Object recognition on general purposed Conic Section Function Neural Network integrated circuit

Automatic recognition using a database obtained from existing objects is getting more importance for industrial and security applications. In this work, the database is collected from the images of various objects that are rotated at different angles have been tested on a general purposed conic section function neural network (CSFNN) integrated circuit. Both hardware results of the integrated circuit and the software results of CSFNN have been compared and applicability of the designed integrated circuit to the object recognition problem has been demonstrated.