Results 191 to 200 of about 22,865 (233)

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

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

Classification of Chili Leaf Disease Using the Gray Level Co-occurrence Matrix (GLCM) and the Support Vector Machine (SVM) Methods

International Conference on Intelligent Computing, 2021
Chili is a type of vegetable that has a very high economic value. The problem that often occurs in chili plants is that many agricultural losses are caused by disease.
Y. Sari, Andreyan Rizky Baskara, Rika Wahyuni   +2 more
semanticscholar   +1 more source

Texture description using multi-scale morphological GLCM

Multimedia Tools and Applications, 2018
Texture is the collective repetitive pattern that characterizes the surface of real world objects. The main challenge in the texture description is its application specific definition. The present work aims at bringing the definition of textures under a generalized framework and propose some texture descriptors.
Mudassir Rafi, Susanta Mukhopadhyay
openaire   +1 more source

Texture segmentation using different orientations of GLCM features

Proceedings of the 6th International Conference on Computer Vision / Computer Graphics Collaboration Techniques and Applications, 2013
This paper describes the development of a new texture based segmentation algorithm which uses a set of features extracted from Grey-Level Co-occurrence Matrices. The proposed method segments different textures based on noise reduced features which are effective texture descriptor.
Andrik Rampun, Harry Strange, Reyer Zwiggelaar   +2 more
openaire   +1 more source

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

GLCM Based Feature Extraction and Medical X-RAY Image Classification using Machine Learning Techniques

2019 IEEE Conference on Information and Communication Technology, 2019
The machine learning and artificial intelligence play a vital role to solve the challenging issues in Clinical imaging. The machine learning and artificial intelligence ease the daily life of both medical practitioner and patient's.
P. Mall, Pradeep Singh, Divakar Yadav
semanticscholar   +1 more source

GLCM texture classification for EEG spectrogram image

2010 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), 2010
Over the past century, time based and frequency based is used for analyzing Electroencephalography (EEG) signals. EEG is a scientific tool for measure signal from human brain. This paper proposes a time-frequency approach or spectrogram image processing technique for analyzing EEG signals.
Mahfuzah Mustafa, null Mohd Nasir Taib, Zunairah Hj. Murat, null Noor Hayatee Abdul Hamid   +3 more
openaire   +1 more source

GLCM and neural network-based watermark identification

SPIE Proceedings, 2008
In this work, we extend our previous research on gray level co-occurrence matrix (GLCM) based watermark embedding in the discrete cosine transform (DCT) domain to the discrete wavelet transform (DWT) domain. The GLCM method incorporated human visual system information into the embedding process making the watermark more transparent.
Lifford McLauchlan, Mehrübe Mehrübeoğlu   +1 more
openaire   +1 more source

The Combine of GLCM and Group, Focuses on the Grayscale of Medical Images

2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Medical image classification is very important in the diagnosis of hepatocellular carcinoma, which can provide more accurate computer-aided diagnosis, and accurate extraction of key semantic information from medical data is crucial to improve classification performance.
Zechen Zheng, Chao Fan, Congqian Wang, Miao Wang, Lizhi Zhang, Xiaowei He 0001, Xuelei He   +6 more
openaire   +2 more sources