We propose in this work a dynamic speckle descriptor based on a Hurst wavelet estimator. The dynamic speckle or biospeckle is a phenomenon produced by laser illumination of active materials, such as biological tissue or the drying process of paint. Dynamic speckle interferometry is a useful technique for assessing the time evolution of surfaces as also to segment the loci of different activity in living tissues. Considering previous biospeckle characterization based on the autocorrelation function and its relation with the Hurst coefficient, a wavelet-based estimator is proposed as a feature extraction of the dynamic speckle characteristic. Encouraging results of the descriptor performance are obtained via three different experiments: a time history of speckle pattern applied to the drying of painting, segmenting regions in whole field image applied to the viability test of a corn seed and also to the bruising in fruits.
A Comparative Study of Image Retrieval Algorithms for Enhancing a Content-based Image Retrieval System
