Coded hierarchical dictionary strategy for face recognition efficiency

Face recognition is the most studied topic in the pattern recognition research field. This is probably due to the multiple useful applications which can be developed for important domains. Such deployed research efforts produced a huge number of methods, techniques and algorithms with different characteristics according to their simplicity, efficiency, robustness and speed. Present work investigates the performances of a simplified technique using a hierarchical classification scheme based on a constructed multi parts dictionary. The elementary features of the constructed dictionary were obtained using the well-known cross-correlation operator applied to the original images and their transformed images known as integral images and Discrete Cosine Transform. Hierarchical classification scheme is used to overcome the fact that this operator has high consumption time cost. The proposed strategy was implemented and tested on the images of the well known ORL and YALE database sets. Practical results demonstrate largely recognizable efficiency and speed characteristics.