公开(公告)号：US07415136B2

公开(公告)日：2008-08-19

申请号：US11009693

申请日：2004-12-10

申请人： Scott M. Gallagher ,  Sanjay Tiwari

发明人： Scott M. Gallagher ,  Sanjay Tiwari

IPC分类号： G06K9/00

CPC分类号： G02B27/52 ,  A01K61/54 ,  Y02A40/822

摘要： An innovative optical system and method is disclosed for analyzing and uniquely identifying high-order refractive indices samples in a diverse population of nearly identical samples. The system and method are particularly suitable for ultra-fine materials having similar color, shape and features which are difficult to identify through conventional chemical, physical, electrical or optical methods due to a lack of distinguishing features. The invention discloses a uniquely configured optical system which employs polarized sample light passing through a full wave compensation plate, a linear polarizer analyzer and a quarter wave retardation plate for producing vivid color bi-refringence pattern images which uniquely identify high-order refractive indices samples in a diverse population of nearly visually identical samples. The resultant patterns display very subtle differences between species which are frequently indiscernable by conventional microscopy methods. When these images are analyzed with a trainable with a statistical learning model, such as a soft-margin support vector machine with a Gaussian RBF kernel, good discrimination is obtained on a feature set extracted from Gabor wavelet transforms and color distribution angles of each image. By constraining the Gabor center frequencies to be low, the resulting system can attain classification accuracy in excess of 90% for vertically oriented images, and in excess of 80% for randomly oriented images.

摘要翻译： 公开了一种创新的光学系统和方法，用于分析和唯一地识别几乎相同样品的不同种群中的高阶折射率样品。 该系统和方法特别适合于具有相似颜色，形状和特征的超细材料，由于缺乏区别特征而难以通过常规的化学，物理，电学或光学方法鉴定。 本发明公开了一种独特配置的光学系统，其采用通过全波补偿板的偏振采样光，线性偏振器分析仪和四分之一波长延迟板，用于产生唯一地识别高阶折射率样品的鲜明的双重折射图案图像 几乎视觉上相同样品的多样化群体。 所得到的模式在常规显微镜方法常常难以辨认的物种之间显示出非常微妙的差异。 当使用具有统计学习模型的可训练的诸如具有高斯RBF内核的软边距支持向量机来分析这些图像时，对从每个图像的Gabor小波变换和颜色分布角度提取的特征集获得良好的辨别。 通过将Gabor中心频率约束为低，所得到的系统对于垂直取向的图像可以达到超过90％的分类精度，并且对于随机取向的图像超过80％。