Results 191 to 200 of about 15,845 (235)

Source camera identification using GLCM

2015 IEEE International Advance Computing Conference (IACC), 2015
Digital images are becoming main focus of work for the researchers. Digital image forensics (DIF) is at the forefront of security techniques, aiming to restore the lost trust in digital imagery by uncovering digital counterfeiting techniques. Source camera identification provides different ways to identify the characteristics of the digital devices ...
Nilambari Kulkarni, Vanita Mane
openaire   +1 more source

Landslide Detection Based on GLCM Using SAR Images

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020
Detecting the change of texture information is very important for landslide detection. In polarimetric SAR imagery, the landslides not only have typical polarimetric features but also have rich texture features. In this study, the texture feature extraction technique based on gray scale co-occurrence matrix was applied to process two SLC Sentinel-1A C ...
Baihui Li, Yan Chen 0003, Yunping Chen, Youchun Lu, Cunshi Ma   +4 more
openaire   +1 more source

Extraction of Slum Areas From VHR Imagery Using GLCM Variance [PDF]

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016
Many cities in the global South are facing the emergence and growth of highly dynamic slum areas, but often lack detailed information on these developments.
Monika Küffer, Karin Pfeffer, Richard Sliuzas   +2 more
exaly   +2 more sources

GLCM parameters of channel texture analysis

SEG Technical Program Expanded Abstracts 2011, 2011
Summary Channel texture is an acoustic expression of a fluvial facies derived from 3D seismic data. The Gray Level Cooccurrence Matrix (GLCM) technique has been proven to be a promising method for seismic texture analysis. However, while we try to extract seismic texture attributes, there is uncertainty on how to select the optimal GLCM parameters ...
Zhiguo Wang, Cheng Yin, Wei Zhao
openaire   +1 more source

GLCM-based fingerprint recognition algorithm

2011 4th IEEE International Conference on Broadband Network and Multimedia Technology, 2011
An efficient and reliable fingerprint recognition system is the fundamental need of contemporary living. Beside forensic use, it has been deployed in a large number of commercial applications recently. In this paper, a new method for fingerprint recognition is introduced. The Core point is found initially using Poincare Index method.
Amjad Ali, Xiaojun Jing, Nasir Saleem
openaire   +1 more source

Texture Image Segmentation Based on GLCM

Applied Mechanics and Materials, 2012
The paper proposed a method on marble texture image segmentation based on Gray Level Co-occurrence Matrix (GLCM). At first, compute the Contrast matrix on basis of GLCM. Then choose the maximum of the matrix as the threshold to segment the object. At last extract the object contour with curve fitting method.
Min Li, Jian Jun Liao
openaire   +1 more source

Image Retrieval Method with Fisher GLCM and Graph Model

Proceedings of the 2018 2nd International Conference on Video and Image Processing, 2018
Content-based image retrieval (CBIR) technology is a hot topic for finding the needed images from image big data. A new image retrieval method with fisher GLCM and Graph model is proposed in this paper. The new method designs a new image descriptor with Fisher GLCM features, to extract differentiable features of images; and presents a twice retrieval ...
Honghu Hua, Jianghua Cheng, Tong Liu 0006   +2 more
openaire   +1 more source

Influence of GLCM texture parameters on lithological mapping using Sentinel-1 imagery

Geocarto International
Gray Level Co-Occurrence Matrix (GLCM) textures demonstrate great potential in lithological mapping, yet the influence of GLCM parameters (window size, distance, and angle) on mapping lithology using Sentinel-1 images has never been thoroughly explored ...
Changbao Yang
exaly   +2 more sources

The Analysis of Digital Mammograms Using HOG and GLCM Features

2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2018
An algorithm for early detection of breast cancer is proposed in this paper. Breast cancer is one disease if detected early, can be cured effectively. Failure of early detection is causing many deaths among woman worldwide. Early detection requires proper screening. Digital mammograms are useful for this purpose as they are non-invasive.
Krishna Chaitanya Tatikonda, Chandra Mohan Bhuma, Samayamantula Srinivas Kumar   +2 more
openaire   +1 more source

Gingivitis Identification via GLCM and Artificial Neural Network

2020
Gingivitis is a common oral disease. The diagnosis process of gingivitis disease is usually based on the experience of the dentist and previous medical records. In order to diagnose gingivitis more efficiently and accurately, we proposed a gingivitis recognition program based on Gray-Level Co-Occurrence Matrix (GLCM), Artificial Neural Network (ANN ...
Yihao Chen, Xianqing Chen
openaire   +1 more source