License plate character segmentation using likelihood maximization
    1.
    发明授权
    License plate character segmentation using likelihood maximization 有权
    车牌字符分割使用似然最大化

    公开(公告)号:US09014432B2

    公开(公告)日:2015-04-21

    申请号:US13464357

    申请日:2012-05-04

    CPC classification number: G06K9/3258 G06K2209/15

    Abstract: 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.

    Abstract translation: 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。

    Methods and systems for enhancing the performance of automated license plate recognition applications utilizing multiple results
    2.
    发明授权
    Methods and systems for enhancing the performance of automated license plate recognition applications utilizing multiple results 有权
    利用多个结果提高自动车牌识别应用性能的方法和系统

    公开(公告)号:US08781172B2

    公开(公告)日:2014-07-15

    申请号:US13435875

    申请日:2012-03-30

    CPC classification number: G06K9/3258 G06K2209/15

    Abstract: Methods, systems and processor-readable media for enhancing performance of an automated license plate recognition system utilizing multiple results. Multiple images can be captured as a vehicle passes through an observation zone and each image can be processed utilizing an ALPR unit to obtain a plate code result and associated confidence values. Iterative processing of character level information across an OCR code followed by a higher level error checking based on learned context information can be performed. A string correlation approach can be employed to optimally align the OCR code from multiple images despite noise factors. The OCR confidence and state mask information can then be leveraged to select a character for an output plate code taking into account the ALPR error sources.

    Abstract translation: 用于增强利用多个结果的自动车牌识别系统的性能的方法,系统和处理器可读介质。 当车辆通过观察区域时,可以捕获多个图像,并且可以利用ALPR单元处理每个图像以获得平板码结果和相关的置信度值。 可以执行跨越OCR代码的字符级信息的迭代处理,随后基于学习的上下文信息进行更高级别的错误检查。 可以采用字符串相关方法来最佳地对齐来自多个图像的OCR码,尽管噪声因子。 然后可以利用OCR置信度和状态掩码信息来考虑ALPR误差源来选择输出板码的字符。

    License plate optical character recognition method and system
    4.
    发明授权
    License plate optical character recognition method and system 有权
    车牌光学字符识别方法及系统

    公开(公告)号:US08644561B2

    公开(公告)日:2014-02-04

    申请号:US13352554

    申请日:2012-01-18

    CPC classification number: G06K9/6279 G06K2209/01 G06K2209/15

    Abstract: 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.

    Abstract translation: 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。

    METHODS AND SYSTEMS FOR OPTIMIZED PARAMETER SELECTION IN AUTOMATED LICENSE PLATE RECOGNITION
    5.
    发明申请
    METHODS AND SYSTEMS FOR OPTIMIZED PARAMETER SELECTION IN AUTOMATED LICENSE PLATE RECOGNITION 有权
    自动许可证认证中优化参数选择的方法与系统

    公开(公告)号:US20130294653A1

    公开(公告)日:2013-11-07

    申请号:US13466068

    申请日:2012-05-07

    CPC classification number: G06K9/3258 G06K2209/15

    Abstract: A system and method for automatically recognizing license plate information, the method comprising receiving an image of a license plate, and generating a plurality of image processing data sets, wherein each image processing data set of the plurality of image processing data sets is associated with a score of a plurality of scores by a scoring process comprising determining one or more image processing parameters, generating the image processing data set by processing the image using the one or more image processing parameters, generating the score based on the image processing data, and associating the image processing data set with the score.

