Optimised template matching techniques in parallel environment with exhaustive search and swarm intelligence

摘要

Template Matching (TM) techniques are widely used for recognition and location of objects in image and signal processing applications. The existing techniques such as cross, zero and normalised cross-correlations for TM are time consuming. This paper proposes parallel algorithms for TM problems using Normalised Cross Correlation and Particle Swarm Optimisation (PSO) to suit real-time applications. Experimental results show that parallel version of PSO is comparatively efficient.