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    Soft proofing system
    31.
    发明授权
    Soft proofing system 有权
    软打样系统

    公开(公告)号：US09049405B2

    公开(公告)日：2015-06-02

    申请号：US13563100

    申请日：2012-07-31

    Applicant: Ingeborg Tastl ,  Eric Hoarau ,  Ehud Chatow ,  Steven J Simske ,  John Ludd Recker

    Inventor： Ingeborg Tastl ,  Eric Hoarau ,  Ehud Chatow ,  Steven J Simske ,  John Ludd Recker

    IPC: G06F15/00 ,  H04N1/60

    CPC classification number: H04N1/60 ,  H04N1/6013 ,  H04N1/622

    Abstract: A soft proof system includes a display module and a manager. The display module displays a visual representation of a print product, and a color array expressing a tolerance range of a color component of the visual representation and a target color within the range. Via the manager, a visualization function produces the visual representation and the color array according to a soft proof array. A tolerance selection function, associated with the display module, enables selection of the tolerance range for at least a portion of the print product, wherein the selection is expressed on the display in the visual representation and in the color array.

    Abstract translation: 软质防伪系统包括显示模块和管理器。 显示模块显示打印产品的视觉表示，以及表示视觉表示的颜色分量的容许范围和该范围内的目标颜色的颜色阵列。 通过经理，可视化功能根据软性证明阵列产生视觉表示和颜色阵列。 与显示模块相关联的公差选择功能使得能够选择打印产品的至少一部分的公差范围，其中在视觉表示和颜色阵列中的显示器上表示选择。

    Redigitization System and Service
    32.
    发明申请
    Redigitization System and Service 有权
    赎回制度和服务

    公开(公告)号：US20150049949A1

    公开(公告)日：2015-02-19

    申请号：US14364743

    申请日：2012-04-29

    Applicant: Steven J Simske ,  Samson J. Liu

    Inventor： Steven J Simske ,  Samson J. Liu

    IPC: G06K9/18 ,  G06K9/00

    CPC classification number: G06K9/18 ,  G06K9/00442 ,  G06K9/03

    Abstract: A system and method to error correct extant electronic documents is disclosed. An electronic document may be rasterized to obtain a pixel representation of the electronic document (e.g., raster image). One or more optical character recognition (OCR) tasks may be performed on the raster image of the electronic document. Errors discovered by the OCR tasks may be corrected and a customized error corrected version of the electronic document may be created and stored. If the author of the electronic document is known, the raster image may be compared to a personalized tf*idf error dictionary associated with the author to determine known OCR errors specific to the author. The raster image may also be compared to a personalized electronic error dictionary associated with the author to determine known typographical errors specific to the author.

    Abstract translation: 公开了一种错误纠正现有电子文档的系统和方法。 电子文档可以被光栅化以获得电子文档的像素表示（例如，光栅图像）。 可以在电子文档的光栅图像上执行一个或多个光学字符识别（OCR）任务。 可能会纠正由OCR任务发现的错误，并且可以创建和存储电子文档的定制错误更正版本。 如果电子文档的作者是已知的，则光栅图像可以与与作者相关联的个性化tf * idf错误字典进行比较，以确定作者特有的已知OCR错误。 也可以将光栅图像与与作者相关联的个性化电子错误字典进行比较，以确定作者特有的已知印刷错误。

    Workflow-Enhancing Device, System and Method
    33.
    发明申请
    Workflow-Enhancing Device, System and Method 有权
    工作流增强设备，系统和方法

    公开(公告)号：US20130290963A1

    公开(公告)日：2013-10-31

    申请号：US13810697

    申请日：2010-12-20

    Applicant: Steven J Simske ,  Guy Adams

    Inventor： Steven J Simske ,  Guy Adams

    IPC: G06F9/44

    CPC classification number: G06F9/44 ,  G06Q10/06 ,  G06Q10/08 ,  G06Q10/10 ,  G06Q50/18 ,  G06Q50/22

