Image recognition method using two-dimensional stochastic grammars
First Claim
1. A method of identifying bitmapped objects of an image comprising the steps of:
- comparing the templates in an object template library with all areas of like size of the image,generating a set of signals for each such comparison that satisfies a defined matching criteria between the template and the image area being compared, said set of signals identifying the object based on the matching template, the location of the object in the image and an indication of the goodness of the match between the object and the template,forming a series of possible parse trees of the image with a probability of occurrence for each tree, wherein each parent node and its child nodes of each parse tree satisfies a grammatical production rule, in which certain ones of the production rules define spatial relationships between objects in the image, andselecting one of the possible parse trees having the largest probability of occurrence for further utilization.
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Abstract
A method of automatically identifying bitmapped image objects. Each of a set of templates in an object template library is compared with all areas of like size of a bitmapped image. A set of signals is generated for each such comparison that satisfies a defined matching criteria between the template and the image area being compared. The set of signals identifies the object based on the matching template, the location of the object in the image and an indication of the goodness of the match between the object and the template. A series of possible parse trees are formed that describe the image with a probability of occurrence for each tree. Each parent node and its child nodes of each parse tree satisfies a grammatical production rule in which some of the production rules define spatial relationships between objects in the image. The one of the possible parse trees which has the largest probability of occurence is selected for further utilization.
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Citations
7 Claims
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1. A method of identifying bitmapped objects of an image comprising the steps of:
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comparing the templates in an object template library with all areas of like size of the image, generating a set of signals for each such comparison that satisfies a defined matching criteria between the template and the image area being compared, said set of signals identifying the object based on the matching template, the location of the object in the image and an indication of the goodness of the match between the object and the template, forming a series of possible parse trees of the image with a probability of occurrence for each tree, wherein each parent node and its child nodes of each parse tree satisfies a grammatical production rule, in which certain ones of the production rules define spatial relationships between objects in the image, and selecting one of the possible parse trees having the largest probability of occurrence for further utilization. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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6. The method of claim 1 further comprising the step of reestimating the probabilities associated with each production rule from the set of possible parse trees.
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7. The method of claim 1 further comprising the step of reestimating the probability of a pixel error.
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Specification