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    • 4. 发明申请
    • Image on Paper Registration Using Transfer Surface Marks
    • 使用转印表面标记的纸张注册上的图像
    • US20110304886A1
    • 2011-12-15
    • US12813645
    • 2010-06-11
    • Martin Edward HooverJack Gaynor ElliotVladimir Kozitsky
    • Martin Edward HooverJack Gaynor ElliotVladimir Kozitsky
    • G06K15/00
    • B41J3/60B41J11/008B41J11/46G03G15/5062G03G15/5095
    • A method of adjusting the registration of an image printed on sheets. The method including determining a first image location relative to a first sheet, adjusting a second image to be printed based on the determined first image location and printing the adjusted second image to subsequent sheet(s). The first image location determination made by measuring at least one dimension of a fiducial mark disposed directly on a transfer surface. The fiducial mark formed by the engagement of the first sheet with the transfer surface, whereby an inner edge of the fiducial mark forms at least a partial outline of a periphery of the first sheet. Each measured fiducial mark dimension extending from the fiducial mark inner edge to an outer edge of the fiducial mark. The fiducial mark outer edge being disposed remote from the at least partial outline of the first sheet periphery.
    • 调整印刷在纸张上的图像的配准的方法。 该方法包括:确定相对于第一片材的第一图像位置,基于所确定的第一图像位置调整要打印的第二图像,并将经调整的第二图像打印到随后的片材。 通过测量直接设置在转印表面上的基准标记的至少一个维度来进行第一图像位置确定。 通过第一片与转印面的接合形成的基准标记,由此基准标记的内边缘至少形成第一片的周边的局部轮廓。 每个测量的基准标记尺寸从基准标记内边缘延伸到基准标记的外边缘。 基准标记外边缘远离第一片周边的至少局部轮廓设置。
    • 5. 发明申请
    • SYSTEM AND METHOD FOR SENSOR PHASING USING A SUBSTRATE EDGE SIGNAL
    • 使用基板边缘信号的传感器相位的系统和方法
    • US20090326863A1
    • 2009-12-31
    • US12145847
    • 2008-06-25
    • Vladimir KozitskyAaron Michael BurryAlex Scott Brougham
    • Vladimir KozitskyAaron Michael BurryAlex Scott Brougham
    • G06F15/00G06F17/18
    • G03G15/755G03G2215/0016
    • A system and method for measuring a substrate edge signal for image sensor phasing. An intermediate transfer substrate edge signal can be effectively mapped by a substrate edge sensor and recorded for at least one complete revolution. A substrate edge signal from an inter-document zone sampled from any region of a substrate in runtime by a process sensor can also be recorded. A comparison or cross-correlation can be applied between the bare intermediate transfer substrate edge signal and the substrate edge signal sensed in the inter-document zone. A cross-correlation algorithm returns a maximum peak value when the two signals are registered in-phase with one another. This information can then be used to register the bare belt process sensor signal and the process sensor signal over the region of interest in-phase with one another. A flat-fielding algorithm can also be applied to the phase-aligned process sensor data to remove artifacts and compensate for substrate (e.g., belt) induced non-uniformities.
    • 一种用于测量图像传感器定相的衬底边缘信号的系统和方法。 中间转印基板边缘信号可以被基板边缘传感器有效地映射并记录至少一整圈。 还可以记录来自在运行时间中由工艺传感器从衬底的任何区域采样的原文件间区域的衬底边缘信号。 可以在裸露的中间转移衬底边缘信号和在文档间区域中感测到的衬底边缘信号之间应用比较或互相关。 当两个信号彼此同相注册时,互相关算法返回最大峰值。 然后可以将该信息用于将裸带过程传感器信号和过程传感器信号注册在相关区域的相位上。 平场算法也可以应用于相位对准的过程传感器数据以去除伪影并补偿衬底(例如,带)诱导的不均匀性。
    • 6. 发明授权
    • License plate character segmentation using likelihood maximization
    • 车牌字符分割使用似然最大化
    • US09014432B2
    • 2015-04-21
    • US13464357
    • 2012-05-04
    • Zhigang FanYonghui ZhaoAaron Michael BurryVladimir Kozitsky
    • Zhigang FanYonghui ZhaoAaron Michael BurryVladimir Kozitsky
    • G06K9/00G06K9/32
    • G06K9/3258G06K2209/15
    • A method determines a license plate layout configuration. The method includes generating at least one model representing a license plate layout configuration. The generating includes segmenting training images each defining a license plate to extract characters and logos from the training images. The segmenting includes calculating values corresponding to parameters of the license plate and features of the characters and logos. The segmenting includes estimating a likelihood function specified by the features using the values. The likelihood function measures deviations between an observed plate and the model. The method includes storing a layout structure and the distributions for each of the at least one model. The method includes receiving as input an observed image including a plate region. The method includes segmenting the plate region and determining a license plate layout configuration of the observed plate by comparing the segmented plate region to the at least one model.
