Vision is the most important resource of information for human beings which contain several activities. Amongst these activities, object recognition and classification are widely used. Although, images are representation of vision which can be interpreted by machines, some images often do not exhibit regions of uniform intensity, but these images may contain variation of intensities which form ...

Statistical shape-and-texture appearance models use image morphing to define a rich, compact representation of object appearance. They are useful in a variety of applications including object recognition, tracking and segmentation. These techniques, however, have been limited to objects with Lambertian surface reflectance, simple geometry and topology. In this work we present new shape-and-text...

In this paper, we cast natural-image segmentation as a problem of clustering texture features as multivariate mixed data. We model the distribution of the texture features using a mixture of Gaussian distributions. Unlike most existing clustering methods, we allow the mixture components to be degenerate or nearly-degenerate. We contend that this assumption is particularly important for mid-leve...

The aims of this paper are two-fold: to define Gaussian mixture models (GMMs) of colored texture on several feature spaces and to compare the performance of these models in various classification tasks, both with each other and with other models popular in the literature. We construct GMMs over a variety of different color and texture feature spaces, with a view to the retrieval of textured col...

Julesz introduced the concept of statistically defined textures and their perceptual discrimination. Julesz showed that discrimination was possible with statistics equated to third-order, specifying fourth-order textures. Klein and Tyler offered a variety of paradigms suggesting that fourth order might be the limit on human texture processing. To go beyond this limit, new texture paradigms are ...

In recent years, a wide variety of different texture descriptors has been proposed, includingmany LBP variants. New types of descriptors based on multistage convolutional networks and deep learning have also emerged. In different papers the performance comparison of the proposed methods to earlier approaches is mainly done with some well-known texture datasets, with differing classifiers and te...

There exist many computer graphics techniques which could achieve high quality tree generation. However, only a few works focus on realistic modeling of tree bark. Difficulties lie in the complex appearance of the bark surfaces which are largely determined by their mesostructures. Unlike traditional physical based methods, in this paper, we present an appearance-based method to model tree bark ...

Synthetic Aperture Radar (SAR) has been proven to be a powerful earth observation tool. Due to its sensitivity to vegetation, its orientations and various land-covers, SAR polarimetry has the potential to become a principle mean for crop and land-cover classification. A variety of polarimetric classification algorithms have been proposed in the literature for segmentation and/or classification ...

In order to quantify the ability of the human visual system to use texture information to perceive planar surface orientation, I measured subjects’ ability to discriminate planar surface slant (angle away from the fronto-parallel) for a variety of different types of textures and in a number of different viewing conditions. I measured the subjects’ discrimination performance as a function of sur...

This paper deals with the application of a multi-channel ltering-based texture segmentation method to a variety of document image processing problems: text-graphics separation, address-block location, and bar code localization. Both supervised and unsuper-vised methods have been used to identify regions of text or bar code in the input gray level document images. The performance of our segmenta...