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    • 3. 发明申请
    • 3D OBJECT ROTATION-BASED MECHANICAL PARTS SELECTION THROUGH 2D IMAGE PROCESSING
    • 基于二维图像处理的三维目标旋转机械部件选择
    • WO2017074567A1
    • 2017-05-04
    • PCT/US2016/050892
    • 2016-09-09
    • EMPIRE TECHNOLOGY DEVELOPMENT LLC
    • YOSHIDA, Naofumi
    • G03B19/02G03B7/14H04N5/225H04N21/278H04N1/64
    • G06T7/0004G06K9/00208G06K9/64G06K2209/19G06T3/60G06T2200/04G06T2207/30164G06T2219/2016
    • Technologies are generally described for 3D object recognition through 2D image processing based on white balancing and object-rotation in machine vision systems. According to some examples, image recognition of an object captured with a camera under insufficient lighting may be achieved through white balancing. Processing cost reduction may be achieved in the learning process for image recognition through, automatic generation of rotated 2D Images of target objects to be detected, such as machine parts, from a small number of 2D images of a target object and generation of a 3D image of the target object from the rotated 2D images. Image recognition may thus be ensured even under insufficient lighting through execution of the image recognition process for multiple images and learning the successful recognition results. Some examples may be implemented in mechanical parts selection, where 2D images of the parts may be available beforehand.
    • 基于机器视觉系统中白平衡和物体旋转的2D图像处理技术通常用于3D物体识别。 根据一些示例,可以通过白平衡来实现在照明不足的情况下通过照相机捕获的对象的图像识别。 在用于图像识别的学习过程中可以通过从目标对象的少量2D图像自动生成诸如机器部件的待检测目标对象的旋转2D图像并且生成3D图像来实现处理成本降低 来自旋转的2D图像的目标对象的图像。 因此,即使在通过执行多个图像的图像识别过程并且学习成功的识别结果而导致光照不足的情况下,也可以确保图像识别。 一些示例可以在机械部件选择中实施,其中部件的2D图像可以预先获得。