The main goal of this paper is to introduce formally the concept of texture segmentation/identification in three dimensional images. A major problem in texture texture segmentation/identification is the lack of robustness to both translations and rotations. This problem is more difficult to overcome in 3D-images, such as those generated by modalities such as x-ray CT and MRI. To facilitate 3D-t...

In this paper, we study how a multidimensional local binary pattern (LBP) texture feature data can be visually explored and analyzed. The goal is to determine how true paper properties can be characterized with local texture features from visible light images. We utilize isometric feature mapping (Isomap) for the LBP texture feature data and perform non-linear dimensionality reduction for the d...

Texture analysis has many areas of potential application in industry. The problem of determining composition of grain mixtures by texture analysis was recently studied by Kjell. He got promising results when using all nine Laws’ 3x3 features simultaneously and an ordinary feature vector classifier. In this paper the performance of texture classification based on feature distributions in this pr...

This paper explores a design-based method to fuse Gabor filter features and co-occurrence probability features for improved texture recognition. The fused feature set utilizes both the Gabor filter’s capability of accurately capturing lower frequency texture information and the co-occurrence probability’s capability in texture information relevant to higher frequency components. Fisher linear d...

It is known that the human visual system, unsurpassed in its ability to reconstruct surfaces, employs different cues to solve this difficult task. The prevailing method in digital photogrammetry is stereopsis. However, texture may provide valuable information about the shape of surfaces. In this paper we employ Laws' method of texture energy transforms to extract texture information from digita...

Texture analysis plays an increasingly important role in computer vision. Since the textural properties of images appear to carry useful information for discrimination purposes, it is important to develop significant features for texture. This paper presents a novel technique for texture extraction and classification. The proposed feature extraction technique uses 2D–DFT transformation. A combi...

In this technical report, we present a technique to synthesize featured textures easily and interactively. The main idea is to synthesize the texture by copying irregular patches from the source to the target texture, each of them containing a complete feature. The interior part of the feature is not touched while the cutting and stitching is done on the background texture between the features....

In this paper we propose a novel feature extraction scheme for texture classi cation, in which the texture features are extracted by a two-level hybrid scheme by integrating two statistical techniques of texture analysis. In the rst step, the low level features are extracted by the Gabor lters, and they are encoded with the feature map indices using the Kohonen's SOFM algorithm. In the next ste...

This paper presents an approach to texture image segmentation using a family of fractional discrimination functions. In contrast to the conventional methods, the proposed functions provide uniform treatment of the existing functions and operators for selective feature extraction. The effectiveness of fractional discrimination functions for texture feature detection is demonstrated in the presen...