Bio-inspired object classification using polarization imaging
Bio-inspired object classification using polarization imaging
复制标题
使用偏振成像的仿生物体分类
DOI：
10.1109/icsenst.2012.6461672
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Mukul Sarkar
中科院分区：
文献类型：
--
作者：
Aroma Mahendru;Mukul Sarkar
偏振是光的固有属性。由于光从透明物体反射而产生的偏振现象不同于不透明物体。与来自不透明对象的漫反射相比，来自透明对象的镜面反射是高度偏振的。极化模式的差异可以被记录下来，并可用于机器视觉应用，如对象分类和自主代理导航。本文提出了用偏振度、偏振菲涅耳比、斯托克斯偏振度等方法对透明和不透明目标进行分类。基于偏振轮廓，还估计了透明物体的形状。
Polarization is an inherent property of light. The phenomenon of polarization by reflection of light from a transparent object differs from an opaque object. The specular reflection from the transparent object is highly polarized compared to the diffuse reflection from the opaque object. The differences in the polarization pattern can be recorded and can be used in machine vision applications like object classification and autonomous agent navigation. In this paper we present different methodologies like degree of polarization, polarization Fresnel ratio, Stokes degree of polarization to classify among transparent and opaque objects. Based on the polarization profile, the shapes of the transparent objects are also estimated.