This article 3 presents a new adaptive texture model. Locally parallel oscillating patterns are modeled with a weighted Hilbert space defined over local Fourier coefficients. The weights on the local Fourier atoms are optimized to match the local orientation and frequency of the texture. We propose an adaptive method to decompose an image into a cartoon layer and a locally parallel texture laye...

New advances in image based texture synthesis techniques allow the generation of arbitrarily sized textures based on a small sample. The generated textures are perceived as very similar to the given sample. One main drawback of these techniques, however, is that the synthesized result cannot be locally controlled, that is, we are able to synthesize a larger version of the sample but without muc...

In this work, a novel facial feature extraction method is proposed for automatic facial expressions recognition, which detecting local texture information, global texture information and shape information of the face automatically to form the facial features. First, Active Appearance Model (AAM) is used to locate facial feature points automatically. Then, the local texture information in these ...

This paper addresses the challenging problem of the recognition and classification of textured surfaces given a single instance acquired under unknown pose, scale and illumination conditions. We propose a novel texture descriptor, the Adaptive Median Binary Pattern (AMBP) based on an adaptive analysis window of local patterns. The principal idea of the AMBP is to convert a small local image pat...

Local or global rotation invariant feature extraction has been widely used in texture classification. Local invariant features, e.g. local binary pattern (LBP), have the drawback of losing global spatial information, while global features preserve little local texture information. This paper proposes an alternative hybrid scheme, globally rotation invariant matching with locally variant LBP tex...

0957-4174/$ see front matter 2011 Elsevier Ltd. A doi:10.1016/j.eswa.2011.08.165 ⇑ Corresponding author. Tel.: +39 0547 339121; fax E-mail addresses: [email protected] (L. Nanni), (S. Brahnam), [email protected] (A. Lumini). Presented in this paper is a novel feature extractor technique based on texture descriptors. Starting from the standard feature vector representation, we study ...

In this paper, we present a novel approach for image retrieval based on extraction of low level features using techniques such as Directional Binary Code (DBC), Haar Wavelet transform and Histogram of Oriented Gradients (HOG). The DBC texture descriptor captures the spatial relationship between any pair of neighbourhood pixels in a local region along a given direction, while Local Binary Patter...