    Abstract translation: 一种用于自动识别车牌信息的系统和方法,所述方法包括:接收车牌的图像,以及生成多个图像处理数据集,其中所述多个图像处理数据集中的每个图像处理数据集与 通过评分处理得出多个分数,包括确定一个或多个图像处理参数,通过使用一个或多个图像处理参数处理图像来生成图像处理数据集,基于图像处理数据生成分数,以及关联 图像处理数据与分数集合。

    METHOD AND SYSTEM FOR ROBUST TILT ADJUSTMENT AND CROPPING OF LICENSE PLATE IMAGES
    6.
    发明申请
    METHOD AND SYSTEM FOR ROBUST TILT ADJUSTMENT AND CROPPING OF LICENSE PLATE IMAGES 审中-公开
    用于稳定倾斜调整的方法和系统和许可证板图像的合并

    公开(公告)号:US20130279758A1

    公开(公告)日:2013-10-24

    申请号:US13453144

    申请日:2012-04-23

    CPC classification number: G06K9/3258 G06K9/3275 G06K9/342 G06K2209/01

    Abstract: 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.

    Abstract translation: 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。

    SYSTEMS AND METHODS FOR LICENSE PLATE RECOGNITION TO ENABLE ADVANCE ORDER PICKUP
    7.
    发明申请
    SYSTEMS AND METHODS FOR LICENSE PLATE RECOGNITION TO ENABLE ADVANCE ORDER PICKUP 审中-公开
    许可证认证的系统和方法,以便能够提前订购PICKUP

    公开(公告)号:US20130204719A1

    公开(公告)日:2013-08-08

    申请号:US13364768

    申请日:2012-02-02

    CPC classification number: G06Q50/12

    Abstract: An embodiment generally relates to systems and methods for processing orders associated with an establishment. In particular, a customer can submit a remote order for goods offered by the establishment, along with an associated license plate number of a vehicle that is to pick up the order. An image capture device can capture images of a vehicle on the premises of the establishment, and provide the images to a processing module which use automatic license plate recognition (ALPR) techniques to determine license plate data of the vehicle. The processing module can further examine an order list to determine if the license plate data is associated with an order on the order list, and, if so, add the order to a priority queue.

    Abstract translation: 一个实施方案通常涉及用于处理与企业相关联的订单的系统和方法。 特别地,客户可以提交由机构提供的货物的远程订单以及要接收订单的车辆的相关牌照号码。 图像捕获设备可以在建筑物的房屋内捕获车辆的图像,并将图像提供给使用自动车牌识别(ALPR)技术来确定车辆牌照数据的处理模块。 处理模块可以进一步检查订单列表以确定牌照数据是否与订单列表上的订单相关联,如果是,则将订单添加到优先级队列。

    Cleaning edge modification for improved cleaning blade life and reliability
    9.
    发明授权
    Cleaning edge modification for improved cleaning blade life and reliability 有权
    清洁边缘修改,以改善清洁刀片寿命和可靠性

    公开(公告)号:US08380116B2

    公开(公告)日:2013-02-19

    申请号:US12840798

    申请日:2010-07-21

    CPC classification number: G03G21/0076 Y10T156/1062

    Abstract: According to aspects of the embodiments, there is provided an apparatus comprising a cleaning unit with a blade holder that rotates about a pivot point, the cleaning blade is coupled to the blade holder and is positioned to chisel excess toner from a photoreceptor surface. Geometrical changes produce a blade having a plurality of slanted surfaces at the working end of the blade one at an obtuse angle, in the range of 93 degrees to 97 degrees, and a second at an acute angle that forms an offset point between the cleaning edge and the intersection of the two angles. A double cut allows for improvement in the cleaning tip stiffness using the first cut, while the second cut increases the contact width and improves the pressure distribution at the working edge.

    Abstract translation: 根据实施例的方面,提供了一种装置,其包括具有围绕枢转点旋转的刀片保持器的清洁单元,清洁刀片联接到刀片保持器并且定位成从感光体表面凿出多余的调色剂。 几何变化产生具有在刀片工作端的多个倾斜表面的刀片,其钝角在93度至97度的范围内,第二级以锐角形成第二倾斜角,其形成清洁边缘 和两个角度的交点。 双切割允许使用第一切口改善清洁尖端刚度,而第二切口增加接触宽度并改善工作边缘处的压力分布。

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