FPGA-based colour image classification for mobile robot navigation

This paper presents a real-time colour image classification algorithm for mobile robot navigation based on the advanced technology of field programmable gate arrays (FPGA). In order to calibrate the object colour in different lighting conditions, a kind of statistic ellipsoidal model is adopted. We build a 3-D colour look-up table (CLUT) in which only 18 bits are used to represent a kind of colour instead of conventional 24 bits. This method resolves the problem of object overlapping in a colour space, and has the merits of higher classification accuracy and lower memory cost than traditional ones. It is implemented on FPGA, which can highly reduce the CPU computation burden and remarkably improve the performance of robot vision systems. This method is validated by the applications on a mobile robot in the research.