KANSEI Based Clothing Fabric Image Retrieval

Chen, Yen‐Wei; Sobue, Shota; Huang, Xinyin

doi:10.1007/978-3-642-03265-3_8

Cited by 13 publications

(13 citation statements)

References 12 publications

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“…Then we e used a neural network to learn mapping functions between color image (painting) features and impressions for 4 group subjects (Children, students, adults, elderly person). We also developed a KANSEI based cloth fabric image retrieval system by using the learned mapping function [3]. The limitation of our previous works is that we use only global image features for impression estimation.…”

Section: Introductionmentioning

confidence: 99%

Global and local features for accurate impression estimation of cloth fabric images

Huang

Chen

Han

et al. 2013

Proceedings of the 2013 IEEE/SICE International Symposium on System Integration

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Consumers' psychological feeling or impression is an important factor for product design. The impression estimation becomes an important issue. In this paper, we proposed a machine learning based impression estimation method for cloth fabric images. We use a semantic differential (SD) method to measure the user's impression such as bright, warm while they viewing a cloth fabric image. We also extract both global and local features of cloth fabric images such as color and texture using computer vision techniques. Then we use support vector regression to model the mapping function between the impression and image features. The learned mapping function is used to estimate the impression of cloth fabric images.

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Section: Introductionmentioning

confidence: 99%

Global and local features for accurate impression estimation of cloth fabric images

Huang

Chen

Han

et al. 2013

Proceedings of the 2013 IEEE/SICE International Symposium on System Integration

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“…Hunt-Johnson et al investigated the effects of differences in clothing style on the impression of sociability (Hunt-Johnson et al, 1977). Chen et al (2009) investigated images of clothing fabric according to kansei, a Japanese term relating to psychological expression. Ericksen et al (1992) researched the clothing preferences of employed females taking into account self-image congruence and career anchorage.…”

Section: Introductionmentioning

confidence: 99%

Comparison of elegance of Japanese and European jackets

Kim

Nozawa

Takatera

2015

International Journal of Clothing Science and Technology

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Purpose: This study investigates factors affecting the impression of elegance of a jacket's appearance.Design/methodology/approach: A questionnaire survey on the impression of jacket appearance was conducted using images of jackets of Japanese and European brands. A paired comparison and sensory test were carried out for four Japanese and European jackets. To explain different jacket appearances, the jacket patterns and silhouettes were investigated from an engineering point of view.Findings: Most Japanese subjects responded that European jackets in images were more elegant and characteristic of European style. In a comparison of jacket silhouettes, Jacket 1 (European brand) was evaluated as the most elegant. The waist and bust parts of jacket 1 had three-dimensional shape whereas the Japanese jackets had planar and rectilinear shapes. This was due to the difference in the waist darts and curved lines in the patterns. Jacket appearance in terms of elegance is thus mainly affected by the waist and bust shapes, which are affected by darts and lines in the patterns.Originality/value: This is pioneering research on the elegance of garment appearance from an engineering point of view, using actual clothing. The comparison results for commercial jackets will be valuable to the apparel industry.

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“…16 These frameworks all obtain satisfactory results but are only suitable for patterned fabric. For fabric image retrieval, texture extraction methods have been performed by Fourier transform (FT) 19 and Gabor filters, 19,20 LBP descriptors, 21 fractal-based texture, 22 scale-invariant feature transform (SIFT), 23 and deep learning. 24 To meet the factory requirements, the image retrieval of wool fabric includes two parts: texture and color.…”

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confidence: 99%

“…FT is suitable for extracting periodic features, but how to reflect the differences is the main problem. The FT feature proposed by Chen et al 19 only have two values, making different wool fabrics difficult to distinguish. Moreover, some patterns in patterned fabrics are aperiodic and the surfaces of wool fabrics are dark and blurring.…”

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confidence: 99%

Image retrieval of wool fabric. Part I: Based on low-level texture features

Zhang

Xiang

Wang

et al. 2019

Textile Research Journal

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With huge and ever-growing products in the factory, image retrieval can help the worker retrieve the same, or similar, existing products rapidly and accurately to guide production. In this paper, an effective method based on Fourier transform and local binary pattern is proposed to improve the retrieval efficiency of wool fabric. After capturing the fabric image, histogram equalization was implemented on the value of the Hue, Saturation, Value (HSV) mode to enhance the contrast. Subsequently, Fourier transform together with local binary pattern operator were performed to obtain the frequency spectrum and the local binary pattern, respectively. Each frequency spectrum was divided into 22 rings with the same width, and the standard deviation of the frequencies in each ring was calculated as a Fourier feature. Distinct output values of each local binary pattern were counted and normalized as local binary pattern features. Finally, Euclidean distance was adopted to measure the similarity based on the Fourier feature and local binary pattern feature. Twenty thousand wool fabric images were captured to demonstrate the efficacy of the proposed method. Experimental results indicate that the framework is effective and superior for image retrieval of wool fabric, providing referential assistance for the worker in the factory and improving retrieval efficiency.

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KANSEI Based Clothing Fabric Image Retrieval

Cited by 13 publications

References 12 publications

Global and local features for accurate impression estimation of cloth fabric images

Global and local features for accurate impression estimation of cloth fabric images

Comparison of elegance of Japanese and European jackets

Image retrieval of wool fabric. Part I: Based on low-level texture features

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