METHODS AND SYSTEMS FOR PERFORMING BIOMETRIC FUNCTIONS
    1.
    发明公开
    METHODS AND SYSTEMS FOR PERFORMING BIOMETRIC FUNCTIONS 审中-公开
    方法和系统实施生物特征

    公开(公告)号:EP2766716A2

    公开(公告)日:2014-08-20

    申请号:EP12853231.4

    申请日:2012-10-04

    申请人: Lumidigm, Inc.

    IPC分类号: G01N21/86

    CPC分类号: G06K9/0004

    摘要: Methods and sensors are disclosed for executing a biometric function. Illumination light is generated and directed to a deformable layer when the deformable layer is in a state of deformation resulting from pressure applied to the deformable layer by a skin site. Light scattered from the deformable layer is received. A fingerprint pattern of the skin site is determined from the received light. The biometric function is performed with the determined fingerprint pattern.

    OPTICAL TOPOGRAPHIC IMAGING
    2.
    发明公开
    OPTICAL TOPOGRAPHIC IMAGING 有权
    OPTISCHE TOPOGRAPHISCHE BILDGEBUNG

    公开(公告)号:EP2697970A1

    公开(公告)日:2014-02-19

    申请号:EP12771778.3

    申请日:2012-04-11

    申请人: Lumidigm, Inc.

    IPC分类号: H04N7/18

    摘要: Methods and devices of studying a predefined portion of an object having a feature of interest are disclosed. The feature of interest defines a class of objects that includes the object. Light sources directly illuminate the object from different illumination directions. The light sources are maintained in a stable configuration relative to the object. For each illumination direction, an image is generated from light scattered from the object with a camera maintained in a stable configuration relative to the light sources. A methodology derived from machine learning for the class of objects is applied to filter the generated images are filtered for a characteristic consistent with the feature of interest. Surface gradients are determined from the filtered images and integrated to generate a topography of a surface of the object.

    摘要翻译: 公开了研究具有感兴趣特征的对象的预定义部分的方法和装置。 感兴趣的特征定义了一类包含该对象的对象。 光源从不同的照明方向直接照亮物体。 光源相对于物体保持在稳定的构造。 对于每个照明方向,从相对于光源维持在稳定配置的照相机的物体散射的光产生图像。 应用从对象类的机器学习得出的方法来过滤生成的图像,以便与感兴趣的特征一致的特征进行过滤。 从滤波图像确定表面梯度,并将其整合以产生物体表面的形貌。