• Journal of Digital Convergence
• /
• v.10 no.4
• /
• pp.191-197
• /
• 2012

In this paper we present creating 3D image from 2D image by extract initial depth values calculated from focal values. The initial depth values are created by using the extracted focal information, which is calculated by the comparison of original image and Gaussian filtered image. This initial depth information is allocated to the object segments obtained from normalized cut technique. Then the depth of the objects are corrected to the average of depth values in the objects so that the single object can have the same depth. The generated depth is used to convert to 3D image using DIBR(Depth Image Based Rendering) and the generated 3D image is compared to the images generated by other techniques.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.11
• /
• pp.2045-2053
• /
• 2016

Many research institutes have studied 3D stereoscopic images since the release of 3D stereoscopic film 'Avatar' in 2009. Universities have conducted research on and studied 3D stereoscopic image in various ways, and even university curriculums have adopted 3D stereoscopic image production courses. However, universities face many difficulties in purchasing expensive equipment including cameras and rigs for 3D stereoscopic image contents production training. This paper addresses the 3D stereoscopic image content production curriculum using software in university. A practical training course was carried out based on the theoretical contents and theories that must be dealt with in 3D stereoscopic image contents production curriculum. As a result, students could understand the principles of 3D stereoscopic image production and produce various 3D stereoscopic images using various software applications. In this parer, proper instructional methods for 3D stereoscopic image contents production in university are discussed through this production course.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2003.05a
• /
• pp.409-412
• /
• 2003

The 3-D shape use to effect of movie, animation, industrial design, medical treatment service, education, engineering etc... But it is not easy to make 3-D shape from the information of 2-D image. There are two methods in restoring 3-D video image through 2-D image; First the method of using a laser; Second, the method of acquiring 3-D image through stereo vision. Instead of doing two methods with many difficulties, I study the method of simple 3-D image in this research paper. We present here a simple and efficient method, called direct calibration, which does not require any equations at all. The direct calibration procedure builds a lookup table(LUT) linking image and 3-D coordinates by a real 3-D triangulation system. The LUT is built by measuring the image coordinates of a grid of known 3-D points, and recording both image and world coordinates for each point; the depth values of all other visible points are obtained by interpolation.

• Journal of The Korean Association of Information Education
• /
• v.26 no.1
• /
• pp.1-10
• /
• 2022

With the development of artificial intelligence, society is moving toward another world that has never existed before. As a result, interest in artificial intelligence education is also increasing, and research on artificial intelligence education is being conducted more actively in Korea. However, many studies have been conducted focusing on the upper grades of elementary school, and curriculum and programs for the lower grades are still insufficient. Therefore, in this study, a total of 6 sessions of artificial intelligence programs were developed to understand image recognition for the lower grades of elementary school. The validity was secured by conducting expert validity for 8 experts, and the effectiveness was verified through the pre-post-response sample t-test by applying it to the experimental group. As a result, both artificial intelligence understanding and artificial intelligence attitude showed statistically significant results, and both the interest and difficulty of educational programs were found to be suitable for lower grade students. Based on the contents of this study, it is necessary to review its application and effectiveness in various environments through follow-up studies in the future.

• Korean Journal of Acupuncture
• /
• v.25 no.4
• /
• pp.167-174
• /
• 2008

Objectives : Acupuncture points and meridians have been usually depicted as a two dimensional drawing and verbal description. Recently, imaging and three-dimensional image processing technologies have been introduced into medical fields such as anatomy and virtual operation, for the purpose of enhanced efficiency in research and education. This study attempted an image modelling of the meridian and acupoint in the upper limb region. Methods : A vector image model of an arm was produced and medical information on the meridian and acupoint of the arm region was incorporated. Results : A 3D modelling of the acupuncture meridian and acupoint in the upper limb region was produced along with a user console to control the presentation of related information and to facilitate visualization of the 3D model images. Conclusions : A 3D modelling of the acupuncture meridian and acupoint will be an efficient platform for an education and research.

