• 복식
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• 제60권6호
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• pp.37-47
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• 2010

The purpose of this study was to investigate the effect of perceiver's gender, interval and color of checked pattern on clothing image. The experimental materials developed for this study were a set of stimulus and response scales. The stimuli were 16 color pictures, in which the perceiver's gender, interval(0.5cm, 1.5cm, 3.5cm, 5.5cm), and color(red, yellow, blue, purple) were manipulated. The 7-point scale was used for evaluation of clothing image. Data were obtained from 192 male college students and 192 female college students living in Seoul, Gwangju, Jinju, and Masan on December 2009. For data analysis, ANOVA and Duncan-test were used by using SPSS program. Results of this study were as follows.; Clothing image according to interval and color of checked pattern consisted of five dimensions of attractiveness, appeal, warmness, modesty, and freshness. Perceiver's gender showed an independent effect on appeal, modesty, and freshness. Interval showed an independent effect on appeal, warmness, modesty, and freshness. Also, interaction effects of Perceiver's gender and interval on appeal and freshness were found. Interaction effects of Perceiver's gender and color on appeal were found.

• 한국의류학회지
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• 제35권8호
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• pp.867-876
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• 2011

This study investigates the image of casual shirts according to color combination, tone, and interval of checked pattern in tone-in-tone coloration. The experimental materials developed for this study were a set of stimulus and response scales. The stimuli were 24 color pictures, in which color combination (RY: Red+Yellow, BP: Blue+Purple), tone (light, dull, dark), and interval (0.5cm, 1.5cm, 3.5cm, and 5.5cm) were manipulated. The 7-point scale was used for evaluation of image. Data were obtained from 240 female college students living in Seoul, Gwangju, Jinju, and Changwon in April 2010. For data analysis, ANOVA and Duncan-test were used by using SPSS program. The results of this study are as follows. Image according to color combination, tone, and interval of checked pattern consisted of five dimensions of attractiveness, youth- activity, appeal, modesty, and freshness. The cover combination showed an independent effect on freshness. Tone showed an independent effect on attractiveness, youth-activity, appeal, and modesty. Interval showed an independent effect on appeal, modesty, and freshness. Interaction effects of color combination and tone on youth-activity and appeal were found. In addition, interaction effects of tone and interval on attractiveness, youth-activity, and freshness were also found.

• Smart Structures and Systems
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• 제17권6호
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• 디지털산업정보학회논문지
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• 제9권2호
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• pp.111-119
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• 2013

Face recognition has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous applications, such as access control, surveillance, security, credit-card verification, and criminal identification. In this paper, we propose a simple descriptor called an ECSP(Extended Center-Symmetric Pattern) for illumination-robust face recognition. The ECSP operator encodes the texture information of a local face region by emphasizing diagonal components of a previous CS-LBP(Center-Symmetric Local Binary Pattern). Here, the diagonal components are emphasized because facial textures along the diagonal direction contain much more information than those of other directions. The facial texture information of the ECSP operator is then used as the input image of an image covariance-based feature extraction algorithm such as 2D-PCA(Two-Dimensional Principal Component Analysis). Performance evaluation of the proposed approach was carried out using various binary pattern operators and recognition algorithms on the Yale B database. The experimental results demonstrated that the proposed approach achieved better recognition accuracy than other approaches, and we confirmed that the proposed approach is effective against illumination variation.

• 복식문화연구
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• 제9권1호
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• pp.127-140
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• 2001

The purpose of this study is to examine the effect of the style of textile pattern design on the process of building the fashion brand identity. In so doing, the study analyzes the color, style, and layout of the motive, and the drawings of the patter of textile of top seven Italian fashion brands which present in presented eight fashion design collections during the 1997∼2000 period. The results of the analysis show that the seven brands exhibit their unique characteristics of the color, style, and layout of the motive, and the drawings of the pattern of textile. The results can be interpreted in a way that their distinct features oft textile pattern design indeed contribute toward the establishment of their unique brand image and brand identity. The results of this study suggests that to initiate the top fashion brand, the fashion industry should develop its own unique style of textile pattern design.

• 대한가정학회지
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• 제35권2호
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• pp.159-172
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• 1997

The purpose of this study was to investigate visual evaluation according to various methods of motif presentation and the value contrast between the motif and background. The instruments developed for this purpose were two sets of stimuli and a response scale. the first set consisted of pattern stimuli. they were eight photographs of floral patterns constructed by using six different motif presentation methods and two different value contrasts. The second set had eight clothing stimuli, photographs of clothings with the above floral patterns. The 7-point sementic differential scale of 19 bipolar adjectives was used as the response scale. The data was analyzed by factor analysis, ANOVA and T-test. The major findings from this study were as follows; 1. Four factors emerged to account for the dimensional structure of the floral pattern image. These factors were attractiveness, tenderness, attention, and maturity. among them attractiveness and tenderness were the major dimensions 2. The patterns and the clothings had no significant difference from each other in terms of attractiveness and tenderness, but in terms of maturity and attention. The pattern presented a cute and sober image, but the clothing presented mature and gorgeous image. 3. methods of motif presentation had significant effects on all the factors. The pattern by shading method gave the most attractive and soft image, the one by line the most soberest, the one by area the most gorgeous, the one by collage the most unattractive, hardest, and cutest, and the one by mosaics the maturest. 4. The value contrast between the motif and background had no significant effects on attractiveness and maturity, but on tenderness and attention. The patterns with a high valued background presented a soft image, but the one with a low valued background a hard image. The patterns with a low valued area presented gorgeous image.

