Shape object classification using echoes inside a virtual environment application

This work investigates the geometric object-shape classification using the echoes generated by various kinds of obstacles in a cellular automata based virtual environment for ultra-sound propagation. The virtual environment is implemented as a JAVA platform [1] capable of emulate sound propagation in a controlled 2D environment. The echoes are preprocessed by a Feature Processor Vector Unit (FVPU) and then classified using 2 neural networks: Fast Support Vector Classifier (FSVC) and Extreme Learning Machine (ELM).