Water-filling: a novel way for image structural feature extraction

Abstract

The performance of a content based image retrieval (CBIR) system is inherently constrained by the features adopted to represent the images in the database. In this paper, a new approach is proposed for image feature extraction based on edge maps. The feature vector with multiple feature components is computed through a “water-filling algorithm” applied on the edge map of the original image. The idea of this algorithm is to obtain measures of the edge length and complexity by graph traverse. The new feature is move generally applicable than texture or shape features. We call this structure feature. Experiments show that the new feature is capable of catching salient edge/structure information in the images. An experimental retrieval system utilizing the proposed new features yields better results in retrieving city/building images than some global texture features (wavelet moments). The new feature is ideal for images with clear edge structure. After combining the new features with other features in a relevance feedback framework, satisfactory retrieval results are observed.