Robust 2D Fisher Barycenter Contour

In this paper, the algorithm for 2D shape matching and retrieval is developed by using Fisher Barycenter Contour (FBcC). First, the shape is represented into 3D format using the signed enclosed area at each scale level of Barycenter Contour (BcC). Because of high dimension of the feature representation, the eigen Barycenter Contour (EBcC) is applied for dimensionality reduction. Then, the Fisher Barycenter Contour (FBcC) is used for making discrimination. Finally, the similarity is measured using the normalized cross correlation. The experimentation is tested on MPEG-7 contour shape database CE-1 part B of 1400 image shapes. The experimental results illustrate that our approach gives very high retrieval efficiency (or Bulls-eye test) of 89.60% and 98.62% using two parameters, shape signature and its power spectrum respectively, when comparing with all the existing methods.