Image Retrieval Measures Based on Illumination Invariant Textural MRF Features

Content-based image retrieval (CBIR) systems, target database images using feature similarities with respect to the query. We introduce fast and robust image retrieval measures that utilise novel illumination invariant features extracted from three different Markov random field (MRF) based texture representations. These measures allow retrieving images with similar scenes comprising colour-textured objects viewed with different illumination brightness or spectrum. The proposed illumination insensitive measures are compared favourably with the most frequently used features like the Local Binary Patterns, steerable pyramid and Gabor textural features, respectively. The superiority of these new illumination invariant measures and their robustness to added noise are empirically demonstrated in the illumination invariant recognition of textures from the Outex database.

Diagnostic Enhancement of Screening Mammograms by Means of Local Texture Models

   Jiří Grim    Petr Somol    Michal Haindl    Jan Daneš

Statistically based preprocessing of screening mammograms is proposed with the aim to in-crease the diagnostic conspicuity of mammographic lesions. We estimate first the local statis-tical texture model of a single mammogram as a joint probability density of grey levels in a suitably chosen search window. The probability density in the form of multivariate Gaussian mixture is estimated from data obtained by pixel-wise scanning the mammogram with the search window. In the second phase we evaluate the estimated density at each position of the window and display the corresponding log-likelihood value as grey level at window center. Light grey levels correspond to the typical parts of the image and the dark values reflect unusual places. The resulting log-likelihood image closely correlates with fine structural details of the original mammogram and facilitates diagnostic interpretation of suspect abnormalities.

3D Model of Dragon

The 3D model of a dragon measured using laser range scanner.