This paper presents a generalization of dispersed-dot dithering. While existing methods such as Bayer’s assume that color dots are arranged in a square matrix, this method works with arbitrarily-placed color points. To create a good dither pattern for arbitrarily-placed points, they must be ordered so that consecutive pairs are maximally separated. In this papre, the ordering is obtained by hie...

Ambient art is the aesthetic presentation of information, using artistic techniques to achieve a pleasing image that also contains hidden depths, where exposure to it over time allows a viewer to understand something about the information sources that it represents. This paper reviews the artistic and computational background of ambient systems, and presents two case studies of systems develope...

Intensity based registration methods, such as the mutual information (MI), do not commonly consider the spatial geometric information and the initial correspondences are uncertainty. In this paper, we present a novel approach for achieving highly-automatic 2D/3D image registration integrating the advantages from both entropy MI and spatial geometric features correspondence methods. Inspired by ...

This paper proposes an extension to the existing automatic pencil drawing generation technique based on Line Integral Convolution (LIC). The original LIC pencil filter utilizes image segmentation and texture direction detection techniques for defining outlines and stroke directions, and the quality of a resulting image depends largely on the result of the white noises and the texture directions...

We present a generative model with spatial control to synthesize dual-artistic media effects. It generates different artistic effects on the foreground and background of an image. In order apply distinct effect photograph, deep learning-based models require training dataset composed pairs photograph its corresponding artwork images. To build dataset, we some existing techniques that generate im...

Stippling is an artistic rendering technique where shading and texture is given by placing points or stipples on the canvas until the desired darkness is achieved. Computergenerated stippling has focused on producing high quality 2D renditions for print media, while stippling of 3D models in animations has received little attention. After describing current advances in stippling for print media...

We have shown that it is possible to achieve artistic style transfer within a purely image processing paradigm. This is in contrast to previous work that utilized deep neural networks to learn the difference between “style” and “content” in a painting. We leverage the work by Kwatra et. al. on texture synthesis to accomplish “style synthesis” from our given style images, building off the work o...

Visual complexity has been known to be a significant predictor of preference for artistic works for some time. The first study reported here examines the extent to which perceived visual complexity in art can be successfully predicted using automated measures of complexity. Contrary to previous findings the most successful predictor of visual complexity was Gif compression. The second study exa...

A number of Non-Photorealistic Rendering methods for producing artistic style images have been developed. Recently, a method called “Image Analogies” was proposed. This method is based on the idea of example-based filtering that uses a pair of images (an original image and a filtered image) as training data and creates an image which has a style that resembles the filtered image of the training...

In this paper, we present a method which combines the flexibility of the neural algorithm of artistic style with the speed of fast style transfer networks to allow real-time stylization using any content/style image pair. We build upon recent work leveraging conditional instance normalization for multi-style transfer networks by learning to predict the conditional instance normalization paramet...