Texture feature extraction using gray level gradient based co-occurence matrices

By S. Lam. 1996

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Haohan Wang
2. Eric P. Xing
3. Zachary Chase Lipton
4. Zexue He
5. Ivan Popov
6. Ivan N. Jordanov
7. Apostolos Chondronasios
8. Mohit Bansal

Citations in the corpus

• Learning Robust Representations by Projecting Superficial Statistics Out (2018, methodology): “We consulted some classic computer vision techniques for inspiration and extensive experimental evidence (Appendix A1), suggested that gray-level co-occurrence matrix (GLCM) (Haralick et al., 1973; Lam, 1996) may suit our goal.”
• Feature selection for surface defect classification of extruded aluminum profiles (2016, background): “GLGCM i belongs to the gray-level image and j belongs to the gradient [27].”