• Journal of Fashion Business
• /
• v.13 no.6
• /
• pp.76-88
• /
• 2009

This study has the purposes to search the most visually effective and appropriate number of pleats and skirt length, when it's worn, with the changes in the number of pleats and skirt length that could be influential in analyzing the visual evaluation of pleats skirt and to analyze the changes when those factors are applied in real pattern. The stimuli were 18 samples: 6 variations of the number of pleats and 3 variations of the length of skirt. The data were obtained from 54 fashion design majors. The data were analyzed by Factor Analysis, Anova, Scheffe's Test and the MCA method. The results of the study were as follows: The visual image by the number of pleats and the length of skirt were composed of 4 factors : activity, attraction, neatness and commonness. In these factors, activity factor was estimated by the most important factor. The visual image according to the changes in the number of pleats and skirt length had significant differences, and the pleats skirts with 12 and 16 number of pleats and 38cm of skirt length were evaluated to be the most effective. The activity factor had interaction influence effect according to the number of pleats and the skirt length. The skirt length had more influence than the number of pleats in attraction and neatness factors, and the other way around for commonness factor.

• Journal of the Korean Society of Radiology
• /
• v.17 no.1
• /
• pp.141-148
• /
• 2023

The algebraic reconstruction technique is one of the reconstruction methods in CT and shows good image quality against noise-dominant conditions. The number of iteration is one of the key factors determining the execution time for the algebraic reconstruction technique. However, there are some rules for determining the number of iterations that result in more than a few hundred iterations. Thus, the rules are difficult to apply in practice. In this study, we proposed a method to determine the number of iterations for practical applications. The reconstructed image quality shows slow convergence as the number of iterations increases. Image quality 𝜖 < 0.001 was used to determine the optimal number of iteration. The Shepp-Logan head phantom was used to obtain noise-free projection and projections with noise for 360, 720, and 1440 views were obtained using Geant4 Monte Carlo simulation that has the same geometry dimension as a clinic CT system. Images reconstructed by around 10 iterations within the stop condition showed good quality. The method for determining the iteration number is an efficient way of replacing the best image-quality-based method, which brings over a few hundred iterations.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.5 s.37
• /
• pp.87-94
• /
• 2005

This paper describes the method of detecting the region of vehicle number plate in colored car image with number plate. Vehicle number plate region generally shows formula colors in accordance with type of car. According to this, we use the method to combine a color ingredient H of HSI color model and a color ingredient Q of YIQ color model. However, the defect which a total operation time takes much exists if it uses such method. Therefore, in this paper, the concurrent accomplishes a candidate area extraction operation as draw a color H and Q ingredient among steps of extracting a region of vehicle number Plate. After the above step, as a next step in combination with color H and Q we can accomplish an region extraction fast by comparing to candidate regions extracted from each steps not to do a comparison operation to all of image pixel information. We also show implementation results Processed at each steps and compare with extraction time according to image resolutions.

• Journal of Ubiquitous Convergence Technology
• /
• v.1 no.1
• /
• pp.18-22
• /
• 2007

Multi-Instance Learning(MIL) performs well to deal with inherently ambiguity of images in multimedia retrieval. In this paper, an effective framework for Contented-Based Image Retrieval(CBIR) with MIL techniques is proposed, the effective mechanism is based on the image segmentation employing improved Mean Shift algorithm, and processes the segmentation results utilizing mathematical morphology, where the goal is to detect the semantic concepts contained in the query. Every sub-image detected is represented as a multiple features vector which is regarded as an instance. Each image is produced to a bag comprised of a flexible number of instances. And we apply a few number of MIL algorithms in this framework to perform the retrieval. Extensive experimental results illustrate the excellent performance in comparison with the existing methods of CBIR with MIL.

• Journal of KIISE:Software and Applications
• /
• v.27 no.5
• /
• pp.551-562
• /
• 2000

Content-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. GContent-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. Generally, the query image produced by a user is different from the intended target image. To overcome this problem, many image retrieval systems use the spatial relationships of the objects, instead of pixel coordinates of the objects. In this paper, a query-converting algorithm for an image retrieval system, which uses the spatial relationship of every two objects as an image feature, is proposed. The proposed algorithm converts the query image into a graph that has the minimum number of edges, by eliminating every transitive edge. Since each edge in the graph represents the spatial relationship of two objects, the elimination of unnecessary edges makes the retrieval process more efficient. Experimental results show that the proposed algorithm leads the smaller number of comparison in searching process as compared with other algorithms that do not guarantee the minimum number of edges.

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.349-354
• /
• 1999

Electro-Optical Camera (EOC) is the main payload of the KOMPSAT-1 satellite to perform the mission of cartography that builds up a digital map of Korean territory including a digital terrain elevation map. This paper discusses the issues of the digital image simulation of EOC for the generation of EOC simulated scene as taken by EOC at 685km altitude on orbit. For the purpose, simulation work has been performed with the sensor models of EOC and the satellite platform motions models through image chain analysis from the illumination source (Sun) to a simulated image output in digital number. MODTRAN fur radiance calculation, MTF models of optics, detector and motions of EOC for system point spread function (PSF), and signal chain equations for digital number output are described. Several noise models of EOC are also considered. The final output is the EOC simulated image in digital number. The simulation technique can be used in several phase of a spaceborne electro-optical system development project, feasibility study phase, design, manufacturing, test phases, ground image processing phases, and so on.

