Hopfield neural network (hnn) improvement for color image recognition using multi-bitplane and multi-connect architecture

A new approach of using HNN with multi-connect architecture in color image recognition has been produced in this work. HNN consists of a single layer of fully connected processing elements, which is described as an associative memory. However, HNN is useless in dealing with data not in bipolar representation. As such, HNN failed to work directly with color images, unless, another way is produced in order to pave the way for expected right recognition. In RGB bands each represents different values of brightness, still it is possible to assume for 8-bit RGB image consists of 8-layers of binaries, or bipolar. In such way, each layer is as a single binary image for HNN. The results have shown the possibility and usefulness of HNN in RGB image recognition. Besides, the possibility of using wide number of RGB images stored in the net memory without sensed affection on the final results.