• Title/Summary/Keyword: color and texture

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Design of Block-based Image Descriptor using Local Color and Texture (지역 칼라와 질감을 활용한 블록 기반 영상 검색 기술자 설계)

  • Park, Sung-Hyun;Lee, Yong-Hwan;Kim, Youngseop
    • Journal of the Semiconductor & Display Technology
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    • v.12 no.4
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    • pp.33-38
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    • 2013
  • Image retrieval is one of the most exciting and fastest growing research fields in the area of multimedia technology. As the amount of digital contents continues to grow users are experiencing increasing difficulty in finding specific images in their image libraries. This paper proposes an efficient image descriptor which uses a local color and texture in the non-overlapped block images. To evaluate the performance of the proposed method, we assessed the retrieval efficiency in terms of ANMRR with common image dataset. The experimental trials revealed that the proposed algorithm exhibited a significant improvement in ANMRR, compared to Dominant Color Descriptor and Edge Histogram Descriptor.

Knit Design by Applying African Textile Pattern -Focused on Color Knit Jacquard- (아프리카 직물 문양을 응용한 니트디자인 -컬러 니트 자카드를 응용하여-)

  • Yoo, Kyung-Min;Kim, Young-Joo;Lee, Youn-Hee
    • Journal of the Korean Society of Clothing and Textiles
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    • v.31 no.9_10
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    • pp.1475-1486
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    • 2007
  • This study aims to develop knitted ware design to meet desire to express diversity in the modern fashion design so that we designed knitted ware by applying african geometric pattern and color to suggest new knitted ware design. We collect data about african texture pattern through technical books, publications, internet, and preceding research and visit and investigate the African museum. We investigate knitted Jacquard texture through preceding research and collect sample and data which is insufficient in the data source. The conclusions in this study are summarized as follows: First, African textile pattern is formulated with animism based on their religious view of art for a basis and African regards nature like animal and plant as a motive and interprets nature in the so that they can create symbolized geometric features that constitute African texture pattern. Those patterns is composed of extremely geometric figures so that they we fit to apply for color jacquad knit design. Second, color knitted jacquad can be distinguished by knitting method and status of knitting as 7 kinds of techniques such as Nomal, Bird'eye, Floating, Tubular, Ladder's back, Blister, Transfer Jacquard, and as a result of preceding research and knitting texture directly, jacquard technique makes different texture under same condition like consistent spinning rate and same crochet hook. Third, Bird'eye Jacquard used generally to make knitted ware and Ladder's back Jacquard, Tubular Jacquard used to make knitted ware light are fit to apply them to 7GG and 12GG machines. We design a cloak as a outer garment, a coat shaped like one-piece dress and a coat with hood by using Tubular Jacquard which can make thick texture and design a jacket, a skirt and a one-piece dress by using Bird'eye Jacquard. we make a light and flimsy one-piece dress by using Ladder's back Jacquard. Fourth, we apply the contrast of $4{\sim}6$ color and line and the contrast of texture and raw material to jacquard in order to emphasize texture property and visual property.

Formative Properties of Sensibility and Emotion in Fashion (패션에 나타난 감성과 감정의 조형적 특성 연구)

  • 김유진;이경희
    • Journal of the Korean Society of Clothing and Textiles
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    • v.28 no.1
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    • pp.34-44
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    • 2004
  • The purpose of this study was to provide effective design strategy and distinguish productions for the consumer's emotion satisfaction by analyzing formative properties of fashion sensibility and emotion. 54 photos of contemporary costume have been selected which represented the Izard' DES. The questionnaire consisted of bi-polar 25 pairs adjective scale of fashion sensibility and the 18 noun scale of emotion was distributed to 970 male and female living in Pusan area. The data were analyzed by GLM using the statistic SPSS package. The major findings of this research were as follows. 1. In the clothing formative properties following fashion sensibilities, aestheticism shows significant differences in the silhouette and texture, maturity in the silhouette and color, character in the texture and decoration and feminity in the pattern and color. 2. In the clothing formative properties following emotions, negative emotion shows significant differences in the pattern and silhouette, distressㆍfear in the silhouette and pattern, arousal in the texture and color, shame in the color and texture and enjoyment in the silhouette and pattern. 3. In the fashion sensibility and emotion following clothing formative properties, each formative property shows differences in fashion sensibility and emotion. This study result will be utilized in the clothing design development in special usage like theatrical costume, discriminated display and advertisement stratge.

