Abstract COVID-19 has caused over 6.35 million deaths and 555 confirmed cases till 11/July/2022. It a serious impact on individual health, social economic activities, other aspects. Based the gray-level co-occurrence matrix (GLCM), four-direction varying-distance GLCM (FDVD-GLCM) is presented. Afterward, five-property feature set (FPFS) extracts features from FDVD-GLCM. An extreme learning mach...

SUMMARY The grey level co-occurrence matrix (GLCM) is a measure of the texture of an image. It describes how often different combinations of pixel brightness values occur in an image. Based on this, several textural attributes can be calculated. These directional attributes can be used to determine isotropic and anisotropic areas. In anisotropic areas the information of directional GLCM-based a...

In this paper, a new method for heuristics and intermediate features based image retrieval is proposed. Heuristic features are identified and directly stored into the database and easily retrieved also. An algorithm is used to convert low level features hue, saturation and intensity in HSI space to semantic based color names. Images can be retrieved by these semantic color names. For semantics ...

BACKGROUND To assess the feasibility of texture analysis (TA) based on spectral attenuated inversion-recovery T2 weighted magnetic resonance imaging (SPAIR T2W-MRI) for the classification of hepatic hemangioma (HH), hepatic metastases (HM) and hepatocellular carcinoma (HCC). METHODS The SPAIR T2W-MRI data of 162 patients with HH (n=55), HM (n=67) and HCC (n=40) were retrospectively analyzed. ...

A novel approach using volumetric texture and reduced-spectral features is presented for hyperspectral image classification. Using this approach, the volumetric textural features were extracted by volumetric gray-level co-occurrence matrices (VGLCM). The spectral features were extracted by minimum estimated abundance covariance (MEAC) and linear prediction (LP)-based band selection, and a semi-...

A critical shortcoming of determining co-occurrence probability texture features using Haralick’s popular grey level co-occurrence matrix (GLCM) is the excessive computational burden. In this paper, the design, implementation, and testing of a more efficient algorithm to perform this task are presented. This algorithm, known as the grey level co-occurrence integrated algorithm (GLCIA), is a dra...

-In this paper, a new method for intermediate features based image retrieval is proposed. Image database is constructed with low level texture features obtained from Gray Level Co-Occurrence Matrix (GLCM). Semantic level queries from the user mapped to the low level features at retrieval time to retrieve the required images. Artificial Neural Network (ANN) is used in the next steps after receiv...

For terrain recognition needs during vehicle driving, this paper carries out classification research based on vibration and image information. Twenty time-domain features eight frequency-domain of signals that are highly correlated with selected, principal component analysis (PCA) is used to reduce the dimensionality retain main Meanwhile, texture images extracted using gray-level co-occurrence...

As the world continues to battle devastating effects of COVID-19 pandemic, it has become increasingly crucial screen patients for contamination accurately and effectively. One primary screening methods is chest radiography, utilizing radiological imaging detect presence virus in lungs. This study presents a cutting-edge solution classify infections X-ray images by Gray-Level Co-occurrence Matri...