Lapped Block Image Analysis via the Method of Legendre Moments

Abstract

Research investigating the use of Legendre moments for pattern recognition has been performed in recent years. This field of research remains quite open. This paper proposes a new technique based on block-based reconstruction method (BBRM) using Legendre moments compared with the global reconstruction method (GRM). For alleviating the blocking artifact involved in the processing, we propose a new approach using lapped block-based reconstruction method (LBBRM). For the problem of selecting the optimal number of moment used to represent a given image, we propose the maximum entropy principle (MEP) method. The main motivation of the proposed approaches is to allow fast and efficient reconstruction algorithm, with improvement of the reconstructed images quality. A binary handwritten musical character and multi-gray-level Lena image are used to demonstrate the performance of our algorithm.