    Abstract: Systems and methods for performing task execution in a workflow are described. The system comprises at least one modular device (12, 42, 82, 91, 105, 112, 122, 142, 162, 212, 214, 222, 224, 232, 234, 362, 364, 372, 374, 382) comprising a sensor device (14, 44, 84, 92, 106, 114, 144, 164) that is interchangeably coupled to a processor device (72, 95, 103, 120, 150, 210, 220, 230, 360, 370, 380), a software service (20, 60, 78, 96, 96a, 130, 172, 216, 226, 236, 366, 376, 386) and an electronic workflow system (22, 62, 89, 98, 134, 174, 240, 352), where the sensor may correspond to at least one particular task of a workflow, and the software service may control operation of the modular device and generates metadata from task information received by the sensor of the modular devices for the electronic workflow system.

    Abstract translation: 描述用于在工作流中执行任务执行的系统和方法。 该系统包括至少一个模块化装置（12,42,82,91,105,112,122,142,162,212,214,222,224,232,234,362,364,372,474,382,482,346,346,374,374,384,382,482,384,342,482,346,346,342,384,382,482,342,482,346,442,424,342,314,482,4 传感器装置（14,44,84,92,106,114,144,164），其可互换地耦合到处理器装置（72,95,103,120,150,210,220,230,360,370,380 ），软件服务（20,60,78,96,96a，130,172,216,226,236,336,376,386）和电子工作流系统（22,62,89,98,134,174， 其中所述传感器可以对应于工作流的至少一个特定任务，并且所述软件服务可以控制所述模块化设备的操作并且从所述电子工作流系统的模块化设备的传感器接收的任务信息生成元数据 。

    Keyword determination based on a weight of meaningfulness
    34.
    发明授权
    Keyword determination based on a weight of meaningfulness 失效
    基于意义重量的关键词确定

    公开(公告)号：US08375022B2

    公开(公告)日：2013-02-12

    申请号：US12938288

    申请日：2010-11-02

    Applicant: Helen Balinsky ,  Alexander Balinsky ,  Steven J Simske

    Inventor： Helen Balinsky ,  Alexander Balinsky ,  Steven J Simske

    IPC: G06F7/00

    CPC classification number: G06F17/30675

    Abstract: Example embodiments relate to keyword determination based on a weight of meaningfulness. In example embodiments, a computing device may determine a number of occurrences of a word in a particular document and may then determine a weight of meaningfulness for the word based on the number of occurrences. The computing device may then add the word to a set of keywords for the document based on the weight of meaningfulness.

    Abstract translation: 示例性实施例涉及基于有意义的权重的关键字确定。 在示例实施例中，计算设备可以确定特定文档中的单词的出现次数，然后可以基于出现次数来确定单词的有意义的权重。 然后，计算设备可以基于有意义的权重将单词添加到文档的一组关键字。

    GENERATING A REGRESSIVE FNFORMATION OBJECT
    38.
    发明申请
    GENERATING A REGRESSIVE FNFORMATION OBJECT 审中-公开
    生成一个复原的FNFORMATION对象

    公开(公告)号：US20150220521A1

    公开(公告)日：2015-08-06

    申请号：US14419793

    申请日：2012-08-30

    Applicant: Steven J Simske ,  Marie Vans

    Inventor： Steven J Simske ,  Marie Vans

    IPC: G06F17/30

    CPC classification number: G06F17/30011 ,  G06K19/06037 ,  G06K19/06046 ,  G06Q10/0633 ,  G06Q10/103

    Abstract: Example embodiments disclosed hereto relate So generating a regressive information object, information is encoded into an information object at states in a workflow. Information, is encoded such that information encoded in a last state in the workflow is readable by an information object reader and information, encoded in states prior to the last state is not readable by fee information object reader.

