This paper proposes a novel technique for the detection and localization of copy-move regions in image using gray level run length matrix (GLRLM) features. In the proposed method, we first divide the forged image into overlapping blocks and GLRLM features are calculated for each block. Features ...
Applying the gray-level co-occurrence matrix (GLCM) and gray-level run length matrix (GLRLM) feature extraction techniques, the features of the four classes (normal, lung opacity, viral pneumonia, and COVID-19) have been extracted and then classified by utilizing a machine learning (ML) ...
Dominant Gray Level Run Length Matrix method (DGLRLMSupport Vector Machine (SVMSpatial Gray Level Dependence Matrix method (SGLDMGenetic Algorithm(GATumor classification and segmentation from brain computed tomography image data is an important but time consuming task performed manually by medical experts...
This matrix can be seen as a complement to the gray level run length matrix (GLRLM). It offers size distribution of texture elements for a given direction in the image. We find that the feature set of the GLGLM gives good results for texture classification. For periodicity detection, ...
Applying the gray-level co-occurrence matrix (GLCM) and gray-level run length matrix (GLRLM) feature extraction techniques, the features of the four classes (normal, lung opacity, viral pneumonia, and COVID-19) have been extracted and then classified by utilizing a machine learning (ML) ...
We compute a set of texture features from the scaled images including 30 gray level co-occurrence matrix (GLCM) features and 11 gray level run length matrix (GLRLM) features. Using a random forest classifier to distinguish between hyperplastic polyps and all others (adenomas and adenocarcinomas),...
We compute a set of texture features from the scaled images including 30 gray level co-occurrence matrix (GLCM) features and 11 gray level run length matrix (GLRLM) features. Using a random forest classifier to distinguish between hyperplastic polyps and all others (adenomas and adenocarcinomas),...