• The Journal of Korean Philosophical History
• /
• no.28
• /
• pp.387-415
• /
• 2010

This article examines Zhu Xi(朱熹)'s theory of I-Qing(易經) present in Yi Xue Qi Meng. Zhu Xi aims to establish a novel Confucian theory of I-Qing, examining the study of I-Qing in Han Dynasity and the Taoist theory of I-Qing. To this end, he embraces Shao Yong(邵雍)'s theory of Xian Tian. Adapting the notion of Xian Tian(先天) as developed by Shao, he completes the Image-Number(象數) Theory of Hetu-Luoshu(河圖洛書). While discussing Hetu Luoshu, Zhu Xi argues that the Image and Number are not merely a form of prognostication, but a medium that reveals the principles of the nature and the sagely ways of mind. In addition, by studing I-Zhuan(易傳) in authoring Yi Xue Qi Meng, Zhu Xi maintains that the notions of Image and Number as he understands were to be approved by Confucius. This leads to the unification of Sho Yong's Tai-Ji(太極), Zou Dun Yi(周 敦頤)'s Tai-Ji, and Tai-Ji in Hetu. Through this work, Zhu Xi attempts to construct a systematic philosophy that straddles ontology and value theory, while identifying Li (理) with Xiang (象) and Shu (數). The Image-Number Theory of Hetu-Luoshu has replaced numerous theories of Image and Number at the time of Zhu Xi. Based on this theory, he restores the method of divination as presented in Xi CI Zhuan(繫辭傳). By successfully applying his theory of Image and Number to interpreting a number of recorded examples of divination during the Spring and Autumn period and the Warring States period, Zhu Xi demonstrates that his theory is not only an abstract metaphysical theory, but also can function as an adaptable method of divination.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.12
• /
• pp.4326-4344
• /
• 2021

The SinGAN is one of generative adversarial networks that can be trained on a single nature image. It has poor ability to learn more global features from nature image, and losses much local detail information when it generates arbitrary size image sample. To solve the problem, a non-linear function is firstly proposed to control downsampling ratio that is ratio between the size of current image and the size of next downsampled image, to increase the ratio with increase of the number of downsampling. This makes the low-resolution images obtained by downsampling have higher proportion in all downsampled images. The low-resolution images usually contain much global information. Therefore, it can help the model to learn more global feature information from downsampled images. Secondly, the attention mechanism is introduced to the generative network to increase the weight of effective image information. This can make the network learn more local details. Besides, in order to make the output image more natural, the TVLoss function is introduced to the loss function of SinGAN, to reduce the difference between adjacent pixels and smear phenomenon for the output image. A large number of experimental results show that our proposed model has better performance than other methods in generating random samples with fixed size and arbitrary size, image harmonization and editing.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.6-8
• /
• 2005

Study that uses geometrical information in computer vision is lively. Problem that should be preceded is matching problem before studying. Feature point should be extracted for well matching. There are a lot of methods that extract feature point from former days are studied. Because problem does not exist algorithm that is applied for all images, it is a hot water. Specially, it is not easy to find feature point in endoscope image. The big problem can not decide easily a point that is predicted feature point as can know even if see endoscope image as eyes. Also, accuracy of matching problem can be decided after number of feature points is enough and also distributed on whole image. In this paper studied algorithm that can apply to endoscope image. SIFT method displayed excellent performance when compared with alternative way (Affine invariant point detector etc.) in general image but SIFT parameter that used in general image can't apply to endoscope image. The gual of this paper is abstraction of feature point on endoscope image that controlled by contrast threshold and curvature threshold among the parameters for applying SIFT method on endoscope image. Studied about method that feature points can have good distribution and control number of feature point than traditional alternative way by controlling the parameters on experiment result.

• Proceedings of the KSRS Conference
• /
• 2005.10a
• /
• pp.123-125
• /
• 2005

Many researchers conducted the effort for improving the classification accuracy of satellite image. Most of the study has used optical spectrum information of each pixel for image classification. By applying this method for high resolution satellite image, number of class becomes increase. This situation is remarkable for house, because the roof of house has variety of many colors. Even if the classification is carried out for many classes, roof color information of each house is not necessary. Most of the case, we need the information that object is house or not. In this study, we propose the method for detecting the object by using Genetic Algorithms (GA). Aircraft was selected as object. It is easy for this object to detect in the airport. An aircraft was taken as a template. Object image was taken from QuickBird. Target image includes an aircraft and Haneda Airport. Chromosome has four or five parameters which are composed of number of template, position (x,y), rotation angle, rate of enlarge. Good results were obtained in the experiment.