• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.2
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• pp.193-208
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• 2020

This study investigated similarities and differences between 2D flat sketch, 3D virtual clothing and real clothing images. Flat sketch, 3D virtual clothing, and real clothing images of T-shirts and dresses were made. Questionnaires were prepared for fit evaluation, sensory evaluation, and location evaluation. A survey of 440 questionnaires was collected from Chinese women in their 20s and 30s. As results of the sensibility evaluation, 3D virtual clothing expressed real clothing images slightly more similar than a 2D flat sketch. As results of the fit evaluation of the dresses, 2D flat sketch and 3D virtual clothing were rated as slightly longer/wider, and real clothing images were rated as slightly shorter/narrower. The results suggested that presenting 3D images with avatars as 3D virtual clothing images will provide more accurate fit evaluation results. This study presented possibilities and methods for apparel companies to utilize 3D system as an effective apparel production tool.

• Journal of Korea Multimedia Society
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• v.12 no.7
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• pp.947-952
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• 2009

In this paper, we propose a method of generating color sketch images using the DIP operator. In the proposed method, an input RGB color image is first transformed into an HSV color image. A sketch image of the V component image is then extracted by applying the DIP operator to the V component image, which is the brightness component of the input image. For the visual convenience, the extracted sketch image of the V component image is next inverted and contrast-stretched. The S component image is also enhanced to deepen the color of output sketch image while maintaining its color. Finally, the V and S component images along with the original H component image are transformed into an output RGB color sketch image. Experimental results show that the proposed method yields output color sketch images similar to hand-drawn sketch pictures whose colors are the same as those of input color images.

• Journal of IKEEE
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• v.28 no.2
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• pp.209-220
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• 2024

A sketch is an intuitive means to express information, but compared to actual images, it has the problem of being highly abstract, diverse, and sparse. Recent advances in deep learning models have made it possible to discover features that are common to images and sketches. In this paper, we summarize recent trends in sketch-based image retrieval (SBIR) but it is not limited to SBIR. Besides SBIR, we also introduce sketch-based image recognition and generation studies. Zero-shot learning enables models to recognize categories not encountered during training. Zero-shot SBIR methods are also discussed. Commonly used free-hand sketch datasets are summarized and retrieval performance based on these datasets is reported.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.33-43
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• 2020

Retrieving a 3D model from a 3D database and augmenting the retrieved model in the Augmented Reality system simultaneously became an issue in developing the plausible AR environments in a convenient fashion. It is considered that the sketch-based 3D object retrieval is an intuitive way for searching 3D objects based on human-drawn sketches as query. In this paper, we propose a novel deep learning based approach of retrieving a sketch-based 3D object as for an Augmented Reality Model. For this work, we introduce a new method which uses Sketch CNN, Wasserstein CNN and Wasserstein center loss for retrieving a sketch-based 3D object. Especially, Wasserstein center loss is used for learning the center of each object category and reducing the Wasserstein distance between center and features of the same category. The proposed 3D object retrieval and augmentation consist of three major steps as follows. Firstly, Wasserstein CNN extracts 2D images taken from various directions of 3D object using CNN, and extracts features of 3D data by computing the Wasserstein barycenters of features of each image. Secondly, the features of the sketch are extracted using a separate Sketch CNN. Finally, we adopt sketch-based object matching method to localize the natural marker of the images to register a 3D virtual object in AR system. Using the detected marker, the retrieved 3D virtual object is augmented in AR system automatically. By the experiments, we prove that the proposed method is efficiency for retrieving and augmenting objects.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.11-20
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• 2006

This paper describes the technique which utilizes a fuzzy neural network to sketch feature extraction in digital images. We configure an artificial neural network and make it learn fuzzy membership functions to decide a local threshold applying to sketch feature extraction. To do this. we put the learning data which is membership functions generated based on optimal feature map of a few standard images into the artificial neural network. The proposed technique extracts sketch features in an images very effectively and rapidly because the input fuzzy variable have some desirable characteristics for feature extraction such as dependency of local intensity and excellent performance and the proposed fuzzy neural network is learned from their membership functions, We show that the fuzzy neural network has a good performance in extracting sketch features without human intervention.

