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...

PURPOSE To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. METHODS Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed ...

This paper presents preliminary results for the classiication of Pap Smear cell nuclei, using Gray Level Co-occurrence Matrix (GLCM) textural features. We outline a method of nuclear segment-ation using fast morphological gray-scale transforms. For each segmented nucleus, features derived from a modiied form of the GLCM are extracted over several angle and distance measures. Linear Discriminant...

243  Abstract: Accurate automatic detection and classification of images is very challenging task whether they are medical images or other natural images. This paper presents a hybrid technique for automatic classification of MRI images as well as natural images. The proposed method consists of two stages: feature extraction and classification. In first stage, features are extracted from image...

The primary factors in determining beef quality grades are the amount and distribution of intramuscular fat percentage (IMFAT). Texture analysis was applied to ultrasound B-mode images from ribeye muscle of live beef cattle to predict its IMFAT. We used wavelet transform (WT) for multiresolutional texture analysis and second-order statistics using a gray-level co-occurrence matrix (GLCM) techni...

Texture classification is a problem that has been studied and tested using different methods due to its valuable usage in various pattern recognition problems, such as wood recognition and rock classification. The Grey-level Co-occurrence Matrices (GLCM) and Gabor filters are both popular techniques used on texture classification. This paper combines both techniques in order to increase the acc...

Automated grading system plays an important role in many industries. In ceramic industries, the grading of ceramic tiles is a difficult task as it has huge variations of surface properties. In this paper, automated surface grading system based on Discrete Wavelet Transform (DWT) and Gray Level Co-occurrence Matrices (GLCM) is presented. Texture information’s in ceramic tiles are effectively rep...

BACKGROUND Gliomas are the most common primary brain neoplasms. Misdiagnosis occurs in glioma grading due to an overlap in conventional MRI manifestations. The aim of the present study was to evaluate the power of radiomic features based on multiple MRI sequences - T2-Weighted-Imaging-FLAIR (FLAIR), T1-Weighted-Imaging-Contrast-Enhanced (T1-CE), and Apparent Diffusion Coefficient (ADC) map - in...

OBJECTIVES To analyze the texture features on cranial sonography in preterm neonates with white matter injury quantitatively and to correlate these features with magnetic resonance imaging (MRI). METHODS The study included 33 preterm neonates treated in our neonatal intensive care unit who underwent serial cranial sonography and brain MRI near term. Patients were subdivided into 3 groups acco...