Abstract
We have developed a visual system achieving scale and position invariant object classification. The system includes a silicon retina, a field-programmable gate array (FPGA), and a personal computer (PC). Its algorithm is based on the HMAX model, which is a hierarchical model of object recognition in the visual cortex and offers scale and position invariant recognition. In order to perform a lot of spatial filtering required by the model effectively, we employed a resistive network. The output of the system was examined using visual stimuli displayed on a LCD monitor, and the system was successful in classifying several figures and alphabetical letters independently of scale and position of the target.
