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Using laser speckle to measure the roughness of paper
Abstract
Paper surface roughness is an important consideration in paper and board destined for printing. The amount of coating and method of application depend on the roughness of the base paper. We present a method to measure the roughness of the paper based on analysis of speckle pattern on the surface. Images are captured by means of a simple configuration using a laser and a charge-coupled device (CCD) camera. Then, we apply digital image processing using a co-occurrence matrix, providing for a noncontact surface profiling method that can be used online.
... That is why we propose that optical inspection methods, technology enable the use of non-invasive, i.e., not through contact with the surface is completely clean and samples depending on its constitution can be reused [3], [4], [6], [8], [14], and [15]. Since 2009, I have been conducting research in the field of optical metrology and image processing, developing a model for the evaluation of surface roughness in the paper industry, based on texture analysis using co-occurrence matrix of gray levels [23], [24], [25], [26] industrial sectors. Wherefore are plans to extend the field of application to other materials, laminates specifically metallic and nonmetallic used in Panamenian Industry. ...
... This project will use image processing techniques with second-order statistics, specifically the technique based on the cooccurrence matrix of gray levels (GLCM) [5], [12], [13], [17], [23], [24], [25], [26] ARMA (autoregressive movingaverage), Compressive Sensing [20], [21], [22]. Involves removing four GLCM textural descriptors capture a single image of the speckle pattern developed using the subjective speckle, i.e. speckle formation by an optical system [1], [2], [10], [11], [16]. ...
... Involves removing four GLCM textural descriptors capture a single image of the speckle pattern developed using the subjective speckle, i.e. speckle formation by an optical system [1], [2], [10], [11], [16]. With this setup you get the right size speckle pattern and to analyze the influence of: To establish an objective comparison between different texture descriptors examined with optical methods used, were considered and measures used confocal microscopy method as our yardstick, which were taken as the dependent variable the simple linear regression model adopted for the comparison and validation of our proposed method and developed [20], [21], [22], [23], [24], [25], [26]. The coefficient of determination " 2 R " was the measure chosen to evaluate the fit of each method. ...
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.
... By roughness of the paper substrate, the degree of unevenness or irregularity over the surface is meant. The analysis is relatively easy to apply and give stable results, but does not make a roughness measurement, gives rather an idea about it in an indirect fashion [38]. For the measurement, the test piece is first clamped between a flat glass plate and a circular metal ring, the ring is pressed onto the paper surface, and the air leak between the ring and the paper or paper-based substrate is detected in unit time, so that a qualitative result about the roughness is achieved [39,40]. ...
... For the measurement, the test piece is first clamped between a flat glass plate and a circular metal ring, the ring is pressed onto the paper surface, and the air leak between the ring and the paper or paper-based substrate is detected in unit time, so that a qualitative result about the roughness is achieved [39,40]. The greater the air leak, the rougher the surface [38]. Cobb tests are used to calculate the mass of water absorbed by one square meter of paper (based) sample at a given time and is a well known measure for water barrier properties of paper and paper based materials. ...
Hybrid paper sheets were prepared by applying a thin coating layer of cross-linked polydimethylsiloxane (PDMS) and inorganic particles onto Whatman Grade 1 filter paper substrates. Several coatings with different inorganic particle contents and types were applied onto the paper substrates to investigate the effect of the variation in the coating formulation on the (i) wetting, (ii) water barrier properties, (iii) air barrier properties, (iv) surface roughness, and (v) mechanical properties of the samples. It was revealed that the superhydrophobic hybrid paper sheets with significantly low air permeability and high water barrier properties could be prepared which is an indication that the method proposed can be used for the preparation of packaging materials.
... In the paper industry, inspecting paper surfaces is essential since the topographic variations in the paper surface are closely related to the consumption of ink, printing resolution, and printability (Abdiel Pino et al., 2011). Thus, accurate quality control of the paper surface is required in order to minimize unnecessary production expenses. ...
Anomaly detection of three-dimensional (3D) topographic data is a challenging problem in spatial data analysis. In this paper, we investigate spatial patterns of 3D surface data that exhibit multiple in-control modes. In complex manufacturing processes, surfaces of final products could contain different topographic features from one in-control surface to another, thus making it difficult to monitor the surface with existing approaches, which rely on the assumption of the presence of single mode surface topography. We propose a novel anomaly detection approach for monitoring local topographic variations in the presence of multimode surface topography. We present a binarization model to capture the generic behavior of the multimode surfaces and enhance the representation of the surface. To systematically monitor the surface, we introduce a new probabilistic distance measure (PDM) that quantifies the similarity of spatial patterns between two binarized surfaces. The proposed PDM takes advantage of identifying local variations by utilizing the order neighbor statistics, which captures the local property on the surface. Experimental results with numerical simulation data and real-life paper surface data are provided to demonstrate the effectiveness of the proposed approach.
... 20], it is possible to compute the heat transferred from the upper side to the lower side. t l was calculated by adding the measured roughness of the substrate from upper (1685 mL/min) and lower side (1165 mL/min), and interpolating the result into length units according to (34), which resulted in 14 µm. λ l was calculated as the average value of the thermal conductivity of the substrate (0.05 W/m@K) and the thermal conductivity of the air (λ air ). ...
