Anna Maria Van Schurman’s Chinese Calligraphy

Anna-Maria - Application of New Net-Theoretic Analysis Methods in Maria - a Modular Reachability Analyser

Create Your Own Chinese Calligraphy Artwork

In this work, we aim to transform handwritten Chinese characters into calligraphy style characters on a stroke-by-stroke basis. We extracted strokes from a set of handwritten characters by identifying the primary orientation of each stroke. We then adopted autoencoder and self-organizing maps to cluster the extracted strokes into 100 different groups. Using the neural networks obtained, we clus...

Chinese Brush Calligraphy Character Retrieval and Learning

Chinese brush calligraphy is a valuable civilization legacy and a high art of scholarship. It is still popular in Chinese banners, newspaper mastheads, university names, and celebration gifts. There are Web sites that try to help people enjoy and learn Chinese calligraphy. However, there lacks advanced services such as content-based retrieval or vivid writing process simulation for calligraphy ...

An Intelligent System for Chinese Calligraphy

Our work links Chinese calligraphy to computer science through an integrated intelligence approach. We first extract strokes of existent calligraphy using a semi-automatic, twophase mechanism: the first phase tries to do the best possible extraction using a combination of algorithmic techniques; the second phase presents an intelligent user interface to allow the user to provide input to the ex...

Chinese Calligraphy Font Classification and Transformation

This project explores Chinese character font classification and transformation, which are the most important two steps in reconstructing weathered Chinese characters. For font classification, SIFT is first used to capture font features, and neural network is built in Keras with almost perfect results achieved. For font transformation, a convolutional neural network is implemented in Tensorflow,...