LAUSR

Video processing including registration has a significant role in surveillance and real-time applications. Image registration is considered a compulsory step in video registration for numerous aspects. One of the major challenges in image registration is to determine the optimal parameters during the registration process. Bio-inspired computational including natural and artificial cognitive systems can be employed to define the optimal solutions. The present work proposed a comprehensive automatic non-rigid video set registration algorithm using Demons algorithm. For optimal velocity smoothing kernels, the demons registration is optimized using cuckoo search (CS) algorithm, where there are no previous studies that have optimized demons algorithm using CS algorithm. A comparison between the CS algorithm and the particle swarm optimization (PSO)-based demons registration is conducted to evaluate the proposed system performance. Thus, the correlation coefficient is taken as a fitness function. The obtained results using CS show a minor increment of the optimized fitness value compared to PSO-based framework value. The proposed CS-based approach reports faster convergence rate than the PSO-based approach.