Image Analysis with Legendre Moment Descriptors

Corresponding Author: Simon Liao The University of Winnipeg, Winnipeg, Manitoba, Canada, R3B 2E9, Canada Email: [email protected] Abstract: In this research, a numerical integration method is proposed to improve the computational accuracy of Legendre moments. To clarify the improved computation scheme, image reconstructions from higher order of Legendre moments, up to 240, are conducted. With the more accurately generated moments, the distributions of image information in a finite set of Legendre moments are investigated. We have concluded that each individual finite set of Legendre moments will represent the unique image features independently, while the even orders of Legendre moments describe most of the image characteristics.