Texture Synthesis Research Papers - Academia.edu (original) (raw)

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- Information Systems, Texture Synthesis, Surface Texture
- by Xin Wang
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- Information Systems, Texture Synthesis, Surfaces, Surface Texture
- by Mohiy Hadhoud
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- Algorithms, Process Optimization, Pattern Recognition, Image Restoration
- by yao-xun chang
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- Cognitive Science, Texture Synthesis, Computer Graphic
- by Wallace Casaca
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- Cognitive Science, Texture Synthesis, Anisotropic Diffusion, Transport Equation

Abstract. Many image processing algorithms rely on nearest neighbor (NN) or on the k nearest neighbor (kNN) search problem. Several meth-ods have been proposed to reduce the computation time, for instance using space partitionning.... more

- by Frank Nielsen
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- Image Processing, Data Structure, Nearest Neighbor, Gpu programming
- by Li Cheng
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- Engineering, Computational Physics, Image Processing, Pattern Formation

- by George Drettakis
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- Stochastic Process, Interactive Video, Spectral analysis, Texture Synthesis
- by Eero P Simoncelli and +1
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- Computer Vision, Statistical Computing, Efficient Algorithm for ECG Coding, Texture Synthesis
- by Jay Busch
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- Surface Roughness, Facial Modeling, Texture Synthesis, Microstructures
- by Andy Nealen
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- Texture Synthesis, Hybrid Algorithm, Morphological Operation

This paper presents crack detection in concrete structure based on fuzzy logic. Safety inspection of concrete structures is very important since it is closely related with the structural health and reliability. Automated structural health monitoring system becomes necessity in recent years that encourages various researches to be going on in this area. Cheap availability of digital cameras makes research work in this field easier. This paper presents digital image processing and fuzzy logic based efficient crack detection technique in concrete structure. Here features from digital image of concrete structure are extracted by using morphological image processing technique and then extracted features are fed to fuzzy logic to accurately identify the crack.

- by J4R - Journal for Research
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- Restoration, Crack detection, Texture Synthesis, Cracks

Reconstruction of archaeological finds from fragments, is a tedious task requiring many hours of work from the archaeologists and restoration personnel. In this paper we present a framework for the full reconstruction of the original objects using texture and surface design information on the sherd. The texture of a band outside the border of pieces is predicted by inpainting and texture synthesis methods. The confidence of this process is also defined. Feature values are derived from these original and predicted images of ...

- by Aytul Ercil
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- Computer Science, Virtual Reality, Vr, Texture Synthesis
- by Frederick Kingdom
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- Psychophysics, Vision, Humans, Depth Perception
- by Vivek Kwatra
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- Information Systems, Image-based Rendering, Region growing, Flow Visualization
- by Jyoti waykule
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- Computer Science, Image Processing, Image inpainting, Texture Synthesis

Abstract Document analysis is done to analyze entire forms (eg intelligent form analysis, table detection) or to describe the layout/structure of a document. In this paper document analysis is applied to snippets of torn documents to... more

- by Markus Diem
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- Document Analysis, Line Detection, Texture Synthesis, Degeneration
- by Philip Dutré
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- Computer Science, Computational Geometry, Markov Processes, Stochastic processes
- by Remco Renken
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- Perception, Multidisciplinary, Humans, Food Quality

Procedural noise functions are widely used in Computer Graphics, from off-line rendering in movie production to interactive video games. The ability to add complex and intricate details at low memory and authoring cost is one of its main attractions. This state-of-the-art report is motivated by the inherent importance of noise in graphics, the widespread use of noise in industry, and the fact that many recent research developments justify the need for an up-to-date survey. Our goal is to provide both a valuable entry point into the field of procedural ...

- by George Drettakis
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- Stochastic Process, Interactive Video, Spectral analysis, Texture Synthesis
- by Bruno Vallet
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- Interaction Design, Level Set, Texture Synthesis, Texture Mapping
- by jyoti tate
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- Cognitive Science, Algorithms, Computer Graphics, Image Processing
- by Yiying Tong
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- Information Systems, Texture Synthesis
- by S. Brooks
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- Algorithms, Computer Graphics, Art, Colorimetry

This paper presents Vismantic, a semi-automatic system generating proposals of visual composition (visual ideas) in order to express specific meanings. It implements a process of developing visual solutions from 'what to say' to 'how to say', which requires both conceptual and visual creativity. In particular, Vismantic extends our previous work on using conceptual knowledge to find diverse visual representations of abstract concepts, with the capacity of combining two images in three ways, including juxtaposition, replacement and fusion. In an informal evaluation consisting of five communication tasks, Vismantic demonstrated the potential of producing a number of expressive and diverse ideas, among which many are surprising. Our analysis of the generated images confirms that visual meaning-making is a subtle interaction between all elements in a picture, for which Vismantic demands more visual semantic knowledge, higher image analysis and synthesis skills, and the ability of interpreting composed images, in order to deliver more ideas that make sense.