• Journal of Information Processing Systems
• /
• v.16 no.6
• /
• pp.1437-1446
• /
• 2020

For the last few years, smart devices have begun to occupy an essential place in the life of children, by allowing them to access a variety of language activities and books. Various studies are being conducted on using smart devices for education. Our study extracts images and texts from kids' book with smart devices and matches the extracted images and texts to create new images that are not represented in these books. The proposed system will enable the use of smart devices as educational media for children. A deep convolutional generative adversarial network (DCGAN) is used for generating a new image. Three steps are involved in training DCGAN. Firstly, images with 11 titles and 1,164 images on ImageNet are learned. Secondly, Tesseract, an optical character recognition engine, is used to extract images and text from kids' book and classify the text using a morpheme analyzer. Thirdly, the classified word class is matched with the latent vector of the image. The learned DCGAN creates an image associated with the text.

• Journal of Integrative Natural Science
• /
• v.11 no.3
• /
• pp.131-138
• /
• 2018

In this paper, we have implemented speeches that utilized the emotion information of the user's speech and image matching and recommendation system. To classify the user's emotional information of speech, the emotional information of speech about the user's speech is extracted and classified using the PLP algorithm. After classification, an emotional DB of speech is constructed. Moreover, emotional color and emotional vocabulary through factor analysis are matched to one space in order to classify emotional information of image. And a standardized image recommendation system based on the matching of each keyword with the BM-GA algorithm for the data of the emotional information of speech and emotional information of image according to the more appropriate emotional information of speech of the user. As a result of the performance evaluation, recognition rate of standardized vocabulary in four stages according to speech was 80.48% on average and system user satisfaction was 82.4%. Therefore, it is expected that the classification of images according to the user's speech information will be helpful for the study of emotional exchange between the user and the computer.

• The Journal of Korean Academic Society of Nursing Education
• /
• v.19 no.3
• /
• pp.384-395
• /
• 2013

Purpose: This study aimed to investigate the nurse's image and role projected in media and perceived by elementary, middle and high school students. Methods: Data were collected from 544 students in J city, Korea during December 2010 to February 2011. The nurse's image was measured by the instrument developed by Yang (1998). Nursing experiences and nurse's role in media was measured by self-administered questionnaires with 8 questions. Statistical analysis was made with t-test and ANOVA using SPSS win 18.0. Result: The score on personal image was the highest, while the score on social image was the lowest. Elementary school students reported a positive image compared with middle and high school students. Male students had a more positive image than female students. Of various media, students had more experiences related to nurses from TV rather than internet sites, books and newspaper/magazines. Especially, the nurse's role on TV 'seemed to be an assistant of a doctor' was rated the highest by the students. Conclusion: It is necessary to develop a strategy to improve the social image of the nurse through TV by providing correct information on the nurse's role. For this purpose, it is required to consistently monitor and analyze the nurse's role shown in media.

• The Pure and Applied Mathematics
• /
• v.11 no.1
• /
• pp.1-14
• /
• 2004

Due to the development of computer network and mobile communications, the security in image data and other related source are very important as in saving or transferring the commercial documents, medical data, and every private picture. Nonetheless, the conventional encryption algorithms are usually focusing on the word message. These methods are too complicated or complex in the respect of image data because they have much more amounts of information to represent. In this sense, we proposed an efficient secret symmetric stream type encryption algorithm which is based on Boolean matrix operation and the characteristic of image data.

• Journal of information and communication convergence engineering
• /
• v.12 no.4
• /
• pp.263-270
• /
• 2014

Corner detection and feature extraction are essential aspects of computer vision problems such as object recognition and tracking. Feature detectors such as Scale Invariant Feature Transform (SIFT) yields high quality features but computationally intensive for use in real-time applications. The Features from Accelerated Segment Test (FAST) detector provides faster feature computation by extracting only corner information in recognising an object. In this paper we have analyzed the efficient object detection algorithms with respect to efficiency, quality and robustness by comparing characteristics of image detectors for corner detector and feature extractors. The simulated result shows that compared to conventional SIFT algorithm, the object recognition system based on the FAST corner detector yields increased speed and low performance degradation. The average time to find keypoints in SIFT method is about 0.116 seconds for extracting 2169 keypoints. Similarly the average time to find corner points was 0.651 seconds for detecting 1714 keypoints in FAST methods at threshold 30. Thus the FAST method detects corner points faster with better quality images for object recognition.