Patch-based image vectorization with automatic curvilinear feature alignment

Liao, Binbin; Yu, Yizhou

doi:10.1145/1661412.1618461

Cited by 24 publications

(32 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The gradient mesh is widely used in industry for vectorizing images that consist of smooth color regions [Lecot and Levy 2006;Sun et al 2007;Lai et al 2009]. Xia et al [2009] segmented images into triangular patches and modeled the color variation inside a patch with thin plate splines. Diffusion curve images [Elder and Goldberg 2001;Orzan et al 2008] and its extensions [Bezerra et al 2010;Takayama et al 2010] construct images or volumes by diffusing colors specified on curves and surfaces.…”

Section: Related Workmentioning

confidence: 99%

Diffusion curve textures for resolution independent texture mapping

Sun

Xie²,

Dong

et al. 2012

ACM Trans. Graph.

View full text Add to dashboard Cite

Figure 1: Our method provides a compact and explicit representation of diffusion curve images for texture mapping onto a surface. The sharp features and detailed color variations of textures are well preserved in the rendering results. AbstractWe introduce a vector representation called diffusion curve textures for mapping diffusion curve images (DCI) onto arbitrary surfaces. In contrast to the original implicit representation of DCIs [Orzan et al. 2008], where determining a single texture value requires iterative computation of the entire DCI via the Poisson equation, diffusion curve textures provide an explicit representation from which the texture value at any point can be solved directly, while preserving the compactness and resolution independence of diffusion curves. This is achieved through a formulation of the DCI diffusion process in terms of Green's functions. This formulation furthermore allows the texture value of any rectangular region (e.g. pixel area) to be solved in closed form, which facilitates anti-aliasing. We develop a GPU algorithm that renders anti-aliased diffusion curve textures in real time, and demonstrate the effectiveness of this method through high quality renderings with detailed control curves and color variations.

show abstract

Section: Related Workmentioning

confidence: 99%

Diffusion curve textures for resolution independent texture mapping

Sun

Xie²,

Dong

et al. 2012

ACM Trans. Graph.

View full text Add to dashboard Cite

show abstract

“…These filters do not work well on pixel art input, most likely due to the small image size, since edge detectors have a finite support. Xia et al [2009] describe a technique that operates on a pixel level triangulation of the raster image. However, it also relies on Canny edge detection.…”

Section: Lecot and Lévymentioning

confidence: 99%

Depixelizing pixel art

Kopf

Lischinski

2011

ACM SIGGRAPH 2011 Papers

View full text Add to dashboard Cite

Nearest-neighbor result (original: 40×16 pixels) Our result Figure 1: Naïve upsampling of pixel art images leads to unsatisfactory results. Our algorithm extracts a smooth, resolution-independent vector representation from the image, which is suitable for high-resolution display devices. (Input image c Nintendo Co., Ltd.). AbstractWe describe a novel algorithm for extracting a resolutionindependent vector representation from pixel art images, which enables magnifying the results by an arbitrary amount without image degradation. Our algorithm resolves pixel-scale features in the input and converts them into regions with smoothly varying shading that are crisply separated by piecewise-smooth contour curves.In the original image, pixels are represented on a square pixel lattice, where diagonal neighbors are only connected through a single point. This causes thin features to become visually disconnected under magnification by conventional means, and creates ambiguities in the connectedness and separation of diagonal neighbors. The key to our algorithm is in resolving these ambiguities. This enables us to reshape the pixel cells so that neighboring pixels belonging to the same feature are connected through edges, thereby preserving the feature connectivity under magnification. We reduce pixel aliasing artifacts and improve smoothness by fitting spline curves to contours in the image and optimizing their control points.

show abstract

“…Vectorization of full-color 2D raster images [Lecot and Levy 2006;Price and Barrett 2006;Sun et al 2007;Orzan et al 2008;Lai et al 2009;Xia et al 2009] has been popular recently. These images need a more generic vector representation that accounts for color variations across the image plane in addition to feature curves.…”

Section: Related Workmentioning

confidence: 99%

Vector solid textures

Wang¹,

Zhou²,

Yu³

et al. 2010

ACM SIGGRAPH 2010 Papers

Self Cite

View full text Add to dashboard Cite

Figure 1: Several vector solid textures rendered in real time. In each group, the upper inset shows a closer view while the lower inset is rendered using the bitmap solid texture from which the vector version is generated. In the middle group, the reflectance coefficients are stored along with the RGB channels. In the rightmost group, three different scales of the same vector solid texture are composited to yield complex self-similar boundaries. AbstractIn this paper, we introduce a compact random-access vector representation for solid textures made of intermixed regions with relatively smooth internal color variations. It is feature-preserving and resolution-independent. In this representation, a texture volume is divided into multiple regions. Region boundaries are implicitly defined using a signed distance function. Color variations within the regions are represented using compactly supported radial basis functions (RBFs). With a spatial indexing structure, such RBFs enable efficient color evaluation during real-time solid texture mapping. Effective techniques have been developed for generating such a vector representation from bitmap solid textures. Data structures and techniques have also been developed to compactly store region labels and distance values for efficient random access during boundary and color evaluation.

show abstract

Patch-based image vectorization with automatic curvilinear feature alignment

Cited by 24 publications

References 23 publications

Diffusion curve textures for resolution independent texture mapping

Diffusion curve textures for resolution independent texture mapping

Depixelizing pixel art

Vector solid textures

Contact Info

Product

Resources

About