• Journal of Korea Multimedia Society
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• v.3 no.1
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• pp.34-40
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• 2000

'[n this paper, we propose an efficient multi-view image coding algorithm which finds the optimal texture from a restricted number of multi-view image. The X-Y plane of the normalized object space is divided into the triangular patches. The depth of each node is determined by appling a block based disparity compensation method. Thereafter the texture of each patch is extracted by appling an affine transformation based disparity compensation method to the multi-view images. We reduced the number of images needed to determine the texture compared to traditional methods which use all the multi-view image in the texture extraction. The experimental results show that the SNR of images encoded by the proposed algorithm is better than that of images encoded by the traditional method by the approximately 0.2dB for the test sets of multi -view image called dragon, santa, city and kid. Image data recovered after encoding by the proposed method show a better visual results than after using traditional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.311-326
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• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.46-56
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• 2016

Dynamic textures are videos that exhibit a stationary property with respect to time (i.e., they have patterns that repeat themselves over a large number of frames). These patterns can easily be tracked by a linear dynamic system. In this paper, a model that identifies the underlying linear dynamic system using wavelet coefficients, rather than a raw sequence, is proposed. Content based threshold filtering based on Set Partitioning in a Hierarchical Tree (SPIHT) helps to get another representation of the same frames that only have low frequency components. The main idea of this paper is to apply SPIHT based threshold filtering on different bands of wavelet transform so as to have more significant information in fewer parameters for singular value decomposition (SVD). In this case, more flexibility is given for the component selection, as SVD is independently applied to the different bands of frames of a dynamic texture. To minimize the time complexity, the proposed model is implemented on a graphics processing unit (GPU). Test results show that the proposed dynamic system, along with a discrete wavelet and SPIHT, achieve a highly compact model with better visual quality, than the available LDS, Fourier descriptor model, and higher-order SVD (HOSVD).

• ETRI Journal
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• v.36 no.2
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• pp.242-252
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• 2014

Since July of 2012, the 3D video extension of H.264/AVC has been under development to support the multi-view video plus depth format. In 3D video applications such as multi-view and free-view point applications, synthesized views are generated using coded texture video and coded depth video. Such synthesized views can be distorted by quantization noise and inaccuracy of 3D wrapping positions, thus it is important to improve their quality where possible. To achieve this, the relationship among the depth video, texture video, and synthesized view is investigated herein. Based on this investigation, an edge noise suppression filtering process to preserve the edges of the depth video and a method based on a total variation approach to maximum a posteriori probability estimates for reducing the quantization noise of the coded texture video. The experiment results show that the proposed methods improve the peak signal-to-noise ratio and visual quality of a synthesized view compared to a synthesized view without post processing methods.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.333-339
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• 2023

In three-dimensional(3D) modeling, texturing plays a crucial role as a visual element, imparting detail and realism to models. In contrast to traditional texturing methods, the current trend involves utilizing AI tools such as Leonardo.Ai and Meshy to create textures for 3D models in a more efficient and precise manner. This paper focuses on 3D texturing, conducting a comprehensive comparative study of AI tools, specifically Leonardo.Ai and Meshy. By delving into the performance, functional differences, and respective application scopes of these two tools in the generation of 3D textures, we highlight potential applications and development trends within the realm of 3D texturing. The efficient use of AI tools in texture creation also has the potential to drive innovation and enhancement in the field of 3D modeling. In conclusion, this research aims to provide a comprehensive perspective for researchers, practitioners, and enthusiasts in related fields, fostering further innovation and development in this domain.

• Journal of Digital Contents Society
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• v.6 no.2
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• pp.119-123
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• 2005

We proposed a method of effective watermarking based m HVS. To speak generally, HVS parameters are contrast sensitivity, texture degree, entropy sensitivity and standard of deviation, etc. The aim of this paper is evaluated by the experiments of imperceptibility and correctness of watermark. According to some experimental results, contrast sensitivity function is superior in smooth image. On the other hand, standard of deviation provides good results in rough images. Consequently, how to select the parameters considering image attribute is key problem in effective watermarking.

