Design of a classification system for rectangular shapes using a co-design environment

Pattern localization and classification are CPU time intensive, being normally implemented in software. Custom implementations in hardware allow real-time processing. In practice, in ASIC or FPGA implementations, the digitization process introduces errors that should be taken into account. This paper presents initially the state-of-the-art in this field, analyzing the performance and implementation of each work. After we propose a system for rectangular shapes localization and classification using reconfigurable devices (FPGA) and a signal processor (DSP) available in a flexible codesign platform. The system will be described using C and VHDL languages, for the software and hardware parts respectively. Finally, the classification block of the system, implemented as an artificial neural network (ANN) in a rapid prototyping platform, is described.