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    • 2. 发明申请
    • Method for Fast, Robust, Multi-Dimensional Pattern Recognition
    • 快速,鲁棒,多维模式识别的方法
    • US20130142421A1
    • 2013-06-06
    • US13656167
    • 2012-10-19
    • William M. SilverE. John McGarrySanjay NichaniAdam Wagman
    • William M. SilverE. John McGarrySanjay NichaniAdam Wagman
    • G06K9/62
    • G06K9/6201G06K9/481G06K9/6204
    • A method and system for probe-based pattern matching including an apparatus for synthetic training of a model of a pattern. The apparatus comprises a sensor for obtaining an image of the pattern and a processor for receiving the image of the pattern from the sensor and running a program. In the steps performed by the program a boundary of the pattern in the image is identified. A plurality of positive probes are placed at selected points along the boundary of the pattern and at least one straight segment of the boundary of the pattern is identified. The at least one straight segment of the boundary is extended to provide an imaginary straight segment and a plurality of negative probes are placed at selected points along the imaginary straight segment, where each negative probe has a negative weight.
    • 一种用于基于探针的模式匹配的方法和系统,包括用于模式模型的合成训练的装置。 该装置包括用于获得图案的图像的传感器和用于从传感器接收图案的图像并运行程序的处理器。 在由程序执行的步骤中,识别图像中的图案的边界。 沿着图案的边界的选定点放置多个正探针,并且识别图案的边界的至少一个直线段。 边界的至少一个直线段被延伸以提供假想的直线段,并且多个负探针被放置在沿着假想直线段的选定点处,其中每个负探头具有负重。
    • 4. 发明授权
    • Method for fast, robust, multi-dimensional pattern recognition
    • 快速,健壮,多维模式识别的方法
    • US08363942B1
    • 2013-01-29
    • US11027962
    • 2004-12-31
    • William M. SilverE. John McGarrySanjay NichaniAdam Wagman
    • William M. SilverE. John McGarrySanjay NichaniAdam Wagman
    • G06K9/18
    • G06K9/6201G06K9/481G06K9/6204
    • Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.
    • 公开了一种用于确定图像中的预定图案的一个或多个实例的不存在或不存在以及用于在多维空间内确定每个找到的实例的位置的方法。 模型代表要发现的模式,该模型包括多个探针。 每个探针表示在给定姿势下在图像中进行测试的相对位置,每个这样的测试提供了该模式存在于姿势的证据。 该方法还包括在多个姿势中的每个姿势下的模型与运行时图像的比较。 在每个姿态计算匹配得分以提供匹配得分表面。 然后,匹配得分与接受阈值进行比较,并用于提供图像中图案的任何实例的位置。
    • 7. 发明授权
    • Fast high-accuracy multi-dimensional pattern inspection
    • 快速高精度多维图案检查
    • US06850646B1
    • 2005-02-01
    • US10705295
    • 2003-11-10
    • William SilverAaron WallackAdam Wagman
    • William SilverAaron WallackAdam Wagman
    • G06T7/00G06K9/48
    • G06K9/6206G06T7/74
    • A method and apparatus are provided for identifying diffe rences between a stored pattern and a matching image subset, where variations in pattern position, orientation, and size do not give rise to false differences. The invention is also a system for analyzing an object image with respect to a model pattern so as to detect flaws in the object image. The system includes extracting pattern features from the model pattern; generating a vector-valued function using the pattern features to provide a pattern field; extracting image features from the object image; evaluating each image feature, using the pattern field and an n-dimensional transformation that associates image features with pattern features, so as to determine at least one associated feature characteristic; and using at least one feature characteristic to identify at least one flaw in the object image. The invention can find at least two distinct kinds of flaws: missing features, and extra features. The invention provides pattern inspection that is faster and more accurate than any known prior art method by using a stored pattern that represents an ideal example of the object to be found and inspected, and that can be translated, rotated, and scaled to arbitrary precision much faster than digital image re-sampling, and without pixel grid quantization errors. Furthermore, since the invention does not use digital image re-sampling, there are no pixel quantization errors to cause false differences between the pattern and image that can limit inspection performance.
