The aim of this work was to develop a system based on modular neural networks and multi-feature texture analysis that will facilitate the automated interpretation of cloud images. This will speed up the interpretation process and provide continuity in the application of satellite imagery for weather forecasting. A series of infrared satellite images from the Geostationary satellite METEOSAT7 we...

in this paper, a new method is presented for the detection of defects in random textures. in the training stage, the feature vectors of the normal textures’ images are extracted by using the optimal response of gabor wavelet filters, and their probability density is estimated by means of the gaussian mixture model (gmm). in the testing stage, similar to the previous stage,at  first, the feature...

In this paper we have investigated a new approach for texture features extraction using co-occurrence matrix from volumetric lung CT image. Traditionally texture analysis is performed in 2D and is suitable for images collected from 2D imaging modality. The use of 3D imaging modalities provide the scope of texture analysis from 3D object and 3D texture feature are more realistic to represent 3D ...

The long-time historical evolution and recent rapid development of Beijing, China, present before us a unique urban structure. A 10-metre spatial resolution SPOT panchromatic image of Beijing has been studied to capture the spatial patterns of the city. Supervised image classifications were performed using statistical and structural texture features produced from the image. Textural features, i...

Data hiding techniques onto images provide tools for protecting copyright or sending secret messages, and they are currently utilized as a simple input device of a cell phone by detecting a data embedded in an image with an equipped digital camera. This paper presents a method of synthesizing texture images for embedding arbitrary data by utilizing the smart techniques of generating repetitive ...

The aim of our research is to analyse the importance of texture information for affine registration of gray-scale far-infrared (FLIR) images and gray-scale images taken in the visible spectrum. Texture features are extracted by Laws texture coefficients and used for computing registration criterion functions. The proposed feature based approach is compared to the commonly used approach, where a...

A wide variety of texture feature extraction methods have been proposed for texture based image classification and segmentation. These methods are typically evaluated over windows of the same size, the latter being usually chosen for each particular method on an experimental basis. This paper shows that pixel-based texture classification can be significantly improved by evaluating a given textu...

In this paper, a feature extraction technique with orthogonal polynomials based computational model to accurately extract local texture in iris images is presented. Initially, the normalized input iris image is subjected with the orthogonal polynomials model and the model coefficients are obtained. The model coefficients are subjected to statistical hypothesis testing with Hartley’s test so as ...

In this paper, we proposed a system of automatically classifying different types of dates from their images. Different dates have various distinguished features that can be useful to recognize a particular date. These features include color, texture, and shape. In the proposed system, a color image of a date is decomposed into its color components. Then, local texture descriptor in the form of ...

The evaluation of texture features is important for several image processing applications. Texture analysis forms the basis of object recognition and classification in several domains. There is a range of texture extraction methods and their performance evaluation is an important part of understanding the utility of feature extraction tools in image analysis. In this paper we evaluate five diff...