A commonly used representation of a visual pattern is the set of marginal probability distributions of the output of a bank of filters (Gaussian, Laplacian, Gabor etc...). This representation has been used effectively for a variety of vision tasks including texture classification, texture synthesis, object detection and image retrieval. This paper examines the ability of this representation to ...

In this paper, the texture property “coarseness” is modeled by means of type-2 fuzzy sets, relating representative coarseness measures (our reference set) with the human perception of this texture property. The type-2 approach allows to face both the imprecision in the interpretation of the measure value and the uncertainty about the coarseness degree associated with a measure value. In our stu...

Markov/Gibbs random elds have been used for posing a variety of computer vision and image processing problems. Many of these problems are then solved using a simulated annealing type of method which involves the varying of the \temperature," a scale parameter for the model. In this paper we analyze the eeect of temperature on random eld texture patterns. We obtain new results relating structure...

We present a system for detecting the pose of rigid objects using texture and contour information. From a stereo image view of a scene, a sparse hierarchical scene representation is reconstructed using an early cognitive vision system. We define an object model in terms of a simple context descriptor of the contour and texture features to provide a sparse, yet descriptive object representation....

Human vision is the most important resource of information used for object recognition and classification. Images having constant intensities can be easily represented by vision. Textures are one of the important features in computer vision as it identifies different regions of an image on the basis of texture properties. It is widely used in variety of applications. Identifying various regions...

Edges are viewed as statistical outliers with respect to local image gradient magnitudes. Within local image regions we compute a robust statistical measure of the gradient variation and use this in an anisotropic di usion framework to determine a spatially varying \edgestopping" parameter . We show how to determine this parameter for two edge-stopping functions described in the literature (Per...

A novel method for 3D head tracking in the presence of large head rotations and facial expression changes is described. Tracking is formulated in terms of color image registration in the texture map of a 3D surface model. Model appearance is recursively updated via image mosaicking in the texture map as the head orientation varies. The resulting dynamic texture map provides a stabilized view of...

A number of three-dimensional algorithms have been proposed to solve the problem of patching surfaces to rectify and extrapolate missing information due to model problems or bad geometry visibility during data capture. On the other hand, a number of similar yet more simple and robust techniques apply to 2D image data and are used for texture restoration. In this paper we make an attempt to brin...

Skin region detection plays an important role in a variety of applications such as face detection, adult image filtering and gesture recognition. To improve the accuracy and speed of skin detection, in this paper, we describe a fast adaptive skin detection approach that works on DCT domain of JPEG image and classifies each image block according to its color and texture properties. Main contribu...

Extracting textured objects from natural scenes is a challenging task in computer vision. The main difficulties arise from the intrinsic randomness of natural textures and the high-semblance between the objects and the background. In this paper, we approach the extraction problem with a seeded region-growing framework that purely exploits the statistical properties of intensity inhomogeneity. T...