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    • 1. 发明授权
    • Object based adaptive document resizing
    • 基于对象的自适应文档调整大小
    • US08423900B2
    • 2013-04-16
    • US12544561
    • 2009-08-20
    • Claude S. FillionVishal MongaZhigang FanRamesh Nagarajan
    • Claude S. FillionVishal MongaZhigang FanRamesh Nagarajan
    • G06F3/00G06F3/14
    • G06T11/60G06K9/00456G06T2207/30176
    • What is disclosed is a resizing method that utilizes segmentation information to classify objects found within a document and then selects the most appropriate resizing technique for each identified object. The present method employs readily available document parsers to reliably extract objects. e.g. text, background, images, graphics, etc., which compose the document. Information obtained from a document parser is utilized to identify the document components for classification. The extracted objects are then classified according to their object type. Each of classified objects are then resized using a resizing technique having been pre-selected for the object type based on their respective abilities to resize certain types of document content over other resizing techniques. The present method advantageously extends smart or content-based scaling and is especially useful for N-up or variable-information printing. The present method finds its intended uses in enhancing N-up and handout options currently provided in a variety of print-drivers.
    • 所公开的是一种调整大小的方法,其利用分段信息对在文档中找到的对象进行分类,然后为每个识别的对象选择最合适的调整大小的技术。 本方法使用容易获得的文档解析器来可靠地提取对象。 例如 文本,背景,图像,图形等等。 从文档解析器获得的信息用于识别用于分类的文档组件。 然后将提取的对象根据其对象类型进行分类。 然后,使用已经针对对象类型预先选择的调整大小的技术来调整每个分类对象的大小,这些大小基于它们各自的能力,以便通过其他大小调整技术调整某些类型的文档内容的大小。 本方法有利地扩展智能或基于内容的缩放,并且对于N上或可变信息打印特别有用。 本方法用于增强目前在各种打印驱动程序中提供的N-up和Handout选项。
    • 2. 发明申请
    • OBJECT BASED ADAPTIVE DOCUMENT RESIZING
    • 基于对象的自适应文档
    • US20110047505A1
    • 2011-02-24
    • US12544561
    • 2009-08-20
    • Claude S. FillionVishal MongaZhigang FanRamesh Nagarajan
    • Claude S. FillionVishal MongaZhigang FanRamesh Nagarajan
    • G06F3/048
    • G06T11/60G06K9/00456G06T2207/30176
    • What is disclosed is a resizing method that utilizes segmentation information to classify objects found within a document and then selects the most appropriate resizing technique for each identified object. The present method employs readily available document parsers to reliably extract objects. e.g. text, background, images, graphics, etc., which compose the document. Information obtained from a document parser is utilized to identify the document components for classification. The extracted objects are then classified according to their object type. Each of classified objects are then resized using a resizing technique having been pre-selected for the object type based on their respective abilities to resize certain types of document content over other resizing techniques. The present method advantageously extends smart or content-based scaling and is especially useful for N-up or variable-information printing. The present method finds its intended uses in enhancing N-up and handout options currently provided in a variety of print-drivers.
    • 所公开的是一种调整大小的方法,其利用分段信息对在文档中找到的对象进行分类,然后为每个识别的对象选择最合适的调整大小的技术。 本方法使用容易获得的文档解析器来可靠地提取对象。 例如 文本,背景,图像,图形等等。 从文档解析器获得的信息用于识别用于分类的文档组件。 然后将提取的对象根据其对象类型进行分类。 然后,使用已经针对对象类型预先选择的调整大小的技术来调整每个分类对象的大小,这些大小基于它们各自的能力,以便通过其他大小调整技术调整某些类型的文档内容的大小。 本方法有利地扩展智能或基于内容的缩放,并且对于N上或可变信息打印特别有用。 本方法用于增强目前在各种打印驱动程序中提供的N-up和Handout选项。
    • 3. 发明授权
    • Resizing a digital document image via background content removal
    • 通过背景内容删除调整数字文档图像的大小
    • US08274533B2
    • 2012-09-25
    • US12369790
    • 2009-02-12
    • Claude S. FillionVishal MongaZhigang FanRamesh Nagarajan
    • Claude S. FillionVishal MongaZhigang FanRamesh Nagarajan
    • G09G5/02
    • G06T3/0012
    • What is disclosed is a system and method for performing a background deletion that exploits both local and global context to remove background and other white space between objects with the aim of retaining structural relationships between objects in the document. A document image is received and seams are carved through the image. Seams composed of uniform background pixels are identified. Adjacent seams containing background pixels are collected into groups of seams. The background seam groups are classified according to their widths. A target number of seams to be removed for each background seam group is then determined based on the classification. Seam groups which are wider will have at least the same or a greater target number of seams to be deleted therefrom than will seam groups of narrower widths. The document image is then resized by deleting seams from the seam groups based on the assigned target number.