SUMMARY A numerical model based on the finite element method has been constructed to simulate the ignition propensity (IP) tests. The objective of this mathematical model was to quantify the influence of different characteristics of the cellulosic substrate on the results of the IP-tests. The creation and validation of the model included the following steps: (I) formulation of the model based on experimental thermodynamic characteristics of the cellulosic substrate; (ii) calibration of the model according to cone calorimeter tests; (iii) validation of the model through mass loss and temperature profiling during IP-testing. Once the model was validated, the influence of each isolated parameter of the cellulosic substrate was quantified via a parametric study. The results revealed that the substrate heat capacity, the cigarette temperature and the pyrolysis activation energy are the most influencing parameters on the thermodynamic response of the substrates, while other parameters like heat of the pyrolysis reaction, density and roughness of the substrate showed little influence. Also the results indicated that the thermodynamic mechanisms involved in the pyrolysis and combustion of the cellulosic substrate are complex and show low repeatability which might impair the reliability of the IP-tests.
... Speckle pattern illumination methods are convenient to determine roughness in the submicrometer range but require an optical illumination system consisting of a diffuser and a lens. Speckle pattern texture analysis method allows obtaining information about surface roughness directly from speckle pattern texture images using texture analysis [5]. Information extraction from the texture image can be obtained by the gray-level co-occurrence matrix (GLCM) method which based on second-order statistics. ...
Speckle pattern texture analysis method is applied to measure surface roughness of human skin. The method is based on analyzing of a gray level co-occurrence matrix occurred from a speckle image of a rough surface. Paper with different surface roughness is used as a skin phantom. The roughness is controlled by profilometry measurements. The developed methodology could find wide application in dermatology and tissue diagnostics.
The recent development of optical measuring instruments has increased the use of surface topographic data for monitoring the quality of the engineered surface. Due to the complexities of modern industrial processes, however, surfaces of final products under the normal manufacturing process may have multiple modes, such that the surface consists of different topographic features from one in-control mode to another. In this case, existing monitoring approaches based on the single mode surface cannot characterise normal surfaces with multiple modes, and result in poor detection performance. In this article, a new approach for monitoring variations in multimode surface topography is presented. We propose a multimode surface prediction model, which characterises the generic behaviour of normal surfaces with multiple in-control modes. Moreover, we present a mode-specific surface monitoring approach that identifies topographic variations on the surfaces based on the similarity between probability density function (PDF) of residuals from observed and normal surfaces obtained through the prediction model. A novel probabilistic distance measure is introduced to effectively measure the similarity between a single residual PDF and a set of residual PDFs under the same mode. The effectiveness of the proposed approach is demonstrated through numerical simulation and real-life application of paper surface monitoring.
We present a novel method capable of measuring surface roughness of deposited thin films. The method was tested with 4 sets of SiN thin films deposited using a plasma-enhanced chemical vapor deposition system. The range of surface roughness measured over 3 sets of data with atomic force microscopy (AFM) was between 0.13 and 1.66 nm. The remaining one data set had a greater roughness range of 1.63–5.43 nm. The roughness calculated with an algorithm demonstrated a strong correlation with AFM measurement in all the comparisons. This was attributed to the formation of spatial height differences between positive light matter (particles) and negative surface plasmon carriers both comprising a speckle pattern. This indicates that the proposed method can effectively characterize surface roughness tendency with the accuracy comparable to AFM.
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 to measure the roughness of paper based on the analysis of speckle contrast 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, so this method can be considered as a non-contact surface profiling method that can be used online.
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.
The theory of speckle in partially coherent, monochromatic light is extended to cover the entire range of object roughness. For “almost white-noise” objects it is shown how the speckle statistics are related to a Gaussian approximation of the object statistics. Within this approximation, general relations are derived for the spatial speckle correlation and the spatial Wiener spectrum. The theory is applied to calculate rms speckle contrast as function of object roughness, coherence of the illumination, and receiver plane defocusing.
This paper describes a new non-contact measurement approach in characterizing manufactured surfaces. Computer vision is applied to capture digital images of three types of anisotropic steel specimen surfaces from shaping, grinding, and polishing processes. Multiresolution wavelet decomposition is used to obtain signatures of surface profiles from the digital images. Relationships between these signatures and surface roughness parameters (Ra and Rq) are built by response surface methodology (RSM). The proposed models thus developed are suitable for predicting roughness in terms of the roughness parameters. Experimental results show that the proposed approach successfully correlates wavelet signals to Ra and Rq values. In addition, they also show repeatable gage capabilities. The proposed method is a good candidate for on-line, real-time surface roughness inspection when specimens of known surface roughness are available.
