Autocorrelation function of the sum of two spectrally decorrelated laser speckle fields: comparison of Fresnel and Fraunhofer approximation

2003 ◽  
Author(s):  
Dominik Prazak ◽  
Miloslav Ohlidal
1983 ◽  
Vol 15 (6) ◽  
pp. 507-512 ◽  
Author(s):  
N. Nagamatsu ◽  
K. Nakagawa ◽  
T. Asakura ◽  
K. Morishita

2011 ◽  
Vol 189-193 ◽  
pp. 680-683 ◽  
Author(s):  
Zong Heng Yuan ◽  
Yan Hua Zhang ◽  
Jian Wei Zhang ◽  
Ye Fan Ge

Applying autocorrelation method to process laser speckle patterns, the relation between surface roughness and speckle elongation and correlation length of autocorrelation function can be obtained, and the measured surface roughness can be achieved based on this relation. One-dimension autocorrelation and two-dimension autocorrelation function are used, Moreover, surface roughness is evaluated by speckle elongation and correlation length of autocorrelation function. Aspect ratio of speckle granular represents speckle elongation ratio, which eliminates effects of speckle granular average size on measurement results compared to other methods using before. It has high reliability and efficiency in surface roughness measurement evaluation.


Author(s):  
P. Fraundorf ◽  
B. Armbruster

Optical interferometry, confocal light microscopy, stereopair scanning electron microscopy, scanning tunneling microscopy, and scanning force microscopy, can produce topographic images of surfaces on size scales reaching from centimeters to Angstroms. Second moment (height variance) statistics of surface topography can be very helpful in quantifying “visually suggested” differences from one surface to the next. The two most common methods for displaying this information are the Fourier power spectrum and its direct space transform, the autocorrelation function or interferogram. Unfortunately, for a surface exhibiting lateral structure over several orders of magnitude in size, both the power spectrum and the autocorrelation function will find most of the information they contain pressed into the plot’s origin. This suggests that we plot power in units of LOG(frequency)≡-LOG(period), but rather than add this logarithmic constraint as another element of abstraction to the analysis of power spectra, we further recommend a shift in paradigm.


ALQALAM ◽  
2015 ◽  
Vol 32 (2) ◽  
pp. 284
Author(s):  
Muhammad Subali ◽  
Miftah Andriansyah ◽  
Christanto Sinambela

This article aims to look at the similarities and differences in the fundamental frequency and formant frequencies using the autocorrelation function and LPCfunction in GUI MATLAB 2012b on sound hijaiyah letters for adult male speaker beginner and expert based on makhraj pronunciation and both of speaker will be analysis on matching distance of the sound use DTW method on cepstrum. Subject for speech beginner makhraj pronunciation are taken from college student of Universitas Gunadarma and SITC aged 22 years old Data of the speech beginner makhraj pronunciation is recorded using MATLAB algorithm on GUI Subject for speech expert makhraj pronunciation are taken from previous research. They are 20-30 years old from the time of taking data. The sound will be extracted to get the value of the fundamental frequency and formant frequency. After getting both frequencies, it will be obtained analysis of the similarities and differences in the fundamental frequency and formant frequencies of speech beginner and expert and it will shows matching distance of both speech. The result is all of speech beginner and expert based on makhraj pronunciation have different values of fundamental frequency and formant frequency. Then the results of the analysis matching distance using method DTW showed that obtained in the range of 28.9746 to 136.4 between speech beginner and expert based on makhraj pronunciation. Keywords: fundamental frequency, formant frequency, hijaiyah letters, makhraj


1986 ◽  
Vol 6 (3) ◽  
pp. 335-338
Author(s):  
Hitoshi Fujii ◽  
Toshimitsu Asakura ◽  
Yasuhiro Harada ◽  
Kunihiko Nohira ◽  
Yoshihisa Shintomi ◽  
...  

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