Abstract: Methods and systems for monitoring the delivery of workpieces to a position by: storing a digital reference image of the position prior to the delivery of workpieces; storing a digital operating image of the position during delivery of workpieces; performing image arithmetic on the reference image and the operating image to produce a digital evaluation image comprised of a plurality of pixels establishing a threshold image condition for the evaluation image that correlates to the existence of an operating condition relevant to the control of the delivery of workpieces; and examining the pixels in the evaluation image to determine whether the threshold image condition is met.

Abstract: Methods and systems for monitoring the delivery of workpieces to a position by: storing a digital reference image of the position prior to the delivery of workpieces; storing a digital operating image of the position during delivery of workpieces; performing image arithmetic on the reference image and the operating image to produce a digital evaluation image comprised of a plurality of pixels; establishing a threshold image condition for the evaluation image that correlates to the existence of an operating condition relevant to the control of the delivery of workpieces; and examining the pixels in the evaluation image to determine whether the threshold image condition is met.

Abstract: Methods and systems for monitoring the delivery of workpieces to a position by: storing a digital reference image of the position prior to the delivery of workpieces; storing a digital operating image of the position during delivery of workpieces; performing image arithmetic on the reference image and the operating image to produce a digital evaluation image comprised of a plurality of pixels; establishing a threshold image condition for the evaluation image that correlates to the existence of an operating condition relevant to the control of the delivery of workpieces; and examining the pixels in the evaluation image to determine whether the threshold image condition is met.

Abstract: 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.