Digital image processing is an emerging tool to predict fruit quality; therefore present study was carried out to develop an image processing technique for investigating the storage life of cantaloupe. Potassium permanganate (KMnO4) impregnated materials were used to prolong the postharvest life of cantaloupe fruit and the effects of these treatments were evaluated by 3 image textural features ...

A spatial classification technique incorporating a novel feature derivation method is proposed for classifying the heterogeneous classes present in the hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes present in the hyper spectral image are having different textures, textural classif...

The aim of the present study was to design, implement, and evaluate a software system for discriminating between metastases, meningiomas, and gliomas on MRI. The proposed classifier is a modified probabilistic neural network (PNN), incorporating a second degree least squares features transformation (LSFT) into the PNN classifier. Thirty-six textural features were extracted from each one of 75 T...

Lung cancer is the second most prevalent type of cancer. Early detection and classification of lung tumors helps in better survival. The paper presents a computer aided diagnosis (CAD) system for chest computed tomography (CT) images that focus on a new algorithm to classify lung tumor into benign or malignant using advanced neural network based classifier. Statistical textural features are ext...

The constant increase in the amount and resolution of remotely sensed imagery necessitates development of intelligent systems for automatic processing and classification. We describe a Bayesian framework that uses spatial information for classification of high-resolution images. First, spectral and textural features are extracted for each pixel. Then, these features are quantized and are used t...

This paper presents a Gabor filtering approach for automatic inspection of defects in colored texture surfaces. It simultaneously measures both chromatic and textural deviations of an image. Two brightness invariant chromatic features derived from different color spaces are used to form a complex number, which replaces the single gray-level information, for color pixel representation. The propo...

A spatial classification technique incorporating a novel feature derivation method is proposed for classifying the heterogeneous classes present in the hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes present in the hyper spectral image are having different textures, textural classif...

BACKGROUND Videocapsule endoscopy can be useful to detect small intestinal pathology in celiac disease patients. However, presence of extraneous features including air bubbles and opaque fluids can complicate the analysis. A technique for quantitative analysis of videocapsule images is presented that is robust to presence of extraneous features. METHOD Videocapsule clips were acquired from fi...

We introduced new polynomial features described as polynomials on the image pixels domain. After imposing natural conditions these features transform into linear combinations of the image autocovariance function readings. We proposed a way to adjust these features using learning sample textural properties. Experiments on a real diagnostic dataset of lung CT images showed a decrease of the error...