Retrieval of textured images through the use of quantization and modal analysis

This paper proposes a new method for textured image retrieval, by the modal analysis of quantized spectral point patterns as the modal correspondence method of Shapiro and Brady, to match point sets by comparing the eigenvectors of a pairwise point proximity matrix taken from the power spectrum peaks. A variant of the Carcassoni, Ribeiro and Hancock method for performing recognition is taken into account. For choosing image features to represent an image, a quantization scheme is applied. This quantization scheme acts in the spectral space given by the Fourier transform of each image. Its goal is to find a small set which represents an image efficiently, where the most important features are presented. The proposed technique is invariant to rotation and is robust in the presence of noise and damaged images. The techniques here presented are compared, and the commonly used retrieval performance measurement—precision and recall—is used as evaluation of the query results.