- by Ping Xiao
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- Metaphor, Computational Creativity, Conceptual Blending, Design ideation
- by Carlos Vanegas
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- Cognitive Science, Computer Graphics, Land Use, Style
- by Frank Nielsen
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- Information Systems, Non-photorealistic rendering, Texture Synthesis, Cross Section
- by john schott
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- Algorithms, Remote Sensing, Modeling, Digital imaging
- by Emigdio Z-Flores and +1
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- Video Coding, Texture Synthesis, Texture Analysis, Texture Segmentation
- by Shlomo Dubnov
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- Dimension Reduction, Texture Synthesis, Statistical Approach
- by Guoning Chen
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- Algorithms, Computer Graphics, Rheology, Fluid Simulation

Conventional Virtual Reality (VR) is already being used in the design process for styling reviews on a daily basis, but until now only object shape can be assessed in a meaningful way, and neither the look and feel, nor the quality of surface materials can be adequately reproduced. Therefore, most interior design decisions in the automotive industry are still performed

- by Akos Balazs
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- Image-based Rendering, Interior Design, Automotive Industry, Technology development

We provide a solution to problem of occlusion in images by removing the occluding region and filling in the gap left behind. Inpainting algorithms fail in filling occlusions when the occluding region is large since there is loss of both structure and texture. We decompose the image into structure and texture images using a decomposition method based on sparseness of the image. The sparse reconstruction of the decomposed images result in an inpainted image with all the structures made intact. A texture synthesis is performed on the texture only image. Finally the structure and texture images are combined to get an image where the occlusion is filled. The performance of our algorithm in terms of visual effectiveness is compared with other algorithms used for inpainting.

- by Hong Qin
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- Mechanical Engineering, Computer Graphics, Image Processing, Computational Geometry

Current scanning techniques record facial mesostructure with sub-millimeter precision showing pores, wrinkles, and creases. However, surface roughness continues to shape specular reflection at the level of microstructure: micron scale structures. Here, we present an approach to increase the resolution of mesostructure-level facial scans using microstructure examples digitized about the face. We digitize the skin patches using polarized gradient illumination and

- by Jay Busch
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- Surface Roughness, Facial Modeling, Texture Synthesis, Microstructures
- by Ling Huang
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- Texture Synthesis
- by Minglun Gong
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- Computer Science, Computer Vision, Visualization, Image segmentation
- by Irfan Essa
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- Control Application, Texture Synthesis, Natural Phenomena, Web Pages
- by Javier Portilla
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- Texture Synthesis, Texture Analysis, Physical Model, Low Light
- by Vivek Kwatra
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- Information Systems, Machine Learning, Image-based Rendering, Video Processing
- by Mansour Jamzad and +1
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- Image Reconstruction, Image inpainting, Texture Synthesis, Image Decomposition
- by Iasir Journals
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- Computer Science, Image Processing, Texture Synthesis
- by jyoti tate
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- Cognitive Science, Algorithms, Computer Graphics, Image Processing
- by Mohiy Hadhoud
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- Process Optimization, Image Restoration, Image inpainting, Texture Synthesis

Steganography is the method for concealing data inside another file, message, image, or video. The purpose of steganography is to hide data in a manner that existence of communication is unknown by an attacker. This proposed work presents stegnography in texture images utilizing reversible texture synthesis based on error histogram shift. Texture synthesis process synthesizes a large texture image from a smaller texture image, which has same local appearance. The texture synthesis procedure is fabricated into steganography concealing secret messages and in addition the source texture. The algorithm conceals the source texture image and embeds the secret messages through the procedure of texture synthesis and error histogram shift. This permits us to extract the secret messages and the source texture from a stego synthetic texture.

- by Lincoln Ritter
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- Image-based Rendering, Real-time rendering, Visibility, Texture Synthesis