公开(公告)号：US08705851B2

公开(公告)日：2014-04-22

申请号：US13733685

申请日：2013-01-03

申请人： Simon Barker ,  Adam Wagman ,  Aaron Wallack ,  David J Michael

发明人： Simon Barker ,  Adam Wagman ,  Aaron Wallack ,  David J Michael

IPC分类号： G06K9/62

CPC分类号： G06K9/6256 ,  G06K9/3275 ,  G06K9/6255 ,  G06K9/6857 ,  G06T7/74 ,  G06T2207/20081 ,  G06T2207/30208

摘要： 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.

摘要翻译： 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。

公开(公告)号：US08457390B1

公开(公告)日：2013-06-04

申请号：US12249318

申请日：2008-10-10

申请人： Simon Barker ,  Adam Wagman ,  Aaron Wallack ,  David J. Michael

发明人： Simon Barker ,  Adam Wagman ,  Aaron Wallack ,  David J. Michael

IPC分类号： G06K9/62

CPC分类号： G06K9/6256 ,  G06K9/3275 ,  G06K9/6255 ,  G06K9/6857 ,  G06T7/74 ,  G06T2207/20081 ,  G06T2207/30208

摘要： A method for training a pattern recognition algorithm for a machine vision system that uses models of a pattern to be located, the method comprising the steps of training each of a plurality of models using a different training image wherein each of the training images is a version of a single image of the pattern at a unique coarse image resolution, using the models to identify at least one robust image resolution where the image resolution is suitable for locating the pattern within an accuracy limit of the actual location of the pattern in the image and storing the at least one robust image resolution for use in subsequent pattern recognition processes.

摘要翻译： 一种训练用于使用要定位的模式的模型的机器视觉系统的模式识别算法的方法，所述方法包括以下步骤：使用不同的训练图像训练多个模型中的每一个，其中每个训练图像是版本 使用这些模型来识别至少一个鲁棒的图像分辨率，其中图像分辨率适合于将图案定位在图像的图案的实际位置的精度极限内，以及 存储用于后续模式识别过程的至少一个鲁棒图像分辨率。

公开(公告)号：US20130182948A1

公开(公告)日：2013-07-18

申请号：US13733685

申请日：2013-01-03

申请人： Simon A. Barker ,  Adam Wagman ,  Aaron Wallack ,  David J. Michael

发明人： Simon A. Barker ,  Adam Wagman ,  Aaron Wallack ,  David J. Michael

IPC分类号： G06K9/62

CPC分类号： G06K9/6256 ,  G06K9/3275 ,  G06K9/6255 ,  G06K9/6857 ,  G06T7/74 ,  G06T2207/20081 ,  G06T2207/30208

摘要： 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.

摘要翻译： 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。

公开(公告)号：US06993192B1

公开(公告)日：2006-01-31

申请号：US10705288

申请日：2003-11-10

申请人： William Silver ,  Aaron Wallack ,  Adam Wagman

发明人： William Silver ,  Aaron Wallack ,  Adam Wagman

IPC分类号： G06K9/62

CPC分类号： G06K9/32 ,  G06K9/6203 ,  G06T7/75

摘要： A method and apparatus are provided for identifying differences 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.

