Improving the accuracy of combining pairs of thermal images based on the analysis of visual information

Abstract

The use of data obtained by a group of sensors requires the formation of parallel channels. The use of each separate channel leads to the need to allocate additional computing resources and the appointment of time intervals (timing) for a single-processor analysis system. The formation of the decision rule and the subsequent decision-making based on such data requires forming a combined inter-block criterion. This criterion should consider both the possible intersection of data and their discrepancy associated with the use of different parameters when processing the same data. The formation of combined data reduces the computational costs at the decision-making stage, which will improve the efficiency of post-processing and visual control systems. In using combined stationary systems, it is possible to create template fields that allow you to form transformation matrices for a specific space. If it is impossible to use fixed cameras or combined systems in a single body, forming stitching images is complicated. Combining data into a single information field also allows you to increase the operator's work efficiency, allowing you to analyze the entire process as a whole and not its scattered parts. The paper proposes a technique for forming a stitching thermal imaging image based on combined data analysis. For the formation of anchor points for stitching images, primary analysis methods with combined processing parameters are used. Images obtained from the outputs of thermal imaging cameras are pre-processed by the filtering method. The method used is based on the application of a multