• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.2
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• pp.321-330
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• 2022

This study analyzed the difference between 2D image and 3D virtual clothing images based on stripe arrangement to obtain fundamental data for slim appearance. First, the slimming effect according to the three types of stripe ratio was examined. Subsequently, the slimming effects of seven types of one-piece dress designs according to the stripe location were analyzed. Subjective ranking was evaluated. The width items and radius of curvature were measured for the image's respective parts. Consequently, in 2D image and 3D virtual clothing images, the one with the narrowest stripe ratio was evaluated as the slimmest; however, the conditions for the slimming effect were different. In the seven one-piece dress designs, a difference was apparent in the ranking of the 2D image and 3D virtual clothing images. In the 3D virtual clothing image, arranging the stripes on the entire garment proved inefficient. The stripes were curved according to the curvature of the human body, creating an optical illusion that differed from that of the 2D image.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.553-560
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• 2014

In this paper, we propose a method to convert 2D image to 3D anaglyph using quadratic & cubic B$\acute{e}$zier Curves in HTML5. In order to convert 2D image to 3D anaglyph image, we filter the original image to extract the RGB color values and create two images for the left and right eyes. Users are to set up the depth values of the image through the control point using the quadratic and cubic B$\acute{e}$zier curves. We have processed the depth values of 2D image based on this control point to create the 3D image conversion reflecting the value of the control point which the users select. All of this work has been designed and implemented in Web environment in HTML5. So we have made it for anyone who wants to create their 3D images and it is very easy and convenient to use.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1897-1903
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• 2011

This paper discusses a 2D/3D conversion of images using technologies like object extraction and depth-map creation. The general procedure for converting 2D images into a 3D image is extracting objects from 2D image, recognizing the distance of each points, generating the 3D image and correcting the image to generate with less noise. This paper proposes modified new methods creating a depth-map from 2D image and recognizing the distance of objects in it. Depth-map information which determines the distance of objects is the key data creating a 3D image from 2D images. To get more accurate depth-map data, noise filtering is applied to the optical flow. With the proposed method, better depth-map information is calculated and better 3D image is constructed.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.121-126
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• 2002

The stereoscopic image is that we can see it closer than a real thing compared to 2D image, and it has influence on human's vision information because it is more natural method to feel connections between the spaces of the image and himself. There are several method convert from 2d image to 3d image. But, in this paper, we are propose the image separate algorithm of continuous input system through a spatial analysis, not be done with 2D still image. Additionally, we will adapt to the moving vector which has been used in MPEG. In this experiment, we obtained the effect of 3D image.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.479-486
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• 2016

In this paper, the algorithm which can convert a 2D image into a 3D Model will be discussed. The 2D picture drawn by a user is scanned for image processing. The Canny algorithm is employed to find the contour. The waterfront algorithm is proposed to find foreground image area. The foreground area is segmented to decompose the complex shapes into simple shapes. Then, simple segmented foreground image is converted into 3D model to become a complex 3D model. The 3D conversion formular used in this paper is also discussed. The generated 3D model data will be useful for 3D animation and other 3D contents creation.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.319-330
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• 2011

For objective assessment of stereoscopic 3D image quality, we measure quality of left and right image with 2D image quality measurement method. However, this method is inconvenient because that we have to measure quality of left and right image individually. Therefore we propose a method of stereoscopic 3D image quality assessment using one overlaid image with left and right image. Using this method, One can measure quality of stereoscopic 3D image more easily and quickly.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.35-47
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• 2018

The 4th industrial revolution, digital image technology has developed beyond the limit of multimedia industry to advanced IT fusion and composite industry. Particularly, application technology related to HCI element algorithm in 3D image object recognition field is actively developed. 3D image object recognition technology evolved into intelligent image sensing and recognition technology through 3D modeling. In particular, image recognition technology has been actively studied in image processing using object recognition recognition processing, face recognition, object recognition, and 3D object recognition. In this paper, we propose a research method of human factor 3D image recognition technology applying human factor algorithm for 3D object recognition. 1. Methods of 3D object recognition using 3D modeling, image system analysis, design and human cognitive technology analysis 2. We propose a 3D object recognition parameter estimation method using FACS algorithm and optimal object recognition measurement method. In this paper, we propose a method to effectively evaluate psychological research techniques using 3D image objects. We studied the 3D 3D recognition and applied the result to the object recognition element to extract and study the characteristic points of the recognition technology.

• Journal of Korean Ophthalmic Optics Society
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• v.16 no.1
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• pp.83-90
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• 2011

Purpose: This study aimed to compare and assess whether there was a relation between self-reported symptom and stereopsis in viewing an anaglyph 3D and a general 2D image. Methods: Seventy subjects (38 males, 32 females) were students ranging in age from 20 to 30 years. Subjects' symptoms were investigated by a questionnaire after viewing the 2D image and the anaglyph 3D image using red-green glasses for 30 minutes. Titmus circles and TNO stereopsis tests were performed before and after the images. A correlation between symptom and stereopsis was evaluated. Results: Both ocular and nonocular symptom in viewing 3D image were higher than those in 2D image. Titmus circles stereopsises using polarized filters were not changed before and after viewing images, but TNO stereopsises using color filters such as red-green glasses were increased after viewing 3D image. Ocular symptom and TNO stereopsis were increased after viewing 3D image, and there was a good correlation between them (r=0.605). Conclusions: Better stereopsises before viewing 3D are relatively lower ocular symptoms in viewing 3D image. But symptoms are increased in viewing anaglyph 3D image for a short-time and improvement of TNO steropsis is poorly associated with the relief of ocular symptoms. This tendency seems to be related with an adaptation to anaglyph 3D image with red-green glasses.

• International Journal of Internet, Broadcasting and Communication
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• v.6 no.2
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• pp.13-16
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• 2014

This study aims to examine the effects of watching 2D and 3D images on the blink rate. Regarding the image watch, their blink rate for 2D and 3D images was separately checked for 1 minute in the 1m distance, before the watch, after 15 minutes of watch, and after 30 minutes of watch. About the change of their blink rate in the 2D image watch, it tended to become higher than that before watching the image; however, there was no statistical significance (paired t-test, p=0.106, p=0.062). And in the 2D image watch, it tended to increase in comparison between after 15 minutes and after 30 minutes, but there was no statistical significance (paired t-test, p=0.623). Meanwhile, about the change of their blink rate in the 3D image watch, it tended to decrease statistically significantly both after 15 minutes and after 30 minutes when compared with that before watching the image (paired t-test, p=0.000, p=0.000). In the 3D image watch, it tended to increase in comparison between after 15 minutes and after 30 minutes; however, there was no statistical significance (paired t-test, p=0.867).

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.795-807
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• 2013

In recent years, 2D-to-3D conversion techniques have gained much attraction. Most of conventional methods focused on natural images such as movie, animation and so forth. However, it is difficult to apply these techniques to window images mixed with text, image, logo, and icon. Also, different depth values of text pixels will cause distortion and a proper 3D image can not be delivered in some situations. To solve this problem, we propose a method to classify a given image into either a window or a natural image. For the window image, only rectangular image regions (RIR) are detected and converted in 3D. Other text and background are displayed in 2D. The proposed method was performed on more than 10,000 test images. In the experimental results, the detection ratio of window image reaches 97% and RIR detection ratio is 87%.