Assessment of surface roughness based on super resolution reconstruction algorithm

International Journal of Advanced Manufacturing Technology

Volumn 35, Issue 11-12, 2008, Pages 1191-1205

  Dhanasekar, B ^a   Ramamoorthy, B ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

Author keywords

Fourier transform; GMDH; Machine vision; Super resolution; Surface roughness

Indexed keywords

ALGORITHMS; COMPUTER VISION; FOURIER TRANSFORMS; IMAGE RECONSTRUCTION; IMAGE RESOLUTION; PARAMETER ESTIMATION;

DIGITAL PROCESSED IMAGES; FOURIER TRANSFORM PARAMETERS; MECHANICAL STYLUS; SUPER RESOLUTION;

SURFACE ROUGHNESS;

EID: 38149056451     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-006-0799-5     Document Type: Article

References (21)

1. Kiran M, Ramamoorthy B, Radhakrishnan V (1998) Evaluation of surface roughness by vision system. Int J Mach Tool Manufact 38:685-690
2. Luk F, Hyunh V, North W (1989) Measurement of surface roughness by a machine vision system. J Phys E 22:977-980
3. Al-kindi GA, Baul RM, Gill KF (1992) An application of machine vision in the automated inspection of engineering surfaces. Int J Prod Res 2:241-253
4. Jason DG, Rourke JM, Bell AC (1984) High-speed surface roughness measurement. Transactions of ASME 34(106):34-39
5. Tsai DM, Tseng CF (1999) Surface roughness classification for castings. Pattern Recogn 32:389-405
6. Kartik A, Chandra S, Ramamoorthy B, Das S (1997) 3D tool wear measurement and visualization using stereo imaging. Int J Mach Tool Manufact 37:1573-1581
7. Rajneesh Kumar, Dhanasekar B, Ramamoorthy B (2005) Application of digital image magnification for surface roughness evaluation using machine vision. Int J Mach Tool Manufact 45:228-234
8. Lee BY, Tarng YS (2001) Surface roughness inspection by computer vision in turning operations. Int J Mach Tool Manufact 41:1251-1263
9. Younis MA (1998) On line surface roughness measurements using image processing towards an adaptive control. Comput. Ind. Eng. 35:49-52
10. Vandewalle P, Süsstrunk S, Vetterli M (2004) Double resolution from a set of aliased images. Proc. IS&T/SPIE Electronic Imaging 2004: Sensors and Camera Systems for Scientific, Industrial, and Digital Photography Applications: 5301
11. Irani M, Peleg S (1991) Improving resolution by image registration. CVGIP, Graph Models Image Process 53:231-239
12. Tsai RY, Huang TS (1984) Multiple frame image restoration and registration. Advances in Computer Vision and Image Processing:317-339
13. Park SM, Park MK, Kang MG (2003) Super-Resolution Image Construction: A Technical Overview. IEEE Signal Process Mag
14. Patti AJ, Ibrahim M, Tekalp AM (1997) Super resolution video reconstruction with arbitrary sampling lattices and nonzero aperture time. IEEE Trans Image Process 5:1064-1075
15. Liu S, Jernigan M (1990) Texture analysis and discrimination in additive noise. Comput Vis Graph Image Process 49(1):52-67
16. Ivakhenko AG (1971) Polynomial theory of complex systems. IEEE Trans Syst Man Cyb 1(4):364-378
17. Farlow SJ (1984) The GMDH algorithm, self-organizing methods in modeling. GMDH type algorithms
18. Keren D, Peleg S, Brada R (1988) Image sequence enhancement using sub-pixel displacement. Proceedings IEEE Conference on Computer Vision and Pattern Recognition:742-746
19. Papoulis A (1975) A new algorithm in spectral analysis and band-limited extrapolation. IEEE Trans Circuits Syst 22(9):735-742
20. Marcel B, Briot M, Murrieta R (1997) Calcul de translation et rotation par la transformation de Fourier. Traitement du signal 14:135-149
21. Vandewalle P, Susstrunk S, Vetterli M (2003) Superresolution images reconstructed from aliased images. SPIE/IS & T Visual Communication and Image Processing Conference 5150:1398-1405