Classification and correlation of surface roughness in metallic parts using texture descriptors

Annals of DAAAM and Proceedings of the International DAAAM Symposium

Volumn , Issue , 2009, Pages 1293-1294

  Suarez, Sir ^a   Alegre, Enrique ^a   Barreiro, Joaquin ^a   Morala Arguello, Patricia ^a   Gonzalez Castro, Victor ^a  

^a NONE

Author keywords

Co occurrence matrix; Laws; Roughness; Surface texture

Indexed keywords

COMPUTER VISION; DISCRIMINANT ANALYSIS; MANUFACTURE; NEURAL NETWORKS; SURFACE ROUGHNESS; TEXTURES;

ARTIFICIAL VISION SYSTEM; CO-OCCURRENCE-MATRIX; LAWS; MACHINING PROCESS; QUADRATIC DISCRIMINANT ANALYSIS; SURFACE TEXTURES; TEXTURE ANALYSIS METHOD; TEXTURE DESCRIPTORS;

ENGINEERING EDUCATION;

EID: 84867571895     PISSN: 17269679     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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3. Al-Kindi, G & Shirinzadeh, B. (2009). Feasibility assessment of vision-based surface roughness parameters acquisition for different types of machined specimens. Image Vision Comput, Vol. 7, No. 4, pp 444-458
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5. Haralick, R.M. (1978). Statistical and Structural Approaches to Texture. Proceedings of the IEEE 67, No 5. pp 786-804
6. Laws, K. (1980) Rapid texture identification. In SPIE Vol. 238 Image Processing for Missile Guidance, pp 376-380
7. Persson, U. (2006).Surface roughness measurement on machined surfaces using angular speckle correlation. J. of Materials Processing Technology, Vol. 180, pp 233-238
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