Results 261 to 270 of about 220,110 (307)

Gray Level Co-Occurrence Matrix Computation Based On Haar Wavelet

Computer Graphics, Imaging and Visualisation (CGIV 2007), 2007
In this paper, a new computation for gray level co-occurrence matrix (GLCM) is proposed. The aim is to reduce the computation burden of the original GLCM computation. The proposed computation will be based on Haar wavelet transform. Haar wavelet transform is chosen because the resulting wavelet bands are strongly correlated with the orientation ...
Abu Bakar, S.A.R, Mokji, M.M
openaire   +2 more sources

Skin Disease Identification System using Gray Level Co-occurrence Matrix

Proceedings of the 9th International Conference on Computer and Automation Engineering, 2017
Diagnosis of the skin disease has always been in terms of a doctor's knowledgeable opinion, or by number of laboratory screenings. Diagnosis is made by looking for additional signs that make the doctor's statement accurate, however in some cases signs are indistinguishable that results to miss potential diagnosis.
Joseph Mark G. Aglibut, Luigi L. Alonzo, Monica Francesca B. Coching, Jumelyn L. Torres, Noel B. Linsangan   +4 more
openaire   +1 more source

Early detection of melanoma images using gray level co‐occurrence matrix features and machine learning techniques for effective clinical diagnosis

International journal of imaging systems and technology (Print), 2020
Melanoma is an early stage of skin cancer. The objective of the proposed work is to detect the symptoms of melanoma early through images of the moles obtained from image processing device and classify the types.
B. Thiyaneswaran, K. Anguraj, S. Kumarganesh, K. Thangaraj   +3 more
semanticscholar   +1 more source

Classification of Crop Lodging with Gray Level Co-occurrence Matrix

2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 2018
Lodging in agricultural crops is the permanent displacement of a plant from its upright position [2]. It may be caused by several weather and environmental conditions. Harvesting severely lodged crops may take twice as much time and results in reduced yield. Plant breeders seek to identify and select for lodging-resistant varieties.
Sajith Rajapaksa, Mark Eramian, Hema Duddu, Menglu Wang, Steve Shirtliffe, Seungbum Ryu, Anique Josuttes, Ti Zhang, Sally Vail, Curtis Pozniak, Isobel Parkin   +10 more
openaire   +1 more source

Research on Characteristic Properties of Gray Level Co-Occurrence Matrix

Applied Mechanics and Materials, 2012
Gray level co-occurrence matrix (GLCM) is a second-order statistical measurement. In order to understand the characterization degree of GLCM’s different feature properties, we use images of Brodatz texture images as experimental samples, analyze the change process of feature properties in horizontal, vertical and principal and secondary diagonal ...
Ying Chen, Feng Yu Yang
openaire   +1 more source

Solid waste bin level detection using gray level co-occurrence matrix feature extraction approach

Journal of Environmental Management, 2012
This paper presents solid waste bin level detection and classification using gray level co-occurrence matrix (GLCM) feature extraction methods. GLCM parameters, such as displacement, d, quantization, G, and the number of textural features, are investigated to determine the best parameter values of the bin images.
Maher, Arebey, M A, Hannan, R A, Begum, Hassan, Basri   +3 more
openaire   +2 more sources

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

Textural analysis by means of a gray level co-occurrence matrix method. Case: Corrosion in steam piping systems

Materials Today: Proceedings, 2021
Corrosion phenomena are usually difficult to recognize without a deep knowledge of the electrochemical properties of materials, this creates difficulties in the analysis of corrosion in practice, control measures are developed through image processing to
J. Fajardo, César A. Paltán, Luis M. López, E. Carrasquero   +3 more
semanticscholar   +1 more source

3D shape recovery from image focus using gray level co-occurrence matrix

Tenth International Conference on Machine Vision (ICMV 2017), 2018
Recovering a precise and accurate 3-D shape of the target object utilizing robust 3-D shape recovery algorithm is an ultimate objective of computer vision community. Focus measure algorithm plays an important role in this architecture which convert the color values of each pixel of the acquired 2-D image dataset into corresponding focus values.
Mahmood, F., Munir, U., Mehmood, Fahad, Iqbal, J.   +3 more
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Skin Cancer Detection Using Gray Level Co-occurrence Matrix Feature Processing

2020 5th International Conference on Devices, Circuits and Systems (ICDCS), 2020
At present time, skin cancer is becoming common explanation for death in citizenry . Often when body exposed to the daylight , it's going to causes carcinoma it's a abnormal growth of skin cells within the physical body . Generally most of the skin cancers are often cured if they're detected in early of its stage.
Swati Jayade, D. T. Ingole, Manik D. Ingole   +2 more
openaire   +1 more source