    Abstract translation: 所涉及的示例性实施例因此，生成回归信息对象，信息在工作流中的状态被编码成信息对象。 信息被编码，使得在工作流程中以最后状态编码的信息被信息对象读取器读取，并且在最后状态之前以状态编码的信息不能被费用信息对象读取器读取。

    Selecting metrics for substrate classification
    39.
    发明授权
    Selecting metrics for substrate classification 有权
    选择底物分类的指标

    公开(公告)号：US08917930B2

    公开(公告)日：2014-12-23

    申请号：US13466170

    申请日：2012-05-08

    Applicant: Steven J Simske ,  Malgorzata M Sturgill ,  Guy Adams ,  Paul S Everest

    Inventor： Steven J Simske ,  Malgorzata M Sturgill ,  Guy Adams ,  Paul S Everest

    IPC: G06K9/00

    CPC classification number: G06K9/00577

    Abstract: Methods for selecting metrics for substrate classification, and apparatus to perform such methods. The methods include determining a value of a metric from an image of a substrate sample for each substrate sample of a plurality of substrate samples, wherein the metric is indicative of a surface texture of each substrate sample and iteratively assigning substrate samples of the plurality of substrate samples to an aggregate of a particular number of aggregates in response to a value of the metric for each substrate sample until a convergence of clustering is deemed achieved, then determining an indication of cluster tightness of the particular number of aggregates. The methods further include selecting or ignoring the metric for substrate classification in response to the indication of cluster tightness of the particular number of aggregates.

    Abstract translation: 用于选择底物分类的度量的方法以及执行这些方法的装置。 所述方法包括从多个衬底样品的每个衬底样品的衬底样品的图像中确定度量的值，其中度量指示每个衬底样品的表面纹理并迭代地分配多个衬底的衬底样品 响应于每个底物样品的度量的值而将样品聚集到特定数量的聚集体，直到聚类的收敛被认为实现，然后确定特定数目的聚集体的聚类紧密度的指示。 所述方法还包括响应于特定数量的聚集体的簇紧密度的指示来选择或忽略用于底物分类的度量。

    Printer Sample Feature Set
    40.
    发明申请
    Printer Sample Feature Set 有权
    打印机样品特征集

    公开(公告)号：US20140333969A1

    公开(公告)日：2014-11-13

    申请号：US14347316

    申请日：2012-01-31

    Applicant: Steven J Simske ,  Malgorzata M. Sturgill ,  Jason S. Aronoff ,  Guy Adams ,  Paul S. Everest

    Inventor： Steven J Simske ,  Malgorzata M. Sturgill ,  Jason S. Aronoff ,  Guy Adams ,  Paul S. Everest

    IPC: G06K15/02

    CPC classification number: G06K15/1881 ,  H04N1/32144 ,  H04N1/40062 ,  H04N1/405 ,  H04N2201/3271

    Abstract: A system can comprise a memory to store machine readable instructions and a processing unit to access the memory and execute the machine readable instructions. The machine readable instructions can comprise a feature set extractor to extract a feature set from each of a plurality of digital images of print samples. The feature set can be a filtered feature set that includes a feature set characterizing a printer that printed a given print sample of the print samples. The machine readable instructions can also comprise a cluster component to determine clusters of the print samples based on the feature set of each of the plurality of scanned images of the print samples. The machine readable instructions can further comprise a printer identifier to identify the printer of the print samples based on the clusters of the print samples.

    Abstract translation: 系统可以包括用于存储机器可读指令的存储器和用于访问存储器并执行机器可读指令的处理单元。 机器可读指令可以包括特征集提取器，以从打印样本的多个数字图像中的每一个提取特征集。 该功能集可以是一个过滤的功能集，其中包含一个功能集，表征打印机打印样本的给定打印样本的打印机。 机器可读指令还可以包括基于打印样本的多个扫描图像中的每一个的特征集来确定打印样本的群集的群集组件。 机器可读指令还可以包括打印机标识符，以基于打印样本的聚类来识别打印样本的打印机。

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