Study of the surface roughness in metals with different surface finishing by two-dimensional correlation of laser speckle pattern

2004 ◽  
Author(s):  
Miguel Asmad ◽  
Guillermo Baldwin-Olguin ◽  
C. Maczeyzik ◽  
Fernando Mendoza Santoyo ◽  
Carlos Perez-Lopez
Keyword(s):  
Surface Roughness ◽  
Speckle Pattern ◽  
Laser Speckle ◽  
Surface Finishing ◽  
Two Dimensional

Experimental study of the surface roughness in metals with different surface finishing by two-dimensional correlation of speckle pattern

2005 ◽  
Author(s):  
Miguel Asmad ◽  
Guillermo Baldwin ◽  
Cordula Maczeyzik ◽  
Fernando Mendoza ◽  
Carlos Perez-Lopez
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Speckle Pattern ◽  
Surface Finishing ◽  
Two Dimensional

scholarly journals Different methods for characterizing surface roughness using laser speckle technique

2019 ◽  
Vol 12 (23) ◽  
pp. 21-29
Author(s):  
Mayada B. Al-Quzweny
Keyword(s):  
Surface Roughness ◽  
Speckle Pattern ◽  
Point Of View ◽  
Laser Speckle ◽  
Image Texture ◽  
Object Surface ◽  
Image Texture Analysis ◽  
Measuring Surface ◽  
Wide Range

In this work, results from an optical technique (laser speckle technique) for measuring surface roughness was done by using statistical properties of speckle pattern from the point of view of computer image texture analysis. Four calibration relationships were used to cover wide range of measurement with the same laser speckle technique. The first one is based on intensity contrast of the speckle, the second is based on analysis of speckle binary image,  the third is on size of speckle pattern spot, and the latest one is based on characterization of the energy feature of the gray level co-occurrence matrices for the speckle pattern. By these calibration relationships surface roughness of an object surface can be evaluated within these relations ranges from single speckle pattern image which was taken from the surface.

Characteristics of Laser Speckle Measurement of Tooth Roughness

2004 ◽  
Vol 261-263 ◽  
pp. 1581-1586 ◽  
Author(s):  
M. Uchino ◽  
W. Fujisaki ◽  
E. Kurihara ◽  
K. Matsuda ◽  
Toshihiko Koseki
Keyword(s):  
Surface Roughness ◽  
Evaluation Method ◽  
Speckle Pattern ◽  
Laser Speckle ◽  
Measuring System ◽  
Tooth Surface ◽  
Dental Clinics ◽  
Test Pieces ◽  
Tooth Surfaces ◽  
Dental Diseases

This study is concerned with the fundamental characteristics of a new nondestructive measuring technique of the tooth roughness with precisely. In the dental clinics, the estimation of roughness of tooth surfaces with a hand explorer is one of the important tests for the finishing the crown re-shaping and resin fillings. If the tooth surface is rough enough to hold dental plaque, it occasio-nally causes dental diseases around it. Therefore, it is important to measure the roughness of the tooth surfaces for the prevention of furthermore distraction of the tooth. Laser speckle measurement is used as an evaluation method for objectively measuring the surface roughness with non-contact. In this study, a laser speckle measurement system for measuring the surface roughness is constructed. Comparison measurement is carried out for the tooth pieces with the various unidirectional roughness and the metallic test pieces with the standard roughness. The experimental results using the actual measuring system show some important points as follows. Firstly, there is a good correla-tion between the laser speckle pattern and the tooth roughness as well as that of the metallic test pieces. Secondly, the reflection from the tooth shows a different tendency in comparison with the reflection from the metallic test pieces.

Research on Non-Planar Roughness Based on Laser Speckle

2012 ◽  
Vol 529 ◽  
pp. 413-418
Author(s):  
Wen Tao Zhang ◽  
Chuan Yang ◽  
Bao Wu Zhang ◽  
Xian Ming Xiong
Keyword(s):  
Surface Roughness ◽  
Speckle Pattern ◽  
Wiener Filter ◽  
Texture Feature ◽  
Characteristic Parameter ◽  
Laser Speckle ◽  
Metal Sample ◽  
Energy Entropy ◽  
Texture Characteristics ◽  
Before And After

Relationship between texture characteristics of laser speckle pattern and surface roughness of turning machinery metal surface was studied in this paper. Based on Wiener filter image processing technology, curve relationship between four texture feature parameters such as energy, entropy, contrast as well as correlation and roughness Ra before and after filtering was also established. Integrated texture feature method was used to analyze the change of each characteristic parameter and roughness Ra and obtain a relatively good curve. The results show that when roughness Ra is in the range of 0.8-6.3μm, energy, entropy and correlation are most suitable to represent surface roughness of turning machinery metal sample.

Surface Roughness Extraction by Gibbs Random Fields of Laser Speckle Pattern Texture

2012 ◽  
Vol 629 ◽  
pp. 515-520
Author(s):  
Lei Yang ◽  
Rong Sheng Lu ◽  
Zhi Jian Liu ◽  
Li Qiao Lei
Keyword(s):  
Surface Roughness ◽  
Texture Analysis ◽  
Diode Laser ◽  
Random Fields ◽  
Speckle Pattern ◽  
Digital Camera ◽  
Texture Features ◽  
Laser Speckle ◽  
Speckle Patterns ◽  
Gibbs Random Fields

Based on computer texture analysis methods, the relationships between laser speckle texture features of grinding surfaces and surface roughness are investigated. The laser speckle texture pictures of different surface roughness are acquired by a simple equipment which consists of a digital camera and a diode laser. The texture method based on Gibbs Random Fields model is used to analyze laser speckle patterns. Gibbs texture features with the second-order neighborhood are extracted. The experiment results display that the surface roughness information included in the laser speckle texture pictures is monotonous withβ2~β5 Gibbs texture features. For comparing, normalized texture features has been done. This method can extract object’s surface roughness information which is the same material and machined by the same method through calibrating beforehand.

scholarly journals Evaluation of surface roughness of a machined metal surface based on laser speckle pattern

2018 ◽  
Vol 2018 (9) ◽  
pp. 773-778
Author(s):  
Dong Xu ◽  
Quan Yang ◽  
Feng Dong ◽  
Sridhar Krishnaswamy
Keyword(s):  
Surface Roughness ◽  
Metal Surface ◽  
Speckle Pattern ◽  
Laser Speckle
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