23 research outputs found

    Survey on Image intensification using Canny Edge Technique

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    Image Processing is generally done in form of Signal Processing. In this images, pictures, video frame etc are given in Input form and the Output appears with certain set of features or parameters in relation to the input given. Edge Detection using Canny Technique is an set of Mathematical Functions whose main goal is to detect points in the Digital input i.e. image and detect how brightness changes variably , and where are discontinuities. Edge detection is an essential stage in processing the image. Mostly image-processing techniques consider the image as a two-dimensional signal then put standard signal-processing techniques to it. Generally it means Digital Image being processed but analog and digital signals can also be processed

    COMPUTATIONALLY EFFECTIVE NUMERICAL SIMULATION METHOD FOR DIFFRACTION-BLURRED IMAGES OF OBJECTS WITH PIECEWISE-LINEAR EDGE CONTOUR

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    ubject of Research. The paper presents research of numerical image simulation for objects with known edge contour, considering optical diffraction blur and image sensor spatial sampling. Computationally effective solution is proposed under restriction of edge contour approximation by a set of straight lines.Method. Proposed method is based on the analytical numerical computation of the Fourier transform for the object bounding polygon. Calculus bandwidthis defined by the optical system diffraction limit and spatial frequency response of the object and background textures.Main Result. Proposed technical solution results in 2-3 order less computation time compared to a subpixel image simulation in spatial domain with subpixel sampling step value of 10-2 pixel.Computational complexity of the proposed approach is invariant with respect to a subpixel accuracy of simulated object geometry representation.Practical Relevance. Proposedapproach may be applied to a solution of inverse problems in the field of optical geometrical measurements and to a study of image processing algorithms with geometrical parameters representation error on the order of 10-1-10-4 pixel

    Quantifying ultrasonic deformation of cell membranes with ultra-high-speed imaging

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    We present a new method for controllable loading of cell models in an ultrasonic (20 kHz) regime. The protocol is based on the inertial-based ultrasonic shaking test and allows to deform cells in the range of few mm/m to help understand potential consequences of repeated loading characteristic of ultrasonic cutting

    Accurate characterisation of hole geometries by fringe projection profilometry

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    Accurate localisation and characterisation of holes is often required in the field of automated assembly and quality control. Compared to time consuming coordinate measuring machines (CMM), fringe-projection-based 3D scanners offer an attractive alternative as a fast, non-contact measurement technique that provides a dense 3D point cloud of a large sample in a few seconds. However, as we show in this paper, measurement artefacts occur at such hole edges, which can introduce errors in the estimated hole diameter by well over 0.25 mm, even though the estimated hole centre locations are largely unaffected. A compensation technique to suppress these measurement artefacts has been developed, by modelling the artefact using data extrapolated from neighboring pixels. By further incorporating a sub-pixel edge detection technique, we have been able to reduce the root mean square (RMS) diameter errors by up to 9.3 times using the proposed combined method

    Reduction of systematic errors in structured light metrology at discontinuities in surface reflectivity

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    In measuring 3D shape with structured light techniques, systematic errors arise in the neighbourhood of discontinuities in reflectivity or geometry. A mechanism for this phenomenon is proposed, based on the finite size of the imaging system’s point spread function. A theoretical analysis for the phase errors in a phase-shifting projected fringe system is given, from which a correction algorithm to minimise the systematic errors is presented. In this algorithm, a closed form expression for the errors based on the intensity values and the phase values in a neighbourhood excluding the affected region is used to remove the estimated error from the measured phase values within the affected region. Experiments on samples with both linear and circular discontinuities in reflectivity demonstrated respective reductions in systematic errors by factors of 2.5× and 3×

    Accurate characterisation of hole geometries by fringe projection profilometry

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    Copyright 2017 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.Accurate localisation and characterisation of holes is often required in the field of automated assembly and quality control. Compared to time consuming coordinate measuring machines (CMM), fringe-projection-based 3D scanners offer an attractive alternative as a fast, non-contact measurement technique that provides a dense 3D point cloud of a large sample in a few seconds. However, as we show in this paper, measurement artefacts occur at such hole edges, which can introduce errors in the estimated hole diameter by well over 0.25 mm, even though the estimated hole centre locations are largely unaffected. A compensation technique to suppress these measurement artefacts has been developed, by modelling the artefact using data extrapolated from neighboring pixels. By further incorporating a sub-pixel edge detection technique, we have been able to reduce the root mean square (RMS) diameter errors by up to 9.3 times using the proposed combined method

    Single yeast cell nanomotions correlate with cellular activity.

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    Living single yeast cells show a specific cellular motion at the nanometer scale with a magnitude that is proportional to the cellular activity of the cell. We characterized this cellular nanomotion pattern of nonattached single yeast cells using classical optical microscopy. The distribution of the cellular displacements over a short time period is distinct from random motion. The range and shape of such nanomotion displacement distributions change substantially according to the metabolic state of the cell. The analysis of the nanomotion frequency pattern demonstrated that single living yeast cells oscillate at relatively low frequencies of around 2 hertz. The simplicity of the technique should open the way to numerous applications among which antifungal susceptibility tests seem the most straightforward
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