Image Texture Feature Extraction Using GLCM Approach

By P. Mohanaiah, P. Sathyanarayana, L. GuruKumar, Dept. of E.C.E NEC-Narasaraopeta Professor, India Nellore. 2013

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State of the Art in Defect Detection Based on Machine Vision (2021, methodology): “It reflects the comprehensive information from the image grey levels regarding the direction, adjacent interval and change amplitude, which can be used to analyze the image primitives and arrangement structure [123–125].”
Classifying urban land use by integrating remote sensing and social media data (2017, unknown): “2006, Mohanaiah et al .”
Utilizing machine learning approaches to improve the prediction of leaf counts and individual leaf segmentation of rosette plant images (2015, methodology): “The texture features are calculated based on the GLCM approach [11].”
Texture Feature Extraction Methods: A Survey (2019, methodology): “Furthermore, the GLCM algorithm is easy to implement and has been shown to give very good results in a large fields of applications (see [25]).”