Highly constrained tomography for automated inspection of area arrays
First Claim
1. A method for automated industrial inspection of manufactured devices characterized by a repetitive array of similar objects, comprising:
- obtaining a set of observed projections of one or more objects under inspection that are members of said repetitive array;
obtaining a highly constrained model of said objects under inspection based partially on or expressing some prior information about said objects under inspection;
obtaining a distribution or density expressing prior probabilities, p(M), for all possible instances of said objects under inspection representable by said highly constrained model;
obtaining a forward map capable of predicting the likelihood of observing specified projections that would result from any collection of objects representable by said highly constrained model;
estimating a model of said objects under inspection based on said set of observed projections, said highly constrained model, said distribution or density expressing prior probabilities, and said forward map.
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Abstract
A tomographic reconstruction method and system incorporating Bayesian estimation techniques to inspect and classify regions of imaged objects, especially objects of the type typically found in linear, areal, or 3-dimensional arrays. The method and system requires a highly constrained model M that incorporates prior information about the object or objects to be imaged, a set of prior probabilities P(M) of possible instances of the object; a forward map that calculates the probability density P(D|M), and a set of projections D of the object. Using Bayesian estimation, the posterior probability p(M|D) is calculated and an estimated model MEST of the imaged object is generated. Classification of the imaged object into one of a plurality of classifications may be performed based on the estimated model MEST, the posterior probability p(M|D) or MAP function, or calculated expectation values of features of interest of the object.
45 Citations
58 Claims
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1. A method for automated industrial inspection of manufactured devices characterized by a repetitive array of similar objects, comprising:
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obtaining a set of observed projections of one or more objects under inspection that are members of said repetitive array; obtaining a highly constrained model of said objects under inspection based partially on or expressing some prior information about said objects under inspection; obtaining a distribution or density expressing prior probabilities, p(M), for all possible instances of said objects under inspection representable by said highly constrained model; obtaining a forward map capable of predicting the likelihood of observing specified projections that would result from any collection of objects representable by said highly constrained model; estimating a model of said objects under inspection based on said set of observed projections, said highly constrained model, said distribution or density expressing prior probabilities, and said forward map. - 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 computer readable storage medium tangibly embodying program instructions implementing a method for automated industrial inspection of manufactured devices characterized by a repetitive array of similar objects, the method comprising the steps of:
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obtaining a set of observed projections of one or more objects under inspection that are members of said repetitive array; obtaining a highly constrained model of said objects under inspection based partially on or expressing some prior information about said objects under inspection; obtaining a distribution or density expressing prior probabilities, p(M), for all possible instances of said objects under inspection representable by said highly constrained model; obtaining a forward map capable of predicting the likelihood of observing specified projections that would result from any collection of objects representable by said highly constrained mode; estimating a model of said objects under inspection based on said set of observed projections, said highly constrained model, said distribution or density expressing prior probabilities, and said forward map. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32)
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33. An automated imaging inspection system for automated industrial inspection of manufactured devices characterized by a repetitive array of similar objects, said system comprising:
a reconstruction engine responsive to receiving a set of observed projections of one or more objects under inspection that are members of said repetitive array by estimating a model of said objects under inspection based on said set of observed projections, a highly constrained model of said objects under inspection based partially on or expressing some prior information about said objects under inspection, a prior probability distribution or density expressing prior probabilities for all possible instances of said object representable by said highly constrained model, and a forward map capable of predicting the likelihood of observing specified projections that would result from any collection of objects representable by said highly constrained model. - View Dependent Claims (34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50)
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51. An automated imaging inspection system for automated industrial inspection of electrical connections arranged in a repetitive array in an electronic assembly, said system comprising:
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a reconstruction engine which receives a set of observed projections of one or more electrical connections under inspection in a repetitive array of an electronic assembly under inspection, said reconstruction engine comprising; a reconstruction algorithm which receives said set of observed projections and estimates one or more of; a maximum a posteriori (MAP) estimate of said one or more electrical connections under inspection; a posterior probability density or distribution of said one or more electrical connections under inspection; one or more expectations of one or more features comprising said highly constrained model or functions thereof; wherein said reconstruction algorithm utilizes; a highly constrained model of said one or more electrical connections under inspection based partially on or expressing some prior information about said one or more electrical connections; a prior probability distribution or density expressing prior probabilities for all possible instances of said one or more electrical connections under inspection representable by said highly constrained model; and a forward map capable of predicting the likelihood of observing said set of observed projections that would result from any collection of said one or more electrical connections representable by said highly constrained model. - View Dependent Claims (52, 53, 54, 55, 56, 57, 58)
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Specification