Fast high-accuracy multi-dimensional pattern inspection
First Claim
1. A geometric pattern matching apparatus for refining the pose of an object in a run-time image, the object having an expected shape and a true pose in the run-time image, the apparatus comprising:
- a training module configured to receive a training image, and to provide a stored model pattern, the stored model pattern including a geometric description of the expected shape of the object, the geometric description including a plurality of pattern boundary points; and
a run-time module configured to;
receive the stored model pattern, a starting pose, and the run-time image, the starting pose representing an initial estimate of the true pose of the object in the run-time image;
detect in the run-time image a plurality of image boundary points; and
provide, using the stored model pattern, the starting pose, and the plurality of image boundary points;
a refined pose, the refined pose representing a refined estimate of the true pose of the object in the run-time image;
an error value;
an aggregate clutter value; and
an aggregate coverage value.
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Abstract
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.
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Citations
34 Claims
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1. A geometric pattern matching apparatus for refining the pose of an object in a run-time image, the object having an expected shape and a true pose in the run-time image, the apparatus comprising:
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a training module configured to receive a training image, and to provide a stored model pattern, the stored model pattern including a geometric description of the expected shape of the object, the geometric description including a plurality of pattern boundary points; and a run-time module configured to; receive the stored model pattern, a starting pose, and the run-time image, the starting pose representing an initial estimate of the true pose of the object in the run-time image; detect in the run-time image a plurality of image boundary points; and provide, using the stored model pattern, the starting pose, and the plurality of image boundary points; a refined pose, the refined pose representing a refined estimate of the true pose of the object in the run-time image; an error value; an aggregate clutter value; and an aggregate coverage value. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
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18. A geometric pattern matching method for refining the pose of an object in a run-time image, the object having an expected shape and a true pose in the run-time image, the method comprising:
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receiving a training image; receiving a starting pose, the starting pose representing an initial estimate of the true pose of the object in the run-time image; receiving a run-time image; using the training image to provide a stored model pattern, the stored model pattern including a geometric description of the expected shape of the object, the geometric description including a plurality of pattern boundary points; using the stored model pattern, the starting pose, and the run-time image to detect in the run-time image a plurality of image boundary points; and using the stored model pattern, the starting pose, and the plurality of image boundary points to provide; a refined pose, the refined pose representing a refined estimate of the true pose of the object in the run-time image; an error value; an aggregate clutter value; and an aggregate coverage value. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34)
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Specification