Color & Texture Attribute Classification System of Fashion Item Image for Standardizing Learning Data in Fashion AI (패션 AI의 학습 데이터 표준화를 위한 패션 아이템 이미지의 색채와 소재 속성 분류 체계)

  • Park, Nanghee;Choi, Yoonmi
    • Journal of the Korean Society of Clothing and Textiles
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    • v.44 no.2
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    • pp.354-368
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    • 2020
  • Accurate and versatile image data-sets are essential for fashion AI research and AI-based fashion businesses based on a systematic attribute classification system. This study constructs a color and texture attribute hierarchical classification system by collecting fashion item images and analyzing the metadata of fashion items described by consumers. Essential dimensions to explain color and texture attributes were extracted; in addition, attribute values for each dimension were constructed based on metadata and previous studies. This hierarchical classification system satisfies consistency, exclusiveness, inclusiveness, and flexibility. The image tagging to confirm the usefulness of the proposed classification system indicated that the contents of attributes of the same image differ depending on the annotator that require a clear standard for distinguishing differences between the properties. This classification system will improve the reliability of the training data for machine learning, by providing standardized criteria for tasks such as tagging and annotating of fashion items.

A Study on Image Classification using Hybrid Method (하이브리드 기법을 이용한 영상 식별 연구)

  • Park, Sang-Sung;Jung, Gwi-Im;Jang, Dong-Sik
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.6 s.44
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    • pp.79-86
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    • 2006
  • Classification technology is essential for fast retrieval in large multi-media database. This paper proposes a combining GA(Genetic Algorithm) and SVM(Support Vector Machine) model to fast retrieval. We used color and texture as feature vectors. We improved the retrieval accuracy by using proposed model which retrieves an optimal feature vector set in extracted feature vector sets. The first performance test was executed for the performance of color, texture and the feature vector combined with color and texture. The second performance test, was executed for performance of SVM and proposed algorithm. The results of the experiment, using the feature vector combined color and texture showed a good Performance than a single feature vector and the proposed algorithm using hybrid method also showed a good performance than SVM algorithm.

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Implementation of the System Converting Image into Music Signals based on Intentional Synesthesia (의도적인 공감각 기반 영상-음악 변환 시스템 구현)

  • Bae, Myung-Jin;Kim, Sung-Ill
    • Journal of IKEEE
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    • v.24 no.1
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    • pp.254-259
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    • 2020
  • This paper is the implementation of the conversion system from image to music based on intentional synesthesia. The input image based on color, texture, and shape was converted into melodies, harmonies and rhythms of music, respectively. Depending on the histogram of colors, the melody can be selected and obtained probabilistically to form the melody. The texture in the image expressed harmony and minor key with 7 characteristics of GLCM, a statistical texture feature extraction method. Finally, the shape of the image was extracted from the edge image, and using Hough Transform, a frequency component analysis, the line components were detected to produce music by selecting the rhythm according to the distribution of angles.

A Study of the Image in Men's Hairstyle Depending on Hair Color and Texture (색채와 질감에 따른 남성 헤어스타일 이미지 연구)