    • 提供了一种用于识别存储的图案和匹配图像子集之间的差异的方法和装置,其中图案位置,取向和尺寸的变化不会引起错误的差异。 本发明还是一种用于分析相对于模型图案的对象图像以便检测对象图像中的缺陷的系统。 该系统包括从模型模式中提取模式特征; 使用所述模式特征生成向量值函数以提供模式字段; 从对象图像提取图像特征; 使用所述图案字段和将图像特征与图案特征相关联的n维变换来评估每个图像特征,以便确定至少一个相关联的特征特征; 以及使用至少一个特征特征来识别所述对象图像中的至少一个缺陷。 本发明可以发现至少两种不同种类的缺陷:缺失特征和额外特征。 本发明通过使用表示待发现和检查的对象的理想示例的存储模式,并且可以被转换,旋转和缩放到任意精度而提供比任何已知的现有技术方法更快更准确的模式检查 比数字图像重采样更快,并且没有像素网格量化误差。 此外,由于本发明不使用数字图像重新采样,因此不存在像素量化误差,导致图案和图像之间可能限制检查性能的误差。
    • 8. 发明授权
    • Method and apparatus for training a probe model based machine vision system
    • 用于训练基于探针模型的机器视觉系统的方法和装置
    • US08705851B2
    • 2014-04-22
    • US13733685
    • 2013-01-03
    • Simon BarkerAdam WagmanAaron WallackDavid J Michael
    • Simon BarkerAdam WagmanAaron WallackDavid J Michael
    • G06K9/62
    • G06K9/6256G06K9/3275G06K9/6255G06K9/6857G06T7/74G06T2207/20081G06T2207/30208
    • A method for training a pattern recognition algorithm including the steps of identifying the known location of the pattern that includes repeating elements within a fine resolution image, using the fine resolution image to train a model associated with the fine image, using the model to examine the fine image resolution image to generate a score space, examining the score space to identify a repeating pattern frequency, using a coarse image that is coarser than the finest image resolution image to train a model associated with the coarse image, using the model associated with the coarse image to examine the coarse image thereby generating a location error, comparing the location error to the repeating pattern frequency and determining if the coarse image resolution is suitable for locating the pattern within a fraction of one pitch of the repeating elements.
    • 一种用于训练模式识别算法的方法,包括以下步骤:使用所述模型来识别包含精细分辨率图像内的重复元素的图案的已知位置,使用所述精细分辨率图像来训练与所述精细图像相关联的模型, 精细图像分辨率图像以生成分数空间,使用与最粗图像分辨率图像相比较粗糙的图像来检查分数空间以识别重复图案频率,以使用与该图像相关联的模型来训练与粗图像相关联的模型 粗图像以检查粗图像,从而产生位置误差,将位置误差与重复图案频率进行比较,并确定粗图像分辨率是否适于将图案定位在重复元件的一个间距的几分之一内。
    • 9. 发明申请
    • Method and Apparatus for Training a Probe Model Based Machine Vision System
    • 用于训练基于探针模型的机器视觉系统的方法和装置
    • US20130182948A1
    • 2013-07-18
    • US13733685
    • 2013-01-03
    • Simon A. BarkerAdam WagmanAaron WallackDavid J. Michael
    • Simon A. BarkerAdam WagmanAaron WallackDavid J. Michael
    • G06K9/62
    • G06K9/6256G06K9/3275G06K9/6255G06K9/6857G06T7/74G06T2207/20081G06T2207/30208
    • A method for training a pattern recognition algorithm including the steps of identifying the known location of the pattern that includes repeating elements within a fine resolution image, using the fine resolution image to train a model associated with the fine image, using the model to examine the fine image resolution image to generate a score space, examining the score space to identify a repeating pattern frequency, using a coarse image that is coarser than the finest image resolution image to train a model associated with the coarse image, using the model associated with the coarse image to examine the coarse image thereby generating a location error, comparing the location error to the repeating pattern frequency and determining if the coarse image resolution is suitable for locating the pattern within a fraction of one pitch of the repeating elements.
    • 一种用于训练模式识别算法的方法,包括以下步骤:使用所述模型来识别包含精细分辨率图像内的重复元素的图案的已知位置,使用所述精细分辨率图像来训练与所述精细图像相关联的模型, 精细图像分辨率图像以生成分数空间,使用与最粗图像分辨率图像相比较粗糙的图像来检查分数空间以识别重复图案频率,以使用与该图像相关联的模型来训练与粗图像相关联的模型 粗图像以检查粗图像,从而产生位置误差,将位置误差与重复图案频率进行比较,并确定粗图像分辨率是否适于将图案定位在重复元件的一个间距的几分之一内。