• Journal of the Semiconductor & Display Technology
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• v.6 no.1 s.18
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• pp.49-52
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• 2007

The recent advances in digital imaging and computing technology have resulted in a rapid accumulation of digital media in the personal computing and entertainment industry. In addition, large collections of such data already exist in many scientific application domains such as the geographic information systems (GIS), digital library, trademark imaging, satellite imaging and medical imaging. Thus, the need for content-based retrieval from visual media, such as image and video data, is ever increasing rapidly in many applications.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.103-111
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• 2007

The spectral information based image analysis, visual interpretation and automatic classification have been widely carried out so far for remote sensing data processing. Yet recently, many researchers have tried to extract the spatial information which cannot be expressed directly in the image itself. Using the texture and wavelet scheme, we made a wavelet-based texture fusion image which includes the advantages of each scheme. Moreover, using these schemes, we carried out image classification for the urban spatial analysis and the geological structure analysis around the caldera area. These two case studies showed that image classification accuracy of texture image and wavelet-based texture fusion image is better than that of using only raw image. In case of the urban area using high resolution image, as both texture and wavelet based texture fusion image are added to the original image, the classification accuracy is the highest. Because detailed spatial information is applied to the urban area where detail pixel variation is very significant. In case of the geological structure analysis using middle and low resolution image, the images added by only texture image showed the highest classification accuracy. It is interpreted to be necessary to simplify the information such as elevation variation, thermal distribution, on the occasion of analyzing the relatively larger geological structure like a caldera. Therefore, in the image analysis using spatial information, each spatial information analysis method should be carefully selected by considering the characteristics of the satellite images and the purpose of study.

• Journal of the Korean Institute of Landscape Architecture
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• v.25 no.2
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• pp.104.1-104.1
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• 1997

The purpose of this study is to grasp the characteristics of user''''s response to perceived safety and visual preferences for outdoor green spaces by the types of campus layouts. This research was investigated by color slide ratings and questionnaire survey to the students who are majoring in Landscape architecture in three universities locating at Taegu area. Two research sites have similarities in many ways but have differences in campus land form and design type such as ''''Closed'''' and ''''Open'''' types. Major results were summarised as follows ; 1. As a result of the slide test, the high degree of visual preference was shown in the campus that is ''''Closed'''' type. However the degree of perceived safety was lower than that of in Youngnam Univ. campus. 2. According to the result of the comparative analysis between user''''s perceived safety and visual preferences in each campus, the degree of perceived safety at ''''Closed'''' type was lower than that of ''''Open'''' type, but the degree of visual satisfactioni was higher at ''''Closed'''' type. 3. The factors affecting visual preference in campus were shown as density of wood, land form, and diverse type of the spaces. On the other hand, the factors affecting perceived safety were ''''enclosed space by wood'''' at the day time, and ''''the condition of lighting'''' at night. 4. Regarding gender differences in sensation of each space variables, female users showed higher satisfactio on the scenic beauty. 5. Regression analysis showed that general satisfation was determined by the variables such as ''''arrangement'''', familiarity'''', ''''cleanness'''', and ''''closed feeling'''', in Kyungbook Univ. And in Youngnam Univ. , the variables were ''''texture'''', ''''perceived beauty'''', ''''cleanness'''', and ''''complexity'''' respectively. 6. In conclusion, campus users wanted the outdoor spaces that have various land form and somewhat ''''open-closed'''' mixture type, which has a good ''''Edge Effect'''' to satisfy both aspects in safety and visual preferneces.

• Journal of the Korean Institute of Landscape Architecture
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• v.25 no.2
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• pp.104-116
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• 1997

The purpose of this study is to grasp the characteristics of user's response to perceived safety and visual preferences for outdoor green spaces by the types of campus layouts. This research was investigated by color slide ratings and questionnaire survey to the students who are majoring in Landscape architecture in three universities locating at Taegu area. Two research sites have similarities in many ways but have differences in campus land form and design type such as 'Closed' and 'Open' types. Major results were summarised as follows ; 1. As a result of the slide test, the high degree of visual preference was shown in the campus that is 'Closed' type. However the degree of perceived safety was lower than that of in Youngnam Univ. campus. 2. According to the result of the comparative analysis between user's perceived safety and visual preferences in each campus, the degree of perceived safety at 'Closed' type was lower than that of 'Open' type, but the degree of visual satisfactioni was higher at 'Closed' type. 3. The factors affecting visual preference in campus were shown as density of wood, land form, and diverse type of the spaces. On the other hand, the factors affecting perceived safety were 'enclosed space by wood' at the day time, and 'the condition of lighting' at night. 4. Regarding gender differences in sensation of each space variables, female users showed higher satisfactio on the scenic beauty. 5. Regression analysis showed that general satisfation was determined by the variables such as 'arrangement', familiarity', 'cleanness', and 'closed feeling', in Kyungbook Univ. And in Youngnam Univ. , the variables were 'texture', 'perceived beauty', 'cleanness', and 'complexity' respectively. 6. In conclusion, campus users wanted the outdoor spaces that have various land form and somewhat 'open-closed' mixture type, which has a good 'Edge Effect' to satisfy both aspects in safety and visual preferneces.