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    • 81. 发明授权
    • Method and system for inspection of containers
    • 集装箱检验方法和系统
    • US08180139B2
    • 2012-05-15
    • US12411918
    • 2009-03-26
    • Samit K. Basu
    • Samit K. Basu
    • G06K9/00G01N23/04
    • G06T7/0004G01V5/0041G01V5/005G06K9/00201G06T11/001G06T11/008G06T15/08G06T2200/24G06T2207/10081G06T2207/30112
    • A method and system for producing images of at least one object of interest in a container. The method includes receiving three-dimensional volumetric scan data from a scan of the container, reconstructing a three-dimensional representation of the container from the three-dimensional volumetric scan data, and inspecting the three-dimensional representation to detect the at least one object of interest within the container. The method also includes re-projecting a two-dimensional image from one of the three-dimensional volumetric scan data and the three-dimensional representation, and identifying a first plurality of image elements in the two-dimensional image corresponding to a location of the at least one object of interest. The method further includes outputting the two-dimensional image with the first plurality of image elements highlighted.
    • 一种用于在容器中产生至少一个感兴趣对象的图像的方法和系统。 该方法包括从容器的扫描接收三维体积扫描数据,从三维体积扫描数据重建容器的三维表示,以及检查三维表示以检测至少一个物体 集装箱内的兴趣。 该方法还包括从三维体积扫描数据和三维表示之一重新投影二维图像,以及识别二维图像中对应于位置的第一多个图像元素 最少一个感兴趣的对象。 该方法还包括输出具有突出显示的第一多个图像元素的二维图像。
    • 82. 发明申请
    • Method and Apparatus to Facilitate Using Fused Images to Identify Materials
    • 使用融合图像识别材料的方法和装置
    • US20100310175A1
    • 2010-12-09
    • US12479322
    • 2009-06-05
    • Kevin M. Holt
    • Kevin M. Holt
    • G06K9/46G09G5/00
    • G06T5/50G06T7/0004G06T2207/10116G06T2207/30112
    • First image data (which comprises a penetrating image of an object formed using a first spectrum) and second image data (which also comprises a penetrating image of this same object formed using a second, different spectrum) is retrieved from memory and fused to facilitate identifying at least one material that comprises at least a part of this object. The aforementioned first spectrum can comprise, for example, a spectrum of x-ray energies having a high typical energy while the second spectrum can comprise a spectrum of x-ray energies with a relatively lower typical energy. By one approach, this process can associate materials as comprise the object with corresponding atomic numbers and hence corresponding elements (such as, for example, uranium, plutonium, and so forth).
    • 第一图像数据(其包括使用第一光谱形成的对象的穿透图像)和第二图像数据(其还包括使用第二,不同光谱形成的相同对象的穿透图像)从存储器检索并融合以便于识别 至少一种材料,其包含该物体的至少一部分。 上述第一光谱可以包括例如具有高典型能量的X射线能量谱,而第二光谱可以包括具有相对较低的典型能量的X射线能量谱。 通过一种方法,该过程可以将包括对象的材料与相应的原子序数相关联,并因此将相应的元素(例如,铀,钚等)相关联。
    • 83. 发明授权
    • Method of enhancing a digital image by gray-level grouping
    • 通过灰度级分组增强数字图像的方法
    • US07840066B1
    • 2010-11-23
    • US11598943
    • 2006-11-14
    • Zhiyu ChenBesma Roui AbidiMongi Al Abidi
    • Zhiyu ChenBesma Roui AbidiMongi Al Abidi
    • G06K9/00G06K9/40G06K9/38
    • G06T5/007G06T5/002G06T5/40G06T2207/10024G06T2207/10032G06T2207/10116G06T2207/20012G06T2207/20021G06T2207/20032G06T2207/20064G06T2207/20221G06T2207/20224G06T2207/30112G06T2207/30201
    • Methods for enhancing the quality of an electronic image, including automated methods for contrast enhancement and image noise reduction. In many embodiments the method provides for grouping the histogram components of a low-contrast image into the proper number of bins according to a criterion, then redistributing these bins uniformly over the grayscale, and finally ungrouping the previously grouped gray-levels. The technique is named gray-level grouping (GLG). An extension of GLG called Selective Gray-Level Grouping (SGLG), and various variations thereof are also provided. SGLG selectively groups and ungroups histogram components to achieve specific application purposes, such as eliminating background noise, enhancing a specific segment of the histogram, and so on. GLG techniques may be applied to both monochromatic grayscale images and to color images. Several preprocessing or postprocessing methods for image noise reduction are provided for use independently or for use with GLG techniques to both reduce or eliminate background noise and enhance the image contrast in noisy low-contrast images.
    • 用于提高电子图像质量的方法,包括用于对比度增强和图像噪声降低的自动化方法。 在许多实施例中,该方法提供了根据标准将低对比度图像的直方图分量分组成适当数量的分组,然后将灰度均匀地重新分布在灰度上,最后取消分组先前分组的灰度级。 该技术被命名为灰阶分组(GLG)。 还提供了GLG的扩展名称选择性灰阶分组(SGLG)及其各种变体。 SGLG选择性地组合和取消分组直方图组件以实现特定的应用目的,例如消除背景噪声,增强直方图的特定段等。 GLG技术可以应用于单色灰度图像和彩色图像。 提供用于图像噪声降低的几种预处理或后处理方法用于独立使用或与GLG技术一起使用以减少或消除背景噪声并增强嘈杂的低对比度图像中的图像对比度。