초록 ▼

A novel method for locating eye point features on patterns or objects whose size varies between the reference object and the find object includes generating a set of reference vectors that define the location of the reference eye point. The set of vectors is modified and separated equidistant from e

A novel method for locating eye point features on patterns or objects whose size varies between the reference object and the find object includes generating a set of reference vectors that define the location of the reference eye point. The set of vectors is modified and separated equidistant from each other. A centroid of the object area is calculated. When a fixed object is to be located, an area of certainty is established which contains a plurality of candidate eye points one of which is the proper find eye point of the object to be located. Sets of find vectors are generated for each candidate eye point which are compared with the set vectors for the reference eye point. Centroids of the find objects having the best comparison are calculated and compared with the centroid of the reference object. The candidate eye point having a best vector correlation match and the best centroid comparison is selected as the eye point of the find object.

대표청구항 ▼

A method for locating eye points on lead frame like objects that are subject to size variations, comprising the steps of: acquiring a video camera image of a reference object having a known position in a PRS system, isolating a teach window area in the camera image field which contains a reference o

A method for locating eye points on lead frame like objects that are subject to size variations, comprising the steps of: acquiring a video camera image of a reference object having a known position in a PRS system, isolating a teach window area in the camera image field which contains a reference object or eye point, generating an edge image of interconnected pixel lines at high contrast edge portions of said reference object, said pixel lines being selected to define unique object shape and eye point, generating a teach eye point in said teach window whose taught location is arbitrarily defined as the center of the teach window, generating a large number of teach vectors between said teach eye point and said edge image of said interconnecting pixel lines, reducing the large number of teach vectors by eliminating some of the large number of vectors to provide a reduced set of teach vectors having a common tail at said teach eye point and heads which are spaced uniformly along said interconnected pixel lines of said unique object shape, storing said teach eye point and said set of teach vectors which define the location of the teach object shape relative to the video camera, acquiring a video camera image of a find object to be located relative to said video camera, generating interconnected pixel lines at high contrast edge portions of said find object, generating sets of find vectors from vector candidate eye points in said image of said find object, comparing said stored teach vectors with said sets of find vectors, scoring the find vectors that compare best with said teach vectors, selecting only the candidate eye points having the highest scores, comparing the selected candidate eye points with the teach eye point, and selecting the one candidate eye point which is closest to the teach eye point as the accurate X-Y position eye point of the find object. *** BRS DOCUMENT BOUNDARY ***