A novel statistical image model is proposed to facilitate the design and analysis of image processing algorithms. A mean-removed image neighborhood is modeled as a scaled segment of a hypothetical texture source, characterized as a 2-D stationary zero-mean unit-variance random field, specified by its autocorrelation function. Assuming that statistically similar image neighborhoods are derived f...

Color models are widely used in image recognition because they represent significant information. On the other hand, texture analysis techniques have been extensively used for facial feature extraction. In this paper; we extract discriminative features related to facial attributes by utilizing different color models and texture analysis techniques. Specifically, we propose novel methods for tex...

An algorithm for synthesizing color textures from a small set of parameters is presented in this paper. The synthesis algorithm is based on the 2-D moving average model, and realistic textures resembling many real textures can be synthesized using this algorithm. A maximum likelihood estimation algorithm to estimate parameters from a sample texture is also presented. Using the estimated paramet...

ISSN: 2277-503X| © 2015 Bonfring Abstract--Fingerprint alteration is the process of changing the regularly spaced ridge structure by mechanical or chemical means to hide the identity from Automated Fingerprint Identification System. This paper presents a method for altered fingerprint matching using texture and ridge frequency in the unaltered region. Wavelet transform is used to create feature...

This paper introduces a texture representation suitable for recognizing images of textured surfaces under a wide range of transformations, including viewpoint changes and nonrigid deformations. At the feature extraction stage, a sparse set of affine-invariant local patches is extracted from the image. This spatial selection process permits the computation of characteristic scale and neighborhoo...

In this paper, we study texture discrimination based on two filter families, Gabor and Hermite, which agree with the Gaussian derivative model of the human visual system. In the first part, discrimination of different textures, based on the output energy of these filters, is compared using the Fisher criterion and classification result. Results show that the presented filter bank is suitable fo...

We have recently introduced a new tool for texture analysis called feature based interaction map (FBIM). The FBIM approach can be efficiently used to assess fundamental structural properties of textures such as anisotropy, symmetry, orientation and regularity [4]. It has been demonstrated [5] that the FBIM is suitable for rotation-invariant texture classification of patterns with regular, weak ...

Texture constitutes one of the fundamental properties of objects, besides color and shape. In several image analysis applications it is often the only exploitable quality of objects. As such, it has been studied, described, segmented, synthesized or in short analyzed, extensively. Among the plethora of texture description methods, mathematical morphology deserves special attention, as it excels...

Various methods have been developed for texture segmentation. Since all of them have their merits and drawbacks, the choice of the most suitable method becomes a nontrivial task. We present a comparative study of texture segmentation methods based on four frequently used texture feature extraction techniques: gray level co-occurrence matrices, Gaussian Markov random fields, Gabor filtering, and...

This paper justifies and demonstrates a machine learning approach to the problem of texture recognition. The learning-based texture recognition is separated into the following phases: (i) the acquisition of texture concepts, (ii) the optimization of concept prototypes, and (iii) the recognition of unknown texture samples. Methodology adapted to the acquisition and recognition of-noisy texture d...