• Journal of The Korean Digital Architecture Interior Association
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• v.6 no.2
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• pp.17-23
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• 2006

The purpose of this study was to investigate how student felt the strengths and shortness of presentation methods for formation of interior spaces. For this study, the process of the interior architecture design class was divided into three stages: the programming. the design development, and the design completion. In the design development stage, students used presentation methods: hand sketch, scale model, computer modeling, and virtual realty. The strengths of hand sketch was that quick expression. Models provided three-dimensional feelings. Computer modelling provide realistic color and texture. Virtual reality provided three-dimensional immersion and real scale. It is effective that students collect brain storm images using quick hand sketch in the beginning of design development stage. After that, they compose interior spaces in study models with small scale. Watching the models, they design details of spaces by using hand sketch and computer modelling. Using virtual reality, they can check the scale and circulation. Finally, they complete computer modelling by texture mapping and check the final design in virtual reality.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.703-712
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• 2003

With the explosive growth n the numbers and sizes of imaging technologies, Content-Based Image Retrieval (CBIR) has been attacked the interests of researchers in the fields of digital libraries, image processing, and database systems. In general, in the case of query-by-image, in user has to select an image from database to query, even though it is not his completely desired one. However, since query-by-sketch approach draws a query shape according to the user´s desire it can provide more high-level searching interface to the user compared to the query-b-image. As a result, query-by-sketch has been widely used. In this paper, we propose a Java-based image retrieval system that consists of sketch query and image classification. We use two features such as color histogram and Haar wavelets coefficients to search similar images. Then the Leave-One-Out method is used to classify database images. The categories of classification are photo & painting, city & nature, and sub-classification of nature image. By using the sketch query and image classification, w can offer convenient image retrieval interface to user and we can also reduce the searching time.

• Journal of The Korean Digital Architecture Interior Association
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• v.6 no.2
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• pp.25-30
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• 2006

The purpose of this study was to investigate how student felt the strengths and shortness of presentation methods for formation of interior spaces. For this study, the process of the interior architecture design class was divided into three stages: the programming. the design development, and the design completion. In the design development stage, students used presentation methods: hand sketch, scale model, computer modeling, and virtual realty. The strengths of hand sketch was that quick expression. Models provided three-dimensional feelings. Computer modelling provide realistic color and texture. Virtual reality provided three-dimensional immersion and real scale. It is effective that students collect brain storm images using quick hand sketch in the beginning of design development stage. After that, they compose interior spaces in study models with small scale. Watching the models, they design details of spaces by using hand sketch and computer modelling. Using virtual reality, they can check the scale and circulation. Finally, they complete computer modelling by texture mapping and check the final design in virtual reality.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.17-25
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• 2023

In this paper, we propose a lightweight deep learning architecture tailored for efficient text detection in fashion design sketch images. Given the increasing prominence of Digital Transformation in the fashion industry, there is a growing emphasis on harnessing digital tools for creating fashion design sketches. As digitization becomes more pervasive in the fashion design process, the initial stages of text detection and recognition take on pivotal roles. In this study, a lightweight network was designed by building upon existing text detection deep learning models, taking into consideration the unique characteristics of apparel design drawings. Additionally, a separately collected dataset of apparel design drawings was added to train the deep learning model. Experimental results underscore the superior performance of our proposed deep learning model, outperforming existing text detection models by approximately 20% when applied to fashion design sketch images. As a result, this paper is expected to contribute to the Digital Transformation in the field of clothing design by means of research on optimizing deep learning models and detecting specialized text information.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.4
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• pp.26-31
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• 2004

Due to the recent explosive progress of Web, We can easily access a large number of images from m. In this paper, we describe our approach of developing a general purpose content based image retrieval system over the H using a Web agent. The Web agent extracts text information of images from the links and file contents in HTML. The proposed system retrieves the images from database using the query by sketch and the query by example on Web browser. Experimental results demonstrate the effectiveness of the new approach.