Gray scale vision method and system utilizing same

Abstract

A method and system are provided for automatically locating an object at a vision station by performing an edge-detecting algorithm on at least a portion of the gray-scale digitized image of the object. Preferably, the algorithm comprises an implementation of the Hough transform which includes the iterative application of a direction-sensitive, edge-detecting convolution to the digital image. Each convolution is applied with a different convolution mask or filter, each of which is calculated to give maximum response to an edge of the object in a different direction. The method and system have the ability to extract edges from low contrast images. Also, preferably, a systolic array processor applies the convolutions. The implementation of the Hough transform also includes the steps of shifting the resulting edge-enhanced images by certain amounts in the horizontal and vertical directions, summing the shifted images together into an accumulator buffer to obtain an accumulator image and detecting the maximum response in the accumulator image which corresponds to the location of an edge. If the object to be found is permitted to rotate, at least one other feature, such as another edge, must be located in order to specify the location and orientation of the object. The location of the object when correlated with the nominal position of the object at the vision station provides the position and attitude of the object. The resultant data may be subsequently transformed into the coordinate frame of a peripheral device, such as a robot, programmable controller, numerical controlled machine, etc. for subsequent use by a controller of the peripheral device.