Results 281 to 290 of about 220,110 (307)

Defect detection on air bearing surface with gray level co-occurrence matrix

The 4th Joint International Conference on Information and Communication Technology, Electronic and Electrical Engineering (JICTEE), 2014
Air bearing surface (ABS) is the part of magnetic read/write head flying height controller. It is very important part in magnetic disk (hard disk drive), defected on ABS lead to crash between read/write head and disk surface, therefore its verifying is necessary. The best way to verify defect on ABS is machine vision.
Pichate Kunakornvong, Chiewchan Tangkongkiet, Pitikhate Sooraksa   +2 more
openaire   +1 more source

Gray Level Co-Occurrence Matrix (GLCM) Parameters Analysis for Pyoderma Image Variants

Journal of Computational and Theoretical Nanoscience, 2020
Analysis of different visual textures present in the given images is one of the important perspectives of human vision for objects segregation and identification. Texture-based features are widely used in medical diagnosis for informal prediction of dermatological diseases.
Chaahat Gupta, Naveen Kumar Gondhi, Parveen Kumar Lehana   +2 more
openaire   +1 more source

Epileptic Seizure Detection Based on Time-Frequency Images of EEG Signals Using Gaussian Mixture Model and Gray Level Co-Occurrence Matrix Features

International Journal of Neural Systems, 2018
The electroencephalogram (EEG) signal analysis is a valuable tool in the evaluation of neurological disorders, which is commonly used for the diagnosis of epileptic seizures.
Y. Li, Weigang Cui, Mei-Lin Luo, Ke Li, Lina Wang   +4 more
semanticscholar   +1 more source

Depth analysis of monocular natural scenes using gray level co-occurrence matrix

2012 4th International Conference on Intelligent and Advanced Systems (ICIAS2012), 2012
Representation of depth in a real world environment is an essential attribute of its semantic representation. A coarse estimate of image-depth (defined as mean distance between the object and the observer) is relevant for identifying the context of the scene and can be used to facilitate search and recognition of objects.
N. P. Rath, Prasanjeeta Pattnaik, Janyadatta Samantaray   +2 more
openaire   +1 more source

A new approach for texture segmentation based on the Gray Level Co-occurrence Matrix

Multimedia tools and applications, 2021
Saliha Aouat, Idir Ait-hammi, Izem Hamouchene   +2 more
semanticscholar   +1 more source

Mammogram Classification Using Nonsubsampled Contourlet Transform and Gray-Level Co-Occurrence Matrix

2020
This chapter explores diagnosis of the breast tissues as normal, benign, or malignant in digital mammography, using computer-aided diagnosis (CAD). System for the early diagnosis of breast cancer can be used to assist radiologists in mammographic mass detection and classification.
Khaddouj Taifi, Naima Taifi, Mohamed Fakir, Said Safi, Muhammad Sarfraz   +4 more
openaire   +1 more source

JPEG image tampering localization based on normalized gray level co-occurrence matrix

Multimedia Tools and Applications, 2018
To locate the tampered region of double compressed JPEG images, one of the most effective methods is based on the statistical characteristic of the images. After tampering operation, the tampered region and the original region will have different statistical distributions. And according to this cue, the histogram of DCT coefficients can be moded as the
Fei Xue, Wei Lu, Ziyi Ye, Hongmei Liu
openaire   +1 more source

A defect detection method for unpatterned fabric based on multidirectional binary patterns and the gray-level co-occurrence matrix

Textile research journal, 2019
A new texture-feature description operator, called the multidirectional binary patterns (MDBP) operator, is proposed in this paper. The operator can extract the detailed distribution of textures in local regions by comparing the differences in the gray ...
Feng Li, Lin Yuan, Kun Zhang, Wenqing Li
semanticscholar   +1 more source

Identifikasi Citra Massa Kistik Berdasar Fitur Gray-Level Co-Occurrence Matrix

Seminar Nasional Aplikasi Teknologi Informasi (SNATI), 2009
We have studied the effectiveness of using texture features derived from gray-level co-occurrence matrix(GLCM) matrices for classification of cystic mass and non-cystic mass in ultra sonograms. Twenty-three (23)region of interest (ROIs) containing cystic masses and fifty-five (55) non-cystic masses were extracted from ultrasonogram for this study.
Wibawanto, Hari, Susanto, Adhi, Widodo, Thomas Sri, Tjokronegoro, S. Maesadji   +3 more
openaire   +1 more source

Speckle Quality Evaluation Based on Gray Level Co-Occurrence Matrix

Laser & Optoelectronics Progress, 2021
初录 Chu Lu, 刘斌 Liu Bin, 许亮 Xu Liang, 李志伟 Li Zhiwei, 张宝峰 Zhang Baofeng   +4 more
openaire   +1 more source