Invariant Object Recognition Using a Distributed Associative Memory

Invariant Object Recognition Using a Distributed Associative Memory Harry Wechsler and George Lee Zimmerman Department or Electrical Engineering University or Minnesota Minneapolis, MN 55455 Abstract This paper describes an approach to 2-dimensional object recognition. Complex-log conformal mappingis combined with a distributed associative memory to create a system which recognizes objects regardless of changes in rotation or scale. Recalled information from the memorized database is used to classify an object, reconstruct the memorized version ofthe object, and estimate the magnitude of changes in scale or rotation. The system response is resistant to moderate amounts of noise and occlusion. Several experiments, using real,gray scale images, are presented to show the feasibility of our approach. Introduction The challenge of the visual recognition problem stems from the fact that the projection of an object onto an image can be confounded by several dimensions of variability such as uncertain perspective, changing orientation and scale, sensor noise, occlusion, and nonuniform illumination.