The features Gray Level Co-occurrence Matrix (GLCM) are mostly explored in Face Recognition and CBIR. GLCM technique is explored here for Copy-Move Forgery Detection. GLCMs are extracted from all the images in the database and statistics such as contrast, correlation, homogeneity and energy are derived. These statistics form the feature vector. Support Vector Machine (SVM) is trained on all the...

In this study we proposes an effective content based image retrieval by color and texture based on wavelet coefficient method to achieve good retrieval in efficiency. Color feature extraction is done by color Histogram. The texture feature extraction is acquired by Gray Level Coocurence Matrix (GLCM) or Color Coocurence Matrix (CCM). This study provides better result for image retrieval by inte...

Seismic interpretation can be supported by seismic attribute analysis. Common seismic attributes use mathematical relationships based on the geometry and the physical properties of the subsurface to reveal features of interest. But they are mostly not capable of describing the spatial arrangement of depositional facies or reservoir properties. Textural attributes such as the grey level co-occur...

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...

For diagnosis of lung tumors, CT scan of lungs is one of the most common imaging modalities. Manually identifying tumors from hundreds of CT image slices for any patient may prove to be a tedious and time consuming task for the radiologists. Therefore, to assist the physicians we propose an automatic lung tumor detection method based on textural features. The lung parenchyma region is segmented...

Automated and accurate classification of brain MRI is such important that leads us to present a new robust classification technique for analyzing magnetic response images. The proposed method consists of three stages, namely, feature extraction, dimensionality reduction, and classification. We use gray level co-occurrence matrix (GLCM) to extract features from brain MRI and for selecting the be...

In this study, we proposed score fusion technique to improve the performance of remote sensing image retrieval system (RS-IRS) using combination of several features. The representation of each feature is selected based on their performance when used as single feature in RS-IRS. Those features are color moment using L*a*b* color space, edge direction histogram extracted from Saturation channel, ...