公开(公告)号：US06856698B1

公开(公告)日：2005-02-15

申请号：US10273855

申请日：2002-10-18

申请人： William Silver ,  Aaron Wallack ,  Adam Wagman

发明人： William Silver ,  Aaron Wallack ,  Adam Wagman

IPC分类号： G06K9/48 ,  G06K9/62 ,  G06K9/64

CPC分类号： G06K9/6204

摘要： A method and apparatus are provided for rapidly refining a given approximate location of a pattern to produce a more accurate location. The invention employs a multi-dimensional space that includes translation, orientation, and scale. The invention can serve as a replacement for the fine resolution phase of any coarse-fine system for pattern location. Patterns and images are represented by a feature-based description that can be translated, rotated, and scaled to arbitrary precision much faster than digital image re-sampling, and without pixel grid quantization errors. Thus, accuracy is not limited by the ability of a grid to represent small changes in position, orientation, or size (or other degrees of freedom). The invention determines an accurate object pose from an approximate starting pose in a small, fixed number of increments that is independent of the number of dimensions of the space, and independent of the distance between the starting and final poses, provided that the starting pose is within the “capture range” of the true pose. Thus, accuracy need not be sacrificed to keep execution time acceptable for practical applications. Specifying locations in four or more dimensions will often result in better matches between the pattern and image than two-dimensional location systems, thereby improving accuracy. Accuracy is not degraded if some portion of the object is missing or occluded, or if unexpected extra features are present.

摘要翻译： 提供了一种方法和装置，用于快速地精化图案的给定的近似位置以产生更准确的位置。 本发明采用包括平移，取向和尺度的多维空间。 本发明可以作为用于图案定位的任何粗细系统的精细分辨率相位的替代。 模式和图像由基于特征的描述表示，其可以比数字图像重新采样更快地转换，旋转和缩放到任意精度，并且没有像素网格量化误差。 因此，精度不受网格表示位置，方向或大小（或其他自由度）的小变化的能力的限制。 本发明根据独立于空间的数量的小的固定数量的增量来确定来自近似起始姿态的准确的物体姿态，并且独立于起始和最终姿态之间的距离，只要起始姿势为 在“拍摄范围”内的真实姿势。 因此，不需要牺牲精度来保持实际应用可接受的执行时间。 在四维或更多维度上指定位置通常会导致图形和图像之间比二维位置系统更好的匹配，从而提高准确性。 如果对象的某些部分丢失或遮挡，或者如果出现意外的额外特征，则精度不会降低。

公开(公告)号：US06850646B1

公开(公告)日：2005-02-01

申请号：US10705295

申请日：2003-11-10

申请人： William Silver ,  Aaron Wallack ,  Adam Wagman

发明人： William Silver ,  Aaron Wallack ,  Adam Wagman

IPC分类号： G06T7/00 ,  G06K9/48

CPC分类号： G06K9/6206 ,  G06T7/74

摘要： 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.

摘要翻译： 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。

公开(公告)号：US07164796B1

公开(公告)日：2007-01-16

申请号：US10705287

申请日：2003-11-11

申请人： William Silver ,  Aaron Wallack ,  Adam Wagman

发明人： William Silver ,  Aaron Wallack ,  Adam Wagman

IPC分类号： G06K9/62

CPC分类号： G06K9/32 ,  G06K9/6203 ,  G06T7/75

摘要： A method and apparatus are provided for identifying differences 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.

摘要翻译： 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。

公开(公告)号：US07043081B1

公开(公告)日：2006-05-09

申请号：US10705296

申请日：2003-11-10

申请人： William Silver ,  Aaron Wallack ,  Adam Wagman

发明人： William Silver ,  Aaron Wallack ,  Adam Wagman

IPC分类号： G06K9/62

CPC分类号： G06K9/32 ,  G06K9/6203 ,  G06T7/75

摘要： A method and apparatus are provided for identifying differences 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.

公开(公告)号：US07006712B1

公开(公告)日：2006-02-28

申请号：US10705298

申请日：2003-11-10

申请人： William Silver ,  Aaron Wallack ,  Adam Wagman

发明人： William Silver ,  Aaron Wallack ,  Adam Wagman

IPC分类号： G06K9/32

CPC分类号： G06K9/32 ,  G06K9/6203 ,  G06T7/75

摘要： A method and apparatus are provided for identifying differences 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.

公开(公告)号：US06985625B1

公开(公告)日：2006-01-10

申请号：US10705564

申请日：2003-11-10

申请人： William Silver ,  Aaron Wallack ,  Adam Wagman

发明人： William Silver ,  Aaron Wallack ,  Adam Wagman

IPC分类号： G06K9/46 ,  G06K9/66

CPC分类号： G06K9/32 ,  G06K9/6203 ,  G06T7/75

摘要： A method and apparatus are provided for identifying differences 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.