The work examines the problem of improving the quality of data obtained in the IR range, their primary processing for possible analysis by the operator. To perform these operations, the work considers an approach based on the use of a group of methods that are unified for a wide range of tasks and, as a consequence, allow processing on computationally simple devices. We also propose iterative primary processing algorithms based on the multi-criteria smoothing method and the extraction of local features on two-dimensional data. The estimated number of elementary operations required for its implementation is shown, processing examples are given, parameters and errors are errors. An algorithm for localizing closed areas according to the temperature threshold class is presented. An algorithm has been developed for parallel analysis of streaming information from a pair of IR sensors that generate data in different ranges. An approach to parallel data extraction and the formation of a new information field with combined data is considered. Using the example of field test data, the results of improving their quality and examples of the formation of combined IR data are shown.
The goal of image enhancement is to improve specific features or details of an image and enhance its overall visual quality. We introduce a novel image enhancement algorithm based on block-rooting processing combined with multi-scale exposure image fusion. The proposed method integrates both local and global transform domain-based feedback mechanisms for imaging applications. The core concept of the local alpha-rooting method involves applying it to disjoint blocks of varying sizes, followed by the decomposition of the weight map and multi-scale enhanced images into Gaussian and Laplacian pyramids. Fusion is achieved by multiplying the multi-scale images and their corresponding weights. A new stage is introduced to obtain a local-global estimate of high-contrast images, which is also employed in the general artificial fusion model. Computer simulations conducted on image datasets demonstrate that the new enhancement algorithm outperforms state-of-the-art techniques.
Image segmentation is the critical step in different imaging and especially optical inspection applications: detection and recognition of objects, classification, analysis, and identification. Also, image gradient, as a preprocessing step, is an essential tool in image processing in many research areas, such as edge detection, segmentation, inpainting, etc. However, these tools have limitations and could be more accurate since the capture devices usually generate low-resolution images, which are primarily noisy and blurry. It is critical to receive useful gradient estimation on noisy color images while preserving the sharp edges. In the present paper, we develop a new gradient by integrating the quaternion framework with local polynomial approximation and the intersection of confidence intervals based on anisotropic gradient concepts for color image processing applications. We apply the proposed gradient technique in a modified active contour method to perform an automated segmentation for optical inspection applications. Computer simulations on the segmentation dataset for optical inspection applications show that the new adaptive quaternion anisotropic gradient exhibits fewer color artefacts than state-of-the-art techniques.
This article proposes a problem statement and its solution for finding a point equidistant from objects in three-dimensional space. The article considers an approach to determining the possible trajectory of a given object in an assumed threedimensional space R³, in which there are static 3D objects that impede the movement of the given object. A computer vision system is used for spatial positioning. To determine the point of displacement of the object's trajectory in space, a solution to the problem of searching for optimal trajectories on planes that do not intersect or touch the boundaries is proposed. The article discusses an algorithm for solving this problem and provides examples of determining optimal trajectories in a curved surface using the method of multicriterial interpolation of curves, with a given discretization step. The generation of a data set for a curved surface (point cloud) is described. Examples of searching for the hovering point of an object in the absence of its contact with external boundaries are given. An example of searching for an equidistant point in space with simple-shaped objects is given on a test data set, and recommendations are given for their use in robotic systems.
The article proposes the use of three directions of development at once to solve the problem of dividing objects into classes. The first direction uses the formation of a computationally simple multi-criteria method for smoothing data in windows of complex adaptive forms, adapting the method of dividing objects into background/structure, and simplifying images. The approaches being developed are intended for implementation on low-computing devices with the ability to parallelize processes. The second direction being worked on is the formation of a model of the structure of a neuron organized on the basis of the use of memristor structures. The paper presents an approach to the formation of such structures, provides the characteristics of such devices, and describes methods for combining analog and digital parts to implement memory or control systems. The final direction discussed in the article is the formation of a neural network for the classification of simple objects based on a model of new neurons and data preprocessing. To test the approach proposed in the work, studies were carried out on a set of test data obtained by a sensor (simple sensor) system. The generated data array for evaluating efficiency is limited by a time window and has real noise (errors). The work provides assessments of effectiveness, recommendations for the selection of parameters and presents requirements for the type and form of the analyzed data.
The article proposes to control of algorithm for the process of forming a coating with an increased content of an oxide layer resulting from the application of plasma formation of surface films. An implementation of an algorithm for adaptive determination of the contours of plasma discharge boundaries during the formation of films of memristor structures is proposed. The construction of the algorithm is based on the use of a multicriteria data processing method in the function of the boundary detector. An implementation of an adaptive change in the contact mask of the plasma discharge with the surface is proposed. Analysis of the contact size and density influences the shape and rate of formation of the oxide layer. The appearance of such a coating has the ability, when exposed to current, to form a complex curve of a function of a given shape. With the subsequent application of voltage, it can be used as an activation function. Recommendations on control and changes influences are presented. A hardware model implementation of an artificial neuron based on blocks of digital elements is presented. Examples of solving the problem of predicting the movement of an actuating element in the control of robotic complexes based on the formed neurons are given.
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