A means of facilitating the transfer of Optical inspection methods knowledge and skills from academic institutions and their research partners into Panama optics and optical research groups is described. The process involves the creation of an Integrated Knowledge Group Research (IKGR), a partnership led by Polytechnic University of Panama with the support of the SENACYT and Optics and Optometry Department, Polytechnic University of Catalonia. This paper describes the development of the Project for knowledge transfer “Implementation of a method of optical inspection of low cost for improving the surface quality of rolled material of metallic and nonmetallic industrial use”, this project will develop a method for measuring the surface quality using texture analysis speckle pattern formed on the surface to be characterized. The project is designed to address the shortage of key skills in the field of precision engineering for optical applications. The main issues encountered during the development of the knowledge transfer teaching and learning are discussed, and the outcomes from the first four months of knowledge transfer activities are described. In overall summary, the results demonstrate how the Integrated Knowledge Group Research and new approach to knowledge transfer has been effective in addressing the engineering skills gap in precision optics for manufactured industrial sector.
We present a new method of measure of the roughness based on the analysis of the texture of speckle pattern on the surface. Images of speckle pattern over the surface are captured by means of a simple configuration using a laser, beam expander, and a camera charge coupled device (CCD). Using the properties of the normalized covariance function that we obtained from the image of the speckle through the inverse Fourier transform, we relate the values of the normalized covariance function. We compare the results obtained with a confocal microscope and co-occurrence matrices method. This method can be considered as a noncontact surface profiling method that is easy to implement and can be used during the manufacturing process.
We present a new method of measure of the roughness based on the analysis of the texture of speckle pattern on the
surface. Images of speckle pattern over the surface are captured by means of a simple configuration using a laser,
beam expander, and a camera charge coupled device (CCD). Using the properties of the normalized covariance
function that we obtain from the image of the speckle through the inverse Fourier transform, we relate the values of
the normalized covariance function. We compare the results obtained with the results obtained with a confocal
microscope. This method can be considered as a noncontact surface profiling method and is easy to implement and
can be used during the manufacturing process.
We present a method of measure of the roughness of the paper based on the analysis of a speckle pattern on the surface. Images of speckle over the surface of paper are captured by means of a simple configuration using a laser, beam expander, and a camera charge-coupled device (CCD). Then we use the normalized covariance function of the fields, leaving the surface to find the roughness. We compare the results obtained with the results obtained with a confocal microscope and the Bendtsen method that is a standard of the paper industry. This method can be considered as a noncontact surface profiling method that can be used online.
Roughness of paper surface is an important parameter in paper manufacturing. Surface roughness measurement is one of
the central measurement problems in paper industry. Surfaces are often coated and the amount of coating and method of
application used depends on the roughness of the base paper [1], [2]. At the moment, air leak methods are standardized
and employed in paper industry as roughness rating methods. Air leak rate between measured paper surface and a
specified flat land is recorded by using specialized pneumatic devices under laboratory conditions. Such a measurement
closely corresponds to the roughness of a surface, the greater the air leak the rougher the surface. Air leak methods are
rather easy to apply to paper and give stable results, although they measure roughness indirectly, need laboratory
conditions, and thus unsuitable for on-line use. To measure real topography of paper surface, it is scanned with
mechanical or optical profilometers. These methods provide accurate information on surface topography, but also
demand laboratory conditions.
In our work, present a method of measure based in the analysis of the texture of speckle pattern on the surface. The
image formed by speckle in the paper surface is considered as a texture, and therefore texture analysis methods are
suitable for the characterization of paper surface. The results are contrasted to air leak methods, optical profilometers
(confocal microscopy), and fringe projection.
Roughness of a paper surface is particularly important in paper and board destined to be printed. Surfaces are often
coated and the amount of coating and method of application used depends on the roughness of the base paper. We
present a method of measure of the roughness of the paper based in the analysis of speckle pattern on the surface. Images
are captured by means of a simple configuration using a laser and a camera CCD. Then, we apply digital image
processing using the co-occurrence matrix, so this method can be considered as a non-contact surface profiling method,
that can be used online.
A device has been designed for off-line optical paper inspection and quality control of stripes and holes in the cigarette paper. Hardware description is first presented including main paper characteristics to be measured. Typical paper stripe and holes structures are then discussed with image processing and analysis considerations to discriminate these structures, focusing in the problems derived from the small area of holes and of their internal structure that is analyzed with a confocal microscope. Algorithms for image processing and analysis are described. These algorithms involve equalization, binarization, stripes structure detection, holes distribution and statistics.
A device has been designed based on the diffraction that will permit to analyze in an objective and quick form, the quality of ophthalmic lenses. This device situated in the line of production will improve the process of fabrication.
The device is based on the phenomenon of the diffraction that takes place in the defects when impacting the light of the laser. The device consists of an optical system, in charge of driving the light of the laser, under good conditions, on the lens to analyze, a sensor, adapted to the wavelength of the laser, that detects the presence of the defect through the produced diffraction and a mechanism in which the lens to inspect is located assures that the laser sweeps the whole surface of the lens. A control system connected to the previous systems regulates the whole process
The image obtained can be used to analyze and characterize the type of defect. Using image processing we segment the images in order to classify the defects that appear in the surface of the lens.
The traditional paper surface characterisation methods, for example based on air-stream leakage (Bendtsen, Parker print surf), are facing severe limitations. These traditional methods are better suited as indicators of erroneous production than for grading paper samples with respect to his print quality potential. It has been acknowledged that this research problem cannot be addressed without taking the papers three-dimensional structure into account. In this work, we will use a confocal image of the surface of the paper, obtained by imaging either a pinhole or a structured light pattern by a very high numerical aperture optical system on the surface of paper to be measured.
In order to analyse the 3D image of the paper we perform a multiresolution analysis. This means that a given signal is decomposed at a coarse approximation plus added details. Applying the successive approximations recursively makes the approximation error go to zero. Using multiresolution analysis and orthonormal wavelet bases, we can construct an algorithm using wavelets. That will allow us to characterise the surface of the paper and grading paper samples with respect to his print quality potential.
The paper formation is one of the most important properties of the paper but remains a difficult property to determine. A method for determining this property has been developed. This method based on light transmission image analysis uses the power spectra of the Fourier transform to analyze the floc distribution. The method has been tested for various furnishes and allows a well discrimination between different qualities of formation that does the standard formation number.
Gabor functions, which localize information in both the spatial and the frequency domains, are used as filters for the inspection of common local defects in textile webs. A variety of defects are analyzed in different fabrics and in every case the flaws are finally segmented from the background.
A novel optical system to check human depth perception is presented. The system uses optotypes generated by holographic methods. This system allows to test depth perception in closer conditions to habitual life.
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