边缘监控线性对象骨架化用于高速摄像机
1Graduate School of Engineering, The University of Tokyo, Tokyo 113-8654, Japan.
Sensors (Basel, Switzerland)
|July 8, 2023
概括
本研究介绍了二进制图像中线性对象的快速骨架化算法. 它使用边缘监督和分支检测高效地提取物体骨,在速度和准确性方面超过现有方法.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 算法开发 算法开发
背景情况:
- 骨架化对于分析数字图像中的线性对象结构至关重要.
- 现有的方法经常在速度和准确性方面扎,特别是在高速应用中.
- 检测具有自我交叉点的复杂线性物体的骨架仍然是一个挑战.
研究的目的:
- 开发一种高速的骨化算法,用于准确地提取线性物体骨.
- 通过将计算集中在相关的对象像素上来提高效率.
- 为了有效地处理线性对象的自我交叉点.
主要方法:
- 该算法使用边缘监控来指导对象内部的搜索.
- 一个分支探测器模块用于识别和管理对象交叉点.
- 这种方法避免了处理无关的背景像素以提高速度.
主要成果:
- 该算法在各种二进制图像 (数字,绳索,电线) 上展示了可靠,准确和高效的骨架化.
- 实验性比较证实了与现有的骨架化技术相比,更高的速度,特别是对于更大的图像尺寸.
- 支部检测模块成功地解决了自我交叉的线性物体所带来的挑战.
结论:
- 拟议的高速骨架化算法为需要快速准确分析线性结构的应用提供了显著的进步.
- 它的效率和处理复杂形状的能力使其适合使用高速摄像头进行实时处理.
- 这种方法为从二进制图像中提取骨架提供了一个强大的解决方案,超过了当前最先进的技术.
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