers who preferred feminine weak and mature clothing images were more satisfied with their middle area of the bodies and all body areas combined.

• 한국표면공학회지
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• 제56권6호
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• pp.353-370
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• 2023

Corrosion detection and analysis is a very important topic in reducing costs and preventing disasters. Recently, image processing techniques have been widely applied to corrosion identification and analysis. In this work, we briefly introduces traditional image processing techniques and machine learning algorithms applied to detect or analyze corrosion in various fields. Recently, machine learning, especially CNN-based algorithms, have been widely applied to corrosion detection. Additionally, research on applying machine learning to region segmentation is very actively underway. The corrosion is reddish and brown in color and has a very irregular shape, so a combination of techniques that consider color and texture, various mathematical techniques, and machine learning algorithms are used to detect and analyze corrosion. We present examples of the application of traditional image processing techniques and machine learning to corrosion detection and analysis.

• 한국의상디자인학회지
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• 제2권2호
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• pp.155-171
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• 2000

This study is to measure and evaluate the sensibility image for textile pattern design based on the generation. Ten patterns classified by a practical survey on the market are presented. A questionnaire has 14 sensibility related words scaled by 7 point semantic differential method. The practical research is performed for 200 women screened by sensibility test for individual character analysis based on the generation. Each subject is answered by a face-to-face interview method to improve survey's accuracy, For statistical test about differences in treatment means, SAS package is used and analyzed through ANOVA, significance probability and mean, In summary, this paper has proposed the sensibility image scale for apparel pattern design to satisfy individual sensibility, The results of this study can be effectively applied to develop textile pattern design based on human sensibility.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 추계학술발표대회
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• pp.351-354
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• 2011

This paper discusses on facial features extraction based on proposed skin color model. Different parts of face from input image are segmented based on skin color model. Moreover, this paper also discusses on concept to detect the eye and mouth position on face. A height and width ratio (${\delta}=1.1618$) based technique is also proposed to accurate detection of face region from the segmented image. Finally, we have cropped the desired part of the face. This exactly exacted face part is useful for face recognition and detection, facial feature analysis and expression analysis. Experimental results of propose method shows that the proposed method is robust and accurate.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.75-80
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• 2002

The mainly used technique to rectify satellite images with distortion is to develop a mathematical relationship between the pixel coordinates on the image and the corresponding points on the ground. By defining the relationship between two coordinate systems, a polynomial model is designed and various linear transformations are used. These GCP based geometric correction has performed overall plane to plane mapping. In the overall plane mapping, overall structure of a scene is considered, but local variation is discarded. The highly variant height of region is resampled with distortion in the rectified image. To solve this problem this paper proposed the TIN-based rectification on a satellite image. The TIN based rectification is good to correct local distortion, but insufficient to reflect overall structure of one scene. So, this paper shows the experimental result and the analysis of each rectification model. It also describes the relationship GCP distribution and rectification model. We can choose a geometric correction model as the structural characteristic of a satellite image and the acquired GCP distribution.

• 한국실내디자인학회논문집
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• 제20권2호
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• pp.20-29
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• 2011

This research is based on the environmental psychology model of Albert Mehrabian & JAMES a. Russell. The purpose of this research is to search a method of planning a spatial image improving the degree of access that is audience's dependent response to a display space image of a museum for children. A museum for children is the place for education with experience and its main audience is children and parents. It indicates with a basis of the environmental psychology model that a designer needs to consider the emotional response of children and parents in designing the space. The space design starts from a plan of space image that is delivered to audience through the five senses. Image on the space means visual image as people acquire information mostly through the sense of sight. Visual image consists of shape, the feel of a material, and color that is the most influential factor to the sensibility of audience. Therefore, firstly, this research measures the degree of audience's approach and avoidence on image of display space. In addition, this research suggests the improvement method by analyzing differences on the access of each space and audience based on visual image. Secondly, four factors are extracted through factor analysis based on the result of adjective survey result.

• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• 정보처리학회논문지B
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• 제9B권3호
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• pp.327-336
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• 2002

텍스쳐 분석은 표면, 물체, 모양, 깊이 인식 등의 많은 영상 이해 분야에서 활용되는 가장 중요한 인식 기술 중의 하나이다. 그러나 기존의 방법들은 다중 텍스쳐 영상에 내재된 텍스쳐 성분의 인식 정보를 활용할 수 없는 분할만을 목적으로 하고 있으며, 내재된 텍스쳐 인식을 기반으로 하는 비교사적인 방법에 관한 연구는 거의 이루어지고 있지 않은 실정이다. 따라서 본 논문에서는 텍스쳐 성분을 방향장(orientation-field) 특징 정보인 방향각과 방향강도로 정의하고 블록-기반 자기조직화 신경회로망에 의해서 비교사적으로 영상 내에 존재하는 텍스쳐 영역을 군화(clustering) 및 통합(merging) 처리에 의해서 식별한다. 또한 제안된 알고리즘의 성능 평가를 위해서는 다양한 형태의 다중 텍스쳐 영상을 생성하여 블록 기반의 불림(dilation) 및 윤곽 검출 과정을 통해서 영상에 내재하는 텍스쳐 영역을 분할함으로써 그 유효성을 보인다.

• Journal of the Korean Data and Information Science Society
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• 제19권2호
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• pp.475-485
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• 2008

One of main issues in watermarking is to resolve the strength of watermark for solving the problem of trade-off between fidelity and robustness of watermarking. In the previous research, the strength of watermark has been resolved fixed value generally without considering local image characteristics such as image brightness, contrast, and edge. This paper proposes a new model to predict the strength of watermark considering local image characteristics such as image brightness, contrast, and edge for digital wavelet transform(DWT)-based image watermarking. For the study, psychological experiment was fulfilled to measure the human image perception and regression analysis showed the proposed model was statistically significant at the level of ${\alpha}\;=\;0.01$. Also the model is practically validated on fidelity and robustness of watermarking.

• Journal of Information Processing Systems
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• 제14권5호
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• pp.1293-1300
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• 2018

For the disadvantages of multi-scale geometric analysis methods such as loss of definition and complex selection of rules in image fusion, an improved multi-focus image fusion method is proposed. First, the initial fused image is quickly obtained based on the lifting stationary wavelet transform, and a simple normalized cut is performed on the initial fused image to obtain different segmented regions. Then, the original image is subjected to NSCT transformation and the absolute value of the high frequency component coefficient in each segmented region is calculated. At last, the region with the largest absolute value is selected as the postfusion region, and the fused multi-focus image is obtained by traversing each segment region. Numerical experiments show that the proposed algorithm can not only simplify the selection of fusion rules, but also overcome loss of definition and has validity.