  • Ha, Kyung-Yun;Lee, Myoung-Hee
    • The Research Journal of the Costume Culture
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    • v.16 no.2
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    • pp.293-304
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    • 2008
  • The objectives of this study were to investigate the images in men's hairstyle by hair color, tone, texture, and perceiver's gender, and to examine the characteristics of hairstyle appropriate to seasons. A quasi-experimental method by questionnaire was used, and the experimental design was $4{\times}3{\times}2{\times}2$(hair color$\times$tone$\times$texture$\times$perceiver's$\times$gender) factorial design. The subjects were 372 men and women in their 20s through 50s. five factors of men's hairstyle image were derived by factor analysis: individuality, dignity, romanticism, refinement, and activity. Black hair was perceived to be high in dignity and activity. Bright tone was perceived to be high in individuality, but low in dignity. Men's wave hair was perceived to be higher in individuality than straight hair, but lower in dignity. Perceiver's gender did not give significant influence on evaluation of all image factors. In brown, neutral tone was perceived to be higher in dignity. romanticism, and activity than dark or bright tone. In black, wave hair was perceived to be more refined than straight hair. Black hair matches with winter the most, and yellow matches with spring the most. In terms of tone, dark tone matches with winter; neutral tone matches with autumn; bright tone matches with summer. The results of this study verified that hair color and texture affect men's image perception, and matching hair colors are associated with seasons.

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Color Image Segmentation Based on Edge Salience Map and Region Merging (경계 중요도 맵 및 영역 병합에 기반한 칼라 영상 분할)

  • Kim, Sung-Young
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.3
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    • pp.105-113
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    • 2007
  • In this paper, an image segmentation method which is based on edge salience map and region merging is presented. The edge salience map is calculated by combining a texture edge map with a color edge map. The texture edge map is computed over multiple spatial orientations and frequencies by using Gabor filter. A color edge is computed over the H component of the HSI color model. Then the Watershed transformation technique is applied to the edge salience map to and homogeneous regions where the dissimilarity of color and texture distribution is relatively low. The Watershed transformation tends to over-segment images. To merge the over-segmented regions, first of all, morphological operation is applied to the edge salience map to enhance a contrast of it and also to find mark regions. Then the region characteristics, a Gabor texture vector and a mean color, in the segmented regions is defined and regions that have the similar characteristics, are merged. Experimental results have demonstrated the superiority in segmentation results for various images.

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Satellite Image Classification Based on Color and Texture Feature Vectors (칼라 및 질감 속성 벡터를 이용한 위성영상의 분류)

  • 곽장호;김준철;이준환
    • Korean Journal of Remote Sensing
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    • v.15 no.3
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    • pp.183-194
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    • 1999
  • The Brightness, color and texture included in a multispectral satellite data are used as important factors to analyze and to apply the image data for a proper use. One of the most significant process in the satellite data analysis using texture or color information is to extract features effectively expressing the information of original image. It was described in this paper that six features were introduced to extract useful features from the analysis of the satellite data, and also a classification network using the back-propagation neural network was constructed to evaluate the classification ability of each vector feature in SPOT imagery. The vector features were adopted from the training set selection for the interesting region, and applied to the classification process. The classification results showed that each vector feature contained many merits and demerits depending on each vector's characteristics, and each vector had compatible classification ability. Therefore, it is expected that the color and texture features are effectively used not only in the classification process of satellite imagery, but in various image classification and application fields.

Depth Image Upsampling Algorithm Using Selective Weight (선택적 가중치를 이용한 깊이 영상 업샘플링 알고리즘)

  • Shin, Soo-Yeon;Kim, Dong-Myung;Suh, Jae-Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.7
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    • pp.1371-1378
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    • 2017
  • In this paper, we present an upsampling technique for depth map image using selective bilateral weights and a color weight using laplacian function. These techniques prevent color texture copy problem, which problem appears in existing upsamplers uses bilateral weight. First, we construct a high-resolution image using the bicubic interpolation technique. Next, we detect a color texture region using pixel value differences of depth and color image. If an interpolated pixel belongs to the color texture edge region, we calculate weighting values of spatial and depth in $3{\times}3$ neighboring pixels and compute the cost value to determine the boundary pixel value. Otherwise we use color weight instead of depth weight. Finally, the pixel value having minimum cost is determined as the pixel value of the high-resolution depth image. Simulation results show that the proposed algorithm achieves good performance in terns of PSNR comparison and subjective visual quality.