论文标题
Saffire：用于自动功能过滤和智能ROI估计的系统
SAFFIRE: System for Autonomous Feature Filtering and Intelligent ROI Estimation
论文作者
论文摘要
这项工作介绍了一个名为Saffire的新框架，以自动从一组图像样本中提取主流的复发图案。这种模式应用于消除样品之间的姿势变化，这在许多计算机视觉和机器学习任务中是一个普遍的要求。该框架是在机器视觉系统进行自动化产品检查的背景下进行专门的。在这里，习惯要求用户识别自动化系统在进一步处理之前将数据归一化的锚定模式。但是，这是一个非常敏感的操作，本质上是主观的，需要高专业知识。迄今为止，Saffire提供了一个独特而破坏性的框架，以完全透明的方式无监督识别最佳锚模式。 Saffire在几个现实的案例研究中对机器视觉检查管道进行了彻底验证。
This work introduces a new framework, named SAFFIRE, to automatically extract a dominant recurrent image pattern from a set of image samples. Such a pattern shall be used to eliminate pose variations between samples, which is a common requirement in many computer vision and machine learning tasks. The framework is specialized here in the context of a machine vision system for automated product inspection. Here, it is customary to ask the user for the identification of an anchor pattern, to be used by the automated system to normalize data before further processing. Yet, this is a very sensitive operation which is intrinsically subjective and requires high expertise. Hereto, SAFFIRE provides a unique and disruptive framework for unsupervised identification of an optimal anchor pattern in a way which is fully transparent to the user. SAFFIRE is thoroughly validated on several realistic case studies for a machine vision inspection pipeline.
