Image object labelling and classification using an associative memory

An essential part of image analysis is the location and identification of objects within the image. Noise and clutter make this identification problematic, and the size of the image may present a computational problem. To overcome these problems, we use a window onto the image to focus onto small areas. Conventionally we still need to know the size of the object we are searching for in order to select a window of the correct size. We describe a method for object location and classification which enables us to use a small window to identify large objects in the image. The window focusses on features in the image, and an associative memory recalls evidence for objects from these features, avoiding the necessity of knowing the dimensions of the objects to be detected.