In order to recognize breast cancer histopathological images, this article proposed a combined model consisting of pyramid gray level co-occurrence matrix (PGLCM) feature extraction and an incremental broad learning (IBL) classification model. The PGLCM is designed extract the fusion features which can reflect multiresolution useful information images facilitate improvement effect in later stag...

T. Beach, P. Gibbs, M. D. Pickles, L. Turnbull Centre for MR Investigations, University of Hull, Hull, United Kingdom Introduction Quantitative textural analysis is an established method of image classification in aerial and satellite photography. In recent years attempts have been made to utilise texture in MRI, particularly in the brain [1-6], but also in other organs such as breast [7] and l...

Texture attributes describe the spatial arrangement of neighboring amplitudes values within a given analysis window. We chose a statistical texture classification method, the gray-level co-occurrence matrix (GLCM), and its derived attributes, to produce a semiautomated description of the spatial arrangement of seismic facies. The GLCM is a measure of how often different combinations of neighbor...

A method for an anomaly detection system was developed to automate process of recognizing an anomaly of roentgen image by utilizing fuzzy histogram hyperbolization image enhancement and gray level co-occurrence matrix(GLCM). The system consists of image acquisition, pre-processor, feature extractor, response selector and output. Fuzzy Histogram Hyperbolization is chosen to improve the quality o...

This study extended the computation of GLCM (gray level co-occurrence matrix) to a three-dimensional form. The objective was to treat hyperspectral image cubes as volumetric data sets and use the developed 3D GLCM computation algorithm to extract discriminant volumetric texture features for classification. As the kernel size of the moving box is the most important factor for the computation of ...

Adequate knowledge, such as information about the unique characteristics of each plant, is necessary to identify plant. Researchers have made plant recognition based on leaf characteristics. The leaf image-based plant recognition in view of different angles is a new challenge. In this study, the research on the plant recognition was conducted based on leaf images resulted from 3D stereo camera....

Reconstructing and repairing damaged parts after object removal of digital video is an important trend in artwork restoration. Video completion is an active subject in video processing, which deals with the recovery of the original data. Most previous video completion approaches consume more time in extensive search to find the best patch to restore the damaged frames. In addition to that, visu...

In this paper, the classification of Brain Magnetic Resonance Images (MRI) and Liver Computed Tomography (CT) images has been analysed using supervised technique. The proposed method includes four stages pre-processing, fuzzy clustering, feature extraction and classification. For extracting the features Gray Level Co-occurrence Matrix (GLCM) method has been used. The main features regarding sha...

This paper proposes a steganalysis technique for both grayscale and color images. It uses the feature vectors derived from gray level co-occurrence matrix (GLCM) in spatial domain, which is sensitive to data embedding process. This GLCM matrix is derived from an image. Several combinations of diagonal elements of GLCM are considered as features. There is difference between the features of stego...

Texture is literally defined as consistency of a substance or a surface. Technically, it is the pattern of information or arrangement of structure found in an image. Texture is a crucial characteristic of many image type and textural features have a plethora of application viz., image processing, remote sensing, content-based imaged retrieval and so on. There are various ways of extracting thes...