    • 一种方法确定车牌布局配置。 该方法包括生成表示车牌布局配置的至少一个模型。 生成包括分割训练图像,每个训练图像定义牌照以从训练图像中提取字符和徽标。 分段包括计算与车牌参数对应的值和字符和标志的特征。 分段包括使用这些值估计由特征指定的似然函数。 似然函数测量观察板和模型之间的偏差。 所述方法包括存储所述至少一个模型中的每一个的布局结构和分布。 该方法包括接收包括板区域的观察图像作为输入。 该方法包括通过将分割板区域与至少一个模型进行比较来分割板区域并确定观察板块的牌照布局配置。
    • 8. 发明授权
    • License plate optical character recognition method and system
    • 车牌光学字符识别方法及系统
    • US08644561B2
    • 2014-02-04
    • US13352554
    • 2012-01-18
    • Aaron Michael BurryVladimir KozitskyPeter Paul
    • Aaron Michael BurryVladimir KozitskyPeter Paul
    • G06K9/00
    • G06K9/6279G06K2209/01G06K2209/15
    • A method and system for recognizing a license plate character utilizing a machine learning classifier. A license plate image with respect to a vehicle can be captured by an image capturing unit and the license plate image can be segmented into license plate character images. The character image can be preprocessed to remove a local background variation in the image and to define a local feature utilizing a quantization transformation. A classification margin for each character image can be identified utilizing a set of machine learning classifiers each binary in nature, for the character image. Each binary classifier can be trained utilizing a character sample as a positive class and all other characters as well as non-character images as a negative class. The character type associated with the classifier with a largest classification margin can be determined and the OCR result can be declared.
    • 一种使用机器学习分类器识别车牌字符的方法和系统。 可以通过图像捕获单元捕获关于车辆的车牌图像,并且可以将车牌图像分割成车牌字符图像。 字符图像可以被预处理以去除图像中的局部背景变化并且使用量化变换来定义局部特征。 可以使用一组机器学习分类器来识别每个字符图像的分类容限,每个二进制的机器学习分类器用于字符图像。 可以使用字符样本作为正类和所有其他字符以及非字符图像作为负类来训练每个二进制分类器。 可以确定与具有最大分类边距的分类器相关联的字符类型,并且可以声明OCR结果。
    • 10. 发明申请
    • METHOD AND SYSTEM FOR ROBUST TILT ADJUSTMENT AND CROPPING OF LICENSE PLATE IMAGES
    • 用于稳定倾斜调整的方法和系统和许可证板图像的合并
    • US20130279758A1
    • 2013-10-24
    • US13453144
    • 2012-04-23
    • Aaron Michael BurryClaude FillionVladimir KozitskyZhigang Fan
    • Aaron Michael BurryClaude FillionVladimir KozitskyZhigang Fan
    • G06K9/46G06K9/00
    • G06K9/3258G06K9/3275G06K9/342G06K2209/01
    • Methods, systems and processor-readable media for robust tilt adjustment and cropping of a license plate image. A vehicle image can be captured by an image-capturing unit and converted to a binary image utilizing a binarization approach. A long run within the binary image can then be removed and a morphological filtering can be applied to break an unwanted connection between characters due to a license plate frame and an image noise. A connected component (CC) within the image can be identified and screened based on a number of key metrics to remove a most likely candidate character connected component. A line-fit based iterative search process can then be performed for robust tilt removal and vertical cropping of the license plate image to obtain a tight bounding box on the license plate characters if sufficient candidate characters remain after the search process. Otherwise, the region of interest can be rejected.
    • 方法,系统和处理器可读介质,用于强大的倾斜调整和车牌图像的裁剪。 车辆图像可以由图像捕获单元捕获并且使用二值化方法被转换成二值图像。 然后可以去除二进制图像中的长时间,并且可以应用形态滤波来打破由于牌照框架和图像噪声引起的字符之间的不期望的连接。 可以基于多个关键指标来识别和屏蔽图像内的连接分量(CC),以消除最可能的候选字符连接分量。 然后可以执行基于线拟合的迭代搜索过程,用于强制倾斜移除和车牌图像的垂直裁剪,以便在搜索过程之后剩余足够的候选人物时,在车牌字符上获得紧密的边界框。 否则,可以拒绝感兴趣的区域。