    • 公开的是用于执行背景删除的系统和方法,其利用本地和全局上下文来移除对象之间的背景和其他空白空间,目的是保留文档中的对象之间的结构关系。 收到文件图像,并通过图像刻成接缝。 识别由均匀背景像素构成的接缝。 包含背景像素的相邻接缝被收集成一组接缝。 背景缝组根据其宽度进行分类。 然后基于分类确定要为每个背景接缝组去除的目标接缝数目。 与较窄宽度的接缝组相比,更宽的接缝组将具有至少相同或更大的目标数量的接缝。 然后通过基于分配的目标号码从接缝组中删除接缝来调整文档图像的大小。
    • 4. 发明授权
    • Iterative selection of pixel paths for content aware image resizing
    • 用于内容感知图像调整大小的像素路径的迭代选择
    • US08270771B2
    • 2012-09-18
    • US12330879
    • 2008-12-09
    • Claude S. FillionVishal MongaRamesh Nagarajan
    • Claude S. FillionVishal MongaRamesh Nagarajan
    • G06K9/32G06K9/36G06K15/10G09G5/00G09G5/02H04N5/44H04N9/74H04N3/223H04N1/393
    • G06T3/00
    • What is disclosed is a method for iterative seam selection in an image resizing system utilizing a seam carving technique. In one embodiment, an importance map is generated for a received source image. Seams are carved through the image from one edge to an opposite edge. An energy is computed for each seam based on pixel importance values. A distance is computed from each seam to a previously selected seam. A weighting for each seam is computed using a defined weighting function and the calculated seam distances. The weighting is applied to the energy of each seam produce a revised energy for each seam. A seam is selected based on the produced revised energy. The image is resized at a location of the selected seam. The process repeats until the image has been resized to a desired target output dimension. In such a manner, unnatural image resizing results are avoided.
    • 公开的是一种利用接缝雕刻技术的图像调整系统中迭代缝选择的方法。 在一个实施例中,为接收的源图像生成重要性图。 接缝通过图像从一个边缘到另一个边缘被雕刻。 基于像素重要性值计算每个接缝的能量。 从每个接缝到先前选择的接缝计算距离。 使用定义的加权函数和计算的接缝距离来计算每个接缝的加权。 权重应用于每个接缝的能量产生每个接缝的修正能量。 根据产生的修正能量选择接缝。 图像在所选缝的位置被调整大小。 该过程重复,直到图像被调整到期望的目标输出尺寸。 以这种方式,避免了不自然的图像调整结果。
    • 6. 发明授权
    • Systems and methods to resize document content
    • 调整文档内容大小的系统和方法
    • US08352856B2
    • 2013-01-08
    • US12616423
    • 2009-11-11
    • Claude S. FillionVishal MongaZhigang Fan
    • Claude S. FillionVishal MongaZhigang Fan
    • G06F17/00
    • G06F17/2229G06F17/211
    • A system resizes content within a document that includes a document segmenter that receives a document that contains content. The document segmenter analyzes the content within the document and segments the content into a plurality of object types. An object priority applicator determines a class value associated with each object type. A location scaler identifies a datum point for each object type within the document, wherein each datum point maintains a relative location to one another regardless of document resizing. An object sizing component resizes each object based at least in part upon the class value.
    • 系统调整文档内的内容大小,其中包含文档分割器,该文档分割器接收包含内容的文档。 文档分割器分析文档内的内容并将内容分段成多个对象类型。 对象优先级施加器确定与每个对象类型相关联的类值。 位置缩放器识别文档中每个对象类型的基准点,其中每个基准点保持彼此的相对位置,而不管文档大小调整。 至少部分基于类值,对象大小调整组件调整每个对象的大小。
    • 7. 发明授权
    • Hybrid importance maps for content aware digital image resizing
    • 用于内容感知数字图像调整大小的混合重要性图
    • US08134578B2
    • 2012-03-13
    • US12174767
    • 2008-07-17
    • Claude S. FillionVishal Monga
    • Claude S. FillionVishal Monga
    • G09G5/00
    • G06T3/40G06T7/11G06T2207/20164
    • What is disclosed is a novel system and method for content-aware resizing of a digital image. To take advantage of the characteristics of various importance maps generated for the image using different operators such as, for example, gradient, entropy, probabilistic operators, and the like, a method is provided herein for combining generated pixel importance maps. The present method uses a weighted combination of pixel importance maps—one corresponding to each image operator, to produce a hybrid map for all the image. The image can then be resized based on this hybrid map. The present method provides a high degree of image resizing flexibility and has broad applicability across differing classes of images and applications such as display, printing, packaging, and other document image processing software performing document layout, image personalization, and the like.
