To eliminate the noise component in infrared images, the paper proposes a method of inter-frame data alignment, built on the operations of pre-processing and highlighting the contours of objects and based on the following basic stapes: at the initial stage, the system operation parameters are determined, the frame size is read, the color field depth and speed fixing frames; the operation of selecting local areas with minimization of objects allows you to create a mask of objects and localize subsequent methods; determining the construction of inter-frame pixel shift vectors; accumulationformation of color intensity change data; data filtering based on a multi-criteria method based on the application of the criterion of the standard deviation of the results and the generated estimates, as well as the standard deviations of the final differences of the second order; frame processing of images by a two-dimensional multi-criteria method with preservation of object boundaries; framing the output image. On the set of test data obtained by the seak and flir cameras, examples of processing objects of simple shapes are given. Examples of visual reduction of the noise component on frames of test images are shown. Examples of error reduction in the formation of the proposed approach on synthetic sequences with superimposed Gaussian noise are given.
The article proposes an algorithm for processing parallel analysis of visual data obtained by a machine vision system, recorded information in the human visible spectrum, and information received by a range camera. An algorithm for the formation of stable features as elements of the human body, head and pupils of a person and parallel tracking of their increment is proposed. To highlight trend lines in element displacement and eliminate the high frequency component based on a combined criterion. The image is preliminarily processed to reduce the effect of the noise component based on a multi-criteria objective function. As test data used to evaluate the effectiveness, a video stream with a resolution of 1024x768 (8-bit, color image, visible range), 3D data, and expert evaluation data are used.
The accurate segmentation of the leaf area on scanned digital images plays a crucial role in the automated evaluation of its morphological characteristics. We propose here a new algorithm for extracting leaf area from the digital images based on a combination of a parametric description of shadow and background areas in the color space by support vector data description (SVDD) and the structure transfer filtering method based on the gamma-normal probabilistic model. The combination of these methods allows us to consider color information as well as sharp changes in image intensity at the edges of a leaf.
The paper proposes a solution to the problem of interpolation of the step function of displacement, obtained from the movement's formation by simple systems of object analysis. The analysis of the motion curve is carried out, taking into account the transformation of data into Cartesian coordinate systems and the processing of 2D signals. A multicriteria objective function is used as an interpolation method. This approach is based on solving the problem of minimizing the functional simultaneously according to three criteria. The first criterion is the mean square of the measure of the discrepancy between the input values and those obtained due to minimization. This criterion is to set the degree of approximation to the input data. As the second criterion, the function of the root-mean-square spread of the neighboring elements of the obtained values is used. This criterion allows you to minimize the scatter of data and set the smoothness of the function. As the third criterion, the root-mean-square functional between adjacent elements of the second group is used. This criterion allows one to increase the degree of smoothness of the function and the rate of convergence. The weighting function is adjusted using weighting factors. The paper provides recommendations on choosing these values, and the diagrams show the rationale for this choice. The graphs showing the effect of the rate of convergence of the results on the degree of smoothness of the function and the selected parameters of the method are presented. The graphs of the tool exit speed to the working point and the calculation of the path lengths are given. Examples of plotting the curves of functions obtained by machine vision systems located on robotic portal complexes are presented on test data sets. Data obtained in the visible range, with a resolution of 1280x1024 pixels, are presented in grayscale.
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