A machine vision approach to the grading of crushed aggregate

The grading of crushed aggregate is carried out usually by sieving. We describe a new image-based approach to the automatic grading of such materials. The operational problem addressed is where the camera is located directly over a conveyor belt. Our approach characterizes the information content of each image, taking into account relative variation in the pixel data, and resolution scale. In feature space, we find very good class separation using a multidimensional linear classifier. The innovation in this work includes (i) introducing an effective image-based approach into this application area, and (ii) our supervised classification using wavelet entropy-based features.

Rapid Implementation and Optimisation of DSP Systems on FPGA-Centric Hetrogeneous Platforms

This paper, chosen as a best paper from the 2005 SAMOS Workshop on Computer Systems: describes the for the first time the major Abhainn project for automated system level design of embedded signal processing systems. In particular, this describes four key novelties: novel algorithm modelling techniques for DSP systems, automated implementation realisation, algorithm transformation for system optimisation and automated inter-processor communication. This is applied to two complex systems: a radar and sonar system. In both cases technology which allows non-experts to automatically create low-overhead, high performance embedded signal processing systems is exhibited.