用几何曲线生成逼真额头纹路，提升身份验证准确率
Generating Realistic Forehead-Creases for User Verification via Conditioned Piecewise Polynomial Curves
- 用B样条和贝塞尔曲线建模额头皱纹的几何结构
- 合成数据结合真实数据使验证准确率显著提升
- 适合做生物特征识别、活体检测相关研究者参考
我们提出一种针对特定生理特征的图像生成方法，通过B样条和贝塞尔曲线对额头皱纹进行几何建模，能够真实生成主纹与非显著纹路。这些几何渲染的图像作为扩散模型的视觉提示，生成对应的匹配样本。由此构建的新型合成身份用于训练额头皱纹验证网络。为增强生成样本的个体内多样性，采用两种策略：(a) 在约束条件下扰动样条控制点以保持标签一致性；(b) 对几何提示图应用专为皱纹模式设计的图像级增强，如丢弃和弹性形变。将该合成数据集与真实数据结合后，本方法在跨数据库验证协议下显著提升了额头皱纹验证系统的性能。
原文摘要 · Abstract (English)
We propose a trait-specific image generation method that models forehead creases geometrically using B-spline and Bézier curves. This approach ensures the realistic generation of both principal creases and non-prominent crease patterns, effectively constructing detailed and authentic forehead-crease images. These geometrically rendered images serve as visual prompts for a diffusion-based Edge-to-Image translation model, which generates corresponding mated samples. The resulting novel synthetic identities are then used to train a forehead-crease verification network. To enhance intra-subject diversity in the generated samples, we employ two strategies: (a) perturbing the control points of B-splines under defined constraints to maintain label consistency, and (b) applying image-level augmentations to the geometric visual prompts, such as dropout and elastic transformations, specifically tailored to crease patterns. By integrating the proposed synthetic dataset with real-world data, our method significantly improves the performance of forehead-crease verification systems under a cross-database verification protocol.
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