In a previous article we have shown that the two speckle patterns produced from the same rough surface illuminated by two coherent plane waves under two different angles of incidence are correlated. The correlation depends on the surface roughness. In this paper a method is described where the rough surface is illuminated simultaneously by the two plane waves. The ensemble-averaged coherence function, that is, the correlation function, of the scattered field is measured by using a two-waves interferometer. This affords a real-time measurement of the surface roughness in the range of large roughness (σ > λ). The theoretical calculations have been performed for a normally distributed surface. The experimental results are in good agreement with theory. We describe the optical arrangement of an instrument based on this principle.
As a practical monitoring tool for measurements of surface roughness properties, a new instrument is actually constructed on the basis of using the average contrast of image speckle patterns. With this instrument an experimental investigation on the contrast variation of image speckle patterns is conducted systematically for various surface roughnesses of the objects under different conditions of an optical imaging system. It is found that the roughness and correlation length of the objects can be precisely determined from the experimental curve of the contrast variation versus the point spread of the imaging system. The present method using image speckle patterns is superior to the previous one which uses the contrast variation of speckle patterns in the diffraction field.
The properties of a speckle pattern are determined by the light source, the rough surface, and the optical system. The degree of correlation of the intensities of two slightly different speckle patterns can be applied to measure surface roughness since it depends on the variance of the surface height distribution. The two speckle patterns are produced by illuminating a rough surface with coherent light of either two different wavelengths or two different angles of incidence. A unified description of the theory for the spectral and angular speckle-correlation methods is presented, and explicit solutions are derived for both far-field and image-plane geometries. The theoretical results essentially yield a factorization of the degree of speckle correlation into a roughness-dependent and a space-dependent part. By maximizing the space-dependent part, one obtains the requirements for experimental arrangements with optimal measuring conditions. Examples of possible setups for each method are presented, and cross references to earlier work published in this field are given.
The Handbook of Surface and Nanometrology explains and challenges current concepts in nanotechnology. It covers in great detail surface metrology and nanometrology and more importantly the areas where they overlap, thereby providing a quantitative means of controlling and predicting processes and performance. Trends and mechanisms are explained with numerous practical examples. Bringing engineering and physics together at the nanoscale reveals some astonishing effects: geometric features such as shape change meaning; roughness can disappear altogether; signals from instruments have to be dealt with differently depending on scale. These and other aspects are dealt with for the first time in this book. It is relevant not only for today's technology but also for future advances. Many aspects of nanotechnology and precision engineering are considered in chapters on manufacture, characterization, standardization, performance and instrumentation. There is a special chapter on nanometrology and this subject permeates the whole book. The Handbook of Surface and Nanometrology is the only book that covers these subject areas and is the definitive work in this field. This book is indispensable for firms making, trading, and researching semiconductor devices, MEMS, and micro-optics, as well as tradition precision engineering products. It will also be useful in quality control as well as for research scientists, development engineers, and production managers.
A new method for measuring the roughness of paper will be described. This method provides information about the spatial variation of surface non-uniformity, and so is far more informative than the traditional air-leak methods. It can be applied to a very wide range of paper types, even specialty papers with laid lines or other imposed structure in the surface. A number of studies done with a prototype instrument will be reported. In one study, a range of paper types (from photo-quality inkJet paper to sack kraft) was used to confirm the dynamic range of the instrument, determine reproducibility of the technique, and to make comparisons with air-leak methods. In another study, power spectrum analysis of the roughness data was used to benchmark the surface structure of a number of different papers and paper types.
The use of light scattering or diffraction for the determination of the surface roughness of machined metal components has been investigated by many researchers. As a result, a number of theoretical formulations relating the r.m.s. height R to the scattered light intensity distribution have been derived for periodic and random surfaces. Experimental results for rougher surfaces have been reported and from them the individual researchers have derived empirical relationships between the standard deviation of the angularly scattered light distribution and the r.m.s. surface slopes. Each of these relationships are claimed to be valid for a certain class of surfaces. As a result of this, commercial optical surface finish sensors, based upon light scattering have been produced. The manufacturers of these instruments have defined some new surface finish parameters like Sn and RQp, thereby contributing to the so-called “parameter rash”. Based upon scalar diffraction theory, formal relationships are derived, between a The specular reflectance and the r.m.s. height parameter R, and b The standard deviation of the scattered light distributionqand the r.m.s. slope parameter ∆q.
We report speckle contrast measurements taken at the centre of the far-field diffraction pattern of weak, medium and strong diffusers illuminated by a focused laser beam. We study the evolution of curves of speckle contrast as a function of the radius of the laser spot as the variance of surface height is steadily increased for a fixed correlation length. We also present experimental curves of speckle contrast as a function of the distance of the rough surface from the beam focus for three of the diffusers.
Conventional measurement of finish using stylus instruments has been in vogue for over half a century. Though these instruments have excellent capabilities and wide range, they are normally used for inspecting machined surfaces of good finish. Further the procedure is a post process approach which is not amenable for automation. In the recent past, higher levels of automation in the shop floor has focused the attention on the application of fast, reliable and cost effective procedures for evaluating surfaces of medium finished parts.This paper deals with the possibility of doing this using a vision system. It briefly reviews a few approaches and examines one — texture unit spectra — in more detail.