Stroke-based Character Reconstruction
arXiv:1806.08990
Abstract
Background elimination for noisy character images or character images from real scene is still a challenging problem, due to the bewildering backgrounds, uneven illumination, low resolution and different distortions. We propose a stroke-based character reconstruction(SCR) method that use a weighted quadratic Bezier curve(WQBC) to represent strokes of a character. Only training on our synthetic data, our stroke extractor can achieve excellent reconstruction effect in real scenes. Meanwhile. It can also help achieve great ability in defending adversarial attacks of character recognizers.
arXiv comment6 pages, 7 figures
References in corpus (5)
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
- MagNet: a Two-Pronged Defense against Adversarial Examples
- Synthesizing Programs for Images using Reinforced Adversarial Learning
- Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting