Results 271 to 280 of about 220,110 (307)

Effects of Iron Oxide Nanoparticles on Structural Organization of Hepatocyte Chromatin: Gray Level Co-occurrence Matrix Analysis

Microscopy and Microanalysis, 2021
Gray level co-occurrence matrix (GLCM) analysis is a contemporary and innovative computer-based algorithm that can be used for the quantification of subtle changes in a cellular structure.
Jovana Paunovic, D. Vučević, T. Radosavljević, B. Vukomanovic Djurdjevic, S. Stanković, I. Pantić   +5 more
semanticscholar   +1 more source

Directional Analysis of Texture Images Using Gray Level Co-Occurrence Matrix

2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, 2008
Direction parameter thetas is one of the important parameters of GLCM (gray level co-occurrence matrix). A fixed angle (such as thetas=45deg) or the average of the measurements in four direction (thetas=0deg,45deg,90deg,135deg) were usually used in calculating GLCM. However, these methods are just empiristic idea, lacking of theoretical support.
Yong Hu, Chun-xia Zhao, Hong-nan Wang
openaire   +1 more source

Iris authentication using Gray Level Co-occurrence Matrix and Hausdorff Dimension

2015 International Conference on Computer Communication and Informatics (ICCCI), 2015
Many of the researchers suggest that, Biometrics is the only solution for user identification and security problems. Password incorrect use and misapplication, intentional and inadvertent is a gaping hole in security. These results are mainly occurs due to Poor human judgment, carelessness and due to tactlessness.
P. Steffi Vanthana, A. Muthukumar
openaire   +1 more source

Fired bullet signature correlation using the finite ridgelet transform (FRIT) and the gray level co-occurrence matrix (GLCM) methods.

Forensic Science International, 2021
When a bullet is fired from a barrel, micro striation marks caused by the sliding motion of the bullet through the rifled barrel are one of the foremost factors in automated ballistic identification.
Jialing Zhu, R. Hong, Hao Zhang, Ran Gu, Hua Wang, Fuzhong Sun   +5 more
semanticscholar   +1 more source

Extended gray level co-occurrence matrix computation for 3D image volume

SPIE Proceedings, 2017
Gray Level Co-occurrence Matrix (GLCM) is one of the main techniques for texture analysis that has been widely used in many applications. Conventional GLCMs usually focus on two-dimensional (2D) image texture analysis only. However, a three-dimensional (3D) image volume requires specific texture analysis computation. In this paper, an extended 2D to 3D
Nurulazirah M. Salih, Dyah Ekashanti Octorina Dewi   +1 more
openaire   +1 more source

Prediction of Malignancy in Lung Nodules Using Combination of Deep, Fractal, and Gray-Level Co-Occurrence Matrix Features

Big Data, 2021
Accurate detection of malignant tumor on lung computed tomography scans is crucial for early diagnosis of lung cancer and hence the faster recovery of patients.
Amrita Naik, D. Edla, Ramesh Dharavath
semanticscholar   +1 more source

Skin Roughness Evaluation Method Based on gray level co-occurrence matrix

2019 Chinese Control And Decision Conference (CCDC), 2019
To evaluate the Skin roughness in the image of human, skin features are based on eigenvalues of the gray level co-occurrence matrix are used, and the Pearson correlation coefficient is used to select the eigenvalues as the evaluation index. In the calculation of new eigenvalue, the normal equation is used to calculate the weight to improve the accuracy
Minghao LU, Yifei LIU, Wenjuan HE, Xiuxiu LI   +3 more
openaire   +1 more source

An optimized skin texture model using gray-level co-occurrence matrix

Neural Computing and Applications, 2017
Texture analysis is devised to address the weakness of color-based image segmentation models by considering the statistical and spatial relations among the group of neighbor pixels in the image instead of relying on color information of individual pixels solely. Due to decent performance of the gray-level co-occurrence matrix (GLCM) in texture analysis
Maktabdar Oghaz, M., Maarof, M. A., Rohani, M. F., Zainal, A., Shaid, S. Z. M.   +4 more
openaire   +1 more source

Electroencephalography-Based Emotion Recognition Using Gray-Level Co-occurrence Matrix Features

2016
Emotions are very essential for our day-to-day activities such as communication, decision-making and learning. Electroencephalography (EEG) is a non-invasive method to record electrical activity of the brain. To make Human–Machine Interaction (HMI) more natural, human emotion recognition is important.
Narendra Jadhav, Ramchandra Manthalkar, Yashwant Joshi   +2 more
openaire   +1 more source

Non-subsampled contourlets and gray level co-occurrence matrix based images segmentation

2011 International Conference on Uncertainty Reasoning and Knowledge Engineering, 2011
Contourlet is a new geometric multiscale tool that is based on multiscale filters and directional filter banks. It not only inherits the multiscale characteristics of dimensionality-inseparable wavelets, but also has the flexible multi-directional characteristic by changing the directions of transform and sequences.
Zhang Jian, Chen Xiaowei
openaire   +1 more source