• 한국의상디자인학회지
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• 제18권1호
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• pp.121-133
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• 2016

The purpose of this study is to recognize the differences of visual evaluation by variations in pattern and silhouette of the block dresses. The stimuli are 9 samples: 3 variations of the silhouette and 3 variations of the size of pattern. The data has been obtained from 55 fashion students and has been analyzed by using Factor Analysis, Anova, Scheffe's Test and the MCA method. The results of this study are as follows; 1) The visual evaluation by pattern and silhouette of block dresses are composed of 4 factors: lovable personality, physical characteristics, boldness, and simplicity. 2) Block dresses were evaluated to display the figure more efficiently, such as looking slimmer or taller, in the order of 2nd stage, 1st stage, and 3rd stage in every silhouette. As the patterns became bigger, straight silhouette dresses were judged to have bolder, more dignified images. 3) Block dresses were evaluated to have cute and lively images in order of hourglass silhouette, straight silhouette, and fitted silhouette in every pattern. They were evaluated to appear slimmer and taller in order of hourglass silhouette, fitted silhouette, and straight silhouette in every pattern. 1st stage and 2nd stage dresses were evaluated to have a bolder, more dignified image in order of fitted silhouette, hourglass silhouette, and straight silhouette. 4) The pattern and the silhouette of the block dresses interacted with boldness. These were the boldest, most dignified image in the fitted silhouette and 1st stage, while they were not judged so in the case of the straight silhouette and 1st stage. 5) According to the MCA regarding lovable personality and physical characteristics, the silhouette affected the visual image of the block dresses more than the pattern did. According to the MCA on simplicity, the pattern affected the visual image of the block dresses more than the silhouette.

• ETRI Journal
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• 제32권5호
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• pp.784-794
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• 2010

Automatic facial expression recognition has many potential applications in different areas of human computer interaction. However, they are not yet fully realized due to the lack of an effective facial feature descriptor. In this paper, we present a new appearance-based feature descriptor, the local directional pattern (LDP), to represent facial geometry and analyze its performance in expression recognition. An LDP feature is obtained by computing the edge response values in 8 directions at each pixel and encoding them into an 8 bit binary number using the relative strength of these edge responses. The LDP descriptor, a distribution of LDP codes within an image or image patch, is used to describe each expression image. The effectiveness of dimensionality reduction techniques, such as principal component analysis and AdaBoost, is also analyzed in terms of computational cost saving and classification accuracy. Two well-known machine learning methods, template matching and support vector machine, are used for classification using the Cohn-Kanade and Japanese female facial expression databases. Better classification accuracy shows the superiority of LDP descriptor against other appearance-based feature descriptors.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3943-3948
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• 2022

Single-photon emission computed tomography is one of the reliable pin-by-pin verification techniques for spent-fuel assemblies. One of the challenges with this technique is to increase the total fuel assembly verification speed while maintaining high verification accuracy. The aim of the present study, therefore, was to develop an artificial intelligence (AI) algorithm-based tomographic image analysis technique for partial-defect verification of fuel assemblies. With the Monte Carlo (MC) simulation technique, a tomographic image dataset consisting of 511 fuel-rod patterns of a 3 × 3 fuel assembly was generated, and with these images, the VGG16, GoogLeNet, and ResNet models were trained. According to an evaluation of these models for different training dataset sizes, the ResNet model showed 100% pattern estimation accuracy. And, based on the different tomographic image qualities, all of the models showed almost 100% pattern estimation accuracy, even for low-quality images with unrecognizable fuel patterns. This study verified that an AI model can be effectively employed for accurate and fast partial-defect verification of fuel assemblies.

• 복식문화연구
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• 제24권1호
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• pp.27-40
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• 2016

This study investigated the preference of sensibility expression factors regarding fashion materials, such as the color, pattern and texture of fabric. Moreover, this study analyzed the relationship between the preference of sensibility expression factors and the preference of fashion images by identifying the preference of fashion images. The survey subjects were 312 women ranging in age from 20 to 40 years old. This study utilized a questionnaire as a measurement tool. First, this study performed a factorial analysis on the preference of sensibility expression factors of fashion materials. In regards to color preference, this study considered color depth such as light tone color, moderate tone color, dark tone color and vivid tone color. In regards to pattern preference, this study examined: geometric pattern, floral pattern, animal skins pattern, check pattern and symbolical pattern. In regard to preference of the texture, this study assessed: roughness, luster, flatness and lightness. Second, this study performed a factorial analysis on the preference of fashion images. This study examined five factors: dignity, uniqueness, femininity, activity and simplicity. Third, this study analyzed the effects of the preference of sensibility expression factors of fashion materials on the preference of fashion images. As a result, the color preference was related to the image preference associated with dignity, femininity and simplicity, whereas the pattern preference was related to the images of uniqueness, femininity, activity and simplicity. Moreover, the preference of texture image was related to the images of dignity, uniqueness, femininity and activity.