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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
