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    • 1. 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。
    • 3. 发明申请
    • ROBUST CHARACTER SEGMENTATION FOR LICENSE PLATE IMAGES
    • 许可证板图像的强大字符分段
    • US20130294654A1
    • 2013-11-07
    • US13539739
    • 2012-07-02
    • Aaron Michael BurryClaude FillionVladimir Kozitsky
    • Aaron Michael BurryClaude FillionVladimir Kozitsky
    • G06K9/34
    • G06K9/34G06K9/325G06K2209/01G06K2209/15
    • A method and system for achieving accurate segmentation of characters with respect to a license plate image within a tight bounding box image. A vehicle image can be captured by an image capturing unit and processed utilizing an ALPR unit. A vertical projection histogram can be calculated to produce an initial character boundary (cuts) and local statistical information can be employed to split a large cut and insert a missing character. The cut can be classified as a valid and/or a suspect character and the suspect character can be analyzed. The suspect character can be normalized and passed to an OCR module for decoding and generating a confidence quote with every conclusion. The non-character images can be rejected at the OCR level by enforcing a confidence threshold. An adjoining suspect narrow character can be combined and the OCR confidence of the combined character can be assessed.
    • 一种用于在紧密的边界框图像内实现相对于车牌图像的字符的精确分割的方法和系统。 车辆图像可以由图像捕获单元捕获并且利用ALPR单元进行处理。 可以计算垂直投影直方图以产生初始字符边界(切割),并且可以采用局部统计信息来分割大剪切并插入缺失的字符。 切割可以分为有效的和/或可疑的角色,并且可以分析可疑的角色。 可疑人物可以归一化并传递给OCR模块进行解码,并产生每个结论的置信度。 非字符图像可以通过强制置信阈值在OCR级别被拒绝。 可以组合相邻的可疑小角色,可以评估组合角色的OCR置信度。
    • 4. 发明申请
    • ROBUST CROPPING OF LICENSE PLATE IMAGES
    • 许可证板图像的稳健修剪
    • US20130272579A1
    • 2013-10-17
    • US13448976
    • 2012-04-17
    • Aaron Michael BurryClaude FillionVladimir KozitskyRaja BalaZhigang Fan
    • Aaron Michael BurryClaude FillionVladimir KozitskyRaja BalaZhigang Fan
    • G06K9/46G06K9/34G06K9/54
    • G06K9/3258G06K2209/15
    • A method, system, and computer-usable tangible storage device for robustly cropping and accurately recognizing license plates to account for noise sources and interfering artifacts are disclosed. License plate images and sub-images can be tightly cropped utilizing an image-based classifier and gradient-based cropping. An image-based classifier can identify the location of valid characters within the image. Because of a number of noise sources, such as, for example, residual plate rotation and shear in the characters within the image, the image-based classifier performs a “rough” identification of the image boundaries. An additional processing step utilizing gradient-based cropping is performed to fine-tune the license plate image boundaries. Gradient-based cropping eliminates unwanted border artifacts that could substantially impact the segmentation and license plate character recognition results.
    • 公开了一种方法,系统和计算机可用的有形存储设备,用于强力裁剪和准确识别牌照以考虑噪声源和干扰伪像。 可以使用基于图像的分类器和基于梯度的裁剪来严格裁剪牌照图像和子图像。 基于图像的分类器可以识别图像中有效字符的位置。 由于许多噪声源,例如图像中的字符中的残余板旋转和剪切,基于图像的分类器对图像边界执行“粗略”识别。 执行利用基于梯度的裁剪的附加处理步骤来微调车牌图像边界。 基于梯度的裁剪消除了不必要的边界伪影,可能会对分割和车牌字符识别结果产生重大影响。
    • 5. 发明授权
    • Robust character segmentation for license plate images
    • 车牌图像的强大字符分割
    • US08934676B2
    • 2015-01-13
    • US13539739
    • 2012-07-02
    • Aaron Michael BurryClaude FillionVladimir Kozitsky
    • Aaron Michael BurryClaude FillionVladimir Kozitsky
    • G06K9/00G06K9/48G06K9/03G06K7/10
    • G06K9/34G06K9/325G06K2209/01G06K2209/15
    • A method and system for achieving accurate segmentation of characters with respect to a license plate image within a tight bounding box image. A vehicle image can be captured by an image capturing unit and processed utilizing an ALPR unit. A vertical projection histogram can be calculated to produce an initial character boundary (cuts) and local statistical information can be employed to split a large cut and insert a missing character. The cut can be classified as a valid and/or a suspect character and the suspect character can be analyzed. The suspect character can be normalized and passed to an OCR module for decoding and generating a confidence quote with every conclusion. The non-character images can be rejected at the OCR level by enforcing a confidence threshold. An adjoining suspect narrow character can be combined and the OCR confidence of the combined character can be assessed.
    • 一种用于在紧密的边界框图像内实现相对于车牌图像的字符的精确分割的方法和系统。 车辆图像可以由图像捕获单元捕获并且利用ALPR单元进行处理。 可以计算垂直投影直方图以产生初始字符边界(切割),并且可以采用局部统计信息来分割大剪切并插入缺失的字符。 切割可以分为有效的和/或可疑的角色,并且可以分析可疑的角色。 可疑的角色可以被归一化并传递给OCR模块进行解码,并产生每个结论的置信度。 非字符图像可以通过强制置信阈值在OCR级别被拒绝。 可以组合相邻的可疑小角色,可以评估组合角色的OCR置信度。
    • 7. 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。
    • 8. 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。
    • 10. 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。