    • 公开的是用于数字图像的内容感知调整大小的新型系统和方法。 为了利用使用诸如梯度,熵,概率运算符等的不同运算符为图像生成的各种重要性图的特征,本文提供了一种用于组合生成的像素重要性图的方法。 本方法使用对应于每个图像算子的像素重要性图的加权组合,以产生所有图像的混合图。 然后可以基于该混合图来调整图像大小。 本方法提供了高度的图像调整大小的灵活性,并且在不同类别的图像和应用(诸如执行文档布局,图像个性化等)的显示,打印,打包和其它文档图像处理软件等方面具有广泛的适用性。
    • 8. 发明授权
    • Smart image resizing with color-based entropy and gradient operators
    • 使用基于颜色的熵和梯度运算符进行智能图像调整
    • US08340411B2
    • 2012-12-25
    • US12718297
    • 2010-03-05
    • Claude S. FillionVishal MongaRaja Bala
    • Claude S. FillionVishal MongaRaja Bala
    • G06K9/00
    • G06K9/00
    • A system and method for resizing a digitally represented color image are presented. A color image with pixels defined by luminance and at least one chrominance value is received. For each pixel of the color image, a luminance spatial variation and respective chrominance spatial variations in the respective neighborhood of the each pixel are computed. The luminance spatial variation and the respective chrominance spatial variations are combined to produce a respective importance value for each pixel. Selected pixels are identified based upon their respective importance values and are removed by seam carving of the color image. The seam carving identifies seams of pixels based upon the respective importance values of pixels within the seams of pixels to create a resized color image. The resized color image is produced to an image output device.
    • 提出了一种用于调整数字化颜色图像大小的系统和方法。 接收由亮度和至少一个色度值定义的像素的彩色图像。 对于彩色图像的每个像素,计算每个像素的相应邻域中的亮度空间变化和相应的色度空间变化。 亮度空间变化和相应的色度空间变化被组合以产生每个像素的相应重要性值。 基于它们各自的重要性值来识别所选择的像素,并且通过彩色图像的缝隙去除。 接缝雕刻基于像素接缝内的像素的相应重要性值来识别接缝像素,以产生调整大小的彩色图像。 调整大小的彩色图像被产生到图像输出装置。
    • 9. 发明授权
    • Photoreceptor motion quality estimation using multiple sampling intervals
    • 使用多个采样间隔的光感受器运动质量估计
    • US08599435B2
    • 2013-12-03
    • US12617117
    • 2009-11-12
    • Peter PaulClaude S. Fillion
    • Peter PaulClaude S. Fillion
    • G06F15/00
    • G03G15/5037G03G15/5033G03G15/5062G03G2215/00075
    • What is disclosed is a novel system and method for determining printer component velocity variations by analyzing multiple page test patterns. A test pattern, such as ladder chart targets, is produced that extends across multiple pages. Corresponding page sync signals are recorded and used to maintain phase coherence when analyzing scanned images associated with the multiple pages. An algorithm determines the ladder rung positions and the average photoreceptor velocity between each ladder rung on each scanned image for each page. Interpolation is used for proper phase alignment of the velocity data that spans multiple pages. The long assembly of phase coherent velocity data is then analyzed in one embodiment to determine its frequency content and to estimate the photoreceptor motion quality error sources. Based upon these estimated error sources, a trouble condition or pending maintenance problem with the printer is able to be indentified.
    • 公开的是通过分析多页测试图案来确定打印机部件速度变化的新型系统和方法。 产生了跨越多个页面的测试模式,例如梯形图目标。 当分析与多页相关联的扫描图像时,相应的页同步信号被记录并用于维持相位相干性。 算法确定梯形梯级位置以及每个梯形图梯度在每页扫描图像上的平均感光体速度。 插值用于跨越多页的速度数据的正确相位对齐。 然后在一个实施例中分析相位相干速度数据的长组件以确定其频率含量并估计感光体运动质量误差源。 基于这些估计的误差源,可以识别打印机的故障状况或待处理的维护问题。
    • 10. 发明授权
    • Method for automatic license plate recognition using adaptive feature set
    • 使用自适应特征集自动车牌识别的方法
    • US08447112B2
    • 2013-05-21
    • US12971643
    • 2010-12-17
    • Peter PaulAaron Michael BurryWilliam J. HannawayClaude S. Fillion
    • Peter PaulAaron Michael BurryWilliam J. HannawayClaude S. Fillion
    • G06K9/18G06K9/00
    • G06K9/00G06K2209/15
    • A method for determining a confidence level to be used in identifying a vehicle. The method includes receiving a vehicle image, extracting a license plate image from the at least one vehicle image, determining a license plate number and associated confidence level based upon the license plate image, and comparing the associated confidence level against a confidence threshold. If the associated confidence level is below the confidence threshold, the method further includes extracting auxiliary data from the at least one vehicle image, corresponding the extracted auxiliary data and a set of stored auxiliary data, and updating the associated confidence level to produce an updated confidence level based upon the correspondence of the extracted auxiliary data and the set of stored auxiliary data.
    • 一种用于确定用于识别车辆的可信度水平的方法。 所述方法包括接收车辆图像,从所述至少一个车辆图像提取车牌图像,基于所述车牌图像来确定车牌号码和相关联的置信度,以及将所述相关联的可信度与置信阈值进行比较。 如果相关联的置信水平低于置信度阈值,则该方法还包括从所述至少一个车辆图像提取辅助数据,对应于所提取的辅助数据和一组存储的辅助数据,以及更新相关联的置信水平以产生更新的置信度 基于所提取的辅助数据和所存储的辅助数据的集合的对应关系。