Pattern recognition system employing unlike templates to detect objects having distinctive features in a video field

A pattern recognition method for recognizing an object having landmark features as imaged in a video field, said method comprising the steps of:

• (a) correlating a first template having a first pattern similar to one of said landmark features with respect to said video field and generating a first correlation surface to preliminarily identify at least one candidate landmark feature of said object which could be either a correctly identified landmark feature or one of a plurality of falsely identified landmark features;
• (b) correlating a second template having a second pattern with unlike feature correlation with respect to said first template pattern to said candidate landmark feature and generating a second correlation surface to determine if said candidate landmark feature is at least one of said falsely identified landmark features;
• (c) correlating a third template having a third pattern with unlike feature correlation with respect to said first and second template patterns over said candidate landmark feature and generating a third correlation surface in order to determine if said candidate landmark feature is at least another of said falsely identified landmark features;
• (d) repeating steps (b) and (c) above until all possible likely falsely identified landmark features have been eliminated,
• (e) selecting said second pattern, wherein said second pattern includes a first element of said landmark feature which extends substantially completely across said second template,
• wherein said correctly identified landmark feature is accurately identified by process of elimination of said falsely identified landmark features.

A pattern recognition method for recognizing an object having distinctive features as imaged in a video field, said method comprising the steps of:

• (a) passing a first template having a first pattern similar to one of said distinctive features over said video field and comparing the same in order to preliminarily identify at least one possible distinctive feature of said object which could be either a correctly identified distinctive feature or one of a plurality of incorrectly identified features;
• and,
• (b) passing a second template having a second pattern different from said first template pattern over said possible distinctive feature and comparing the same in order to determine if said possible distinctive feature is at least one of said incorrectly identified features,
• wherein said second pattern includes a first element of said distinctive feature which extends substantially completely across said second template.

A pattern recognition method for recognizing an object having landmark features as imaged in a video field, said method comprising the steps of:

• (a) correlating a first template having a first pattern similar to one of said landmark features with respect to said video field and generating a first correlation surface to preliminarily identify at least one candidate landmark feature of said object which could be either a correctly identified landmark feature or one of a plurality of falsely identified landmark features;
• and,
• (b) correlating a second template having a second pattern with unlike feature correlation with respect to said first template pattern to said candidate landmark feature and generating a second correlation surface to determine if said candidate landmark feature is at least one of said falsely identified landmark features,
• wherein said second pattern includes a first element of said landmark feature which extends substantially completely across said second template.

A system for recognizing an object having landmark features as imaged in a video field, said system comprising:

• scanning means for scanning said object and forming a series of video fields;
• and,
• correlating means for correlating a first template having a first pattern similar to one of said landmark features with respect to said video field and generating a first correlation surface to preliminarily identify at least one candidate landmark feature of said object which could be either a correctly identified landmark feature or one of a plurality of falsely identified landmark features and for correlating a second template having a second pattern with unlike feature correlation with respect to said first template pattern to said candidate landmark feature and generating a second correlation surface to determine if said candidate landmark feature is at least one of said falsely identified landmark features,
• wherein said second pattern includes a first element of said landmark feature which extends substantially completely across said second template and wherein said correctly identified landmark feature is identified by process of eliminating possible falsely identified landmark features.

A pattern recognition method for recognizing an object having distinctive features as imaged in a video field, said method comprising the steps of:

• (a) passing a first template having a first pattern similar to one of said distinctive features over said video field and comparing the same in order to preliminarily identify at least one possible distinctive feature of said object which could be either a correctly identified distinctive feature or one of a plurality of incorrectly identified features;
• (b) passing a second template having a second pattern different from said first template pattern over said possible distinctive feature and comparing the same in order to determine if said possible distinctive feature is at least one of said incorrectly identified features;
• (c) passing a third template having a third pattern different from said first and second template patterns over said possible distinctive features and comparing the same in order to determine if said possible distinctive feature is at least another of said incorrectly identified features,
• wherein at least two templates are employed and a distinctive feature is determined to exist when the following total function T is maximized:
• T=.SIGMA[SIGMA.P.alpha..sub.i (m,n).+-..SIGMA.P.alpha..sub.i (m+v,n+h)]=maximum
• where T=Total or Sum of function
• P=a given line
• .alpha..sub.i =angle of a given line P to abscissa
• i=2 or more
• m=location of at least a first search template on the vertical, i.e., ordinate, axis
• n=location of at least a first search template on the horizontal, i.e., abscissa, axis.
• v=vertical offset of at least a second search template from point m
• h=horizontal offset of at least a second search template from point n.

A pattern recognition method for recognizing an object having landmark features as imaged in a video field, said method comprising the steps of:

• (a) correlating a first template having a first pattern similar to one of said landmark features with respect to said video field and generating a first correlation surface to preliminarily identify at least one candidate landmark feature of said object which could be either a correctly identified landmark feature or one of a plurality of falsely identified landmark features;
• (b) correlating a second template having a second pattern with unlike feature correlation with respect to said first pattern to said candidate landmark feature and generating a second correlation surface to determine if said landmark feature is at least one of said falsely identified landmark features;
• (c) correlating a third template having a third pattern with unlike feature correlation with respect to said first and second template patterns over said candidate landmark feature and generating a third correlation surface in order to determine if said candidate landmark feature is at least another of said falsely identified landmark features,
• wherein at least two correlation surfaces are generated and a landmark feature is determine to exist when the following total function is maximized:
• T=.SIGMA[SIGMA.P.alpha..sub.i (m,n).+-..SIGMA.P.alpha..sub.i (m-v,n+h)]=maximum
• where T=Total or Sum of function
• P=a given line
• .alpha..sub.i =angle of a given line P to abscissa
• i=2 or more
• m=location of at least a first search template on the vertical, i.e., ordinate, axis
• n=location of at least a first search template on the horizontal, i.e., abscissa, axis.
• v=vertical offset of at least a second search template from point m
• h=horizontal offset of at least a second search template from point n.

A pattern recognition method for recognizing an object having landmark features as imaged in a video field, said method comprising the steps of:

• (a) correlating a first template having a first pattern similar to one of said landmark features with respect to a video field and generating a first correlation surface to preliminarily identify at least one candidate landmark feature of said object which could be either a correctly identified landmark feature or one of a plurality of falsely identified landmark features;
• and,
• (b) correlating a second template having a second pattern with unlike feature correlation with respect to said first template pattern to said candidate landmark feature and generating a second correlation surface to determine if said candidate landmark feature is at least one of said falsely identified landmark features,
• wherein said second pattern does not match any landmark feature sought to be recognized and includes at least one extended element different from said first pattern in order to more rapidly distinguish said landmark features.

A system for recognizing an object having landmark features as imaged in a video field, said system comprising:

• scanning means for scanning said object and forming a series of video fields;
• and,
• correlating means for correlating a first template having a first pattern similar to one of said landmark features with respect to said video field and generating a first correlation surface to preliminarily identify at least one candidate landmark feature of said object which could be either a correctly identified landmark feature or one of a plurality of falsely identified landmark features and for correlating a second template having a second pattern with unlike feature correlation with respect to said first template pattern to said candidate landmark feature and generating a second correlation surface to determine if said candidate landmark feature is at least one of said falsely identified landmark features,
• wherein said second pattern does not match any landmark feature sought to be recognized and includes at least one extended element different from said first pattern in order to more rapidly distinguish said landmark features.