Texture analysis is one of the important as well as useful tasks in image processing applications. Many texture models have been developed over the past few years and Local Binary Patterns (LBP) is one of the simple and efficient approach among them. A number of extensions to the LBP method have been also presented but the problem remains challenging in feature vector generation and comparison....

This paper introduces a new classification scheme called “open-ended texture classification.” The standard approach for texture classification is to use a closed n-class classifier based on the Bayesian paradigm. These perform supervised classification, whereby all the texture classes have to be predefined. We propose a new texture classification scheme, one that does not require a complete set...

In this paper, we propose a texture representation framework to map local texture patches into a low-dimensional texture subspace. In natural texture images, textons are entangled with multiple factors, such as rotation, scaling, viewpoint variation, illumination change, and non-rigid surface deformation. Mapping local texture patches into a low-dimensional subspace can alleviate or eliminate t...

-This paper presents a computational model and a practical algorithm for determining the three-dimensional orientation of a planar surface from visual texture information. The model consists of three parts: (1) a local spatial frequency based texture representation; (2) a model describing the projection of surface texture to image texture; and (3) a solution of the texture projection model for ...

A video content analysis tool for video coding is presented. The underlying assumption of our approach is that the textures in a video scene can be labeled subjectively relevant or irrelevant. Relevant textures are defined as containing subjectively meaningful details, while irrelevant textures contain less important subjective details. We apply this idea to video coding using a texture analyze...

In image processing, a static texture is defined as an image showing spatial stationarity, while A dynamic texture is a sequence of images characterized by temporal as well as spatial stationary nature. Dynamic Texture synthesis is the process of producing artificial Dynamic textures starting from a given sample texture. Videos representing flames, water, smoke, etc. are often defined as dynami...

We assume that the textures in a video scene can be classified into two categories: textures with unimportant subjective details and the remainder. We utilize this assumption for improved video coding using a texture analyzer and a texture synthesizer. The texture analyzer identifies the texture regions with unimportant subjective details and generates coarse masks as well as side information f...

A new approach to analyze and synthesize texture regions in video coding is presented, where texture blocks in video sequence are synthesized using graph cut technique. It first identifies the texture regions by video segmentation technique, and then calculates their motion vectors by motion vector (MV) scaling technique like temporal direct mode. After the correction of these MVs, texture regi...

Providing efficient access to the huge amounts of existing medical imaging data is a highly relevant but challenging problem. In this paper, we present an effective method for content-based image retrieval (CBIR) of anomalies in medical imaging data, based on similarity of local 3D texture. During learning, a texture vocabulary is obtained from training data in an unsupervised fashion by extrac...

As an object approaches the eye, its retinal image size grows larger and its surface texture appears to grow coarser. We compare these two visual correlates of motion in their effectiveness as stimuli for motion in depth. In some experiments texture and object size both expanded or both contracted: in other experiments the two stimuli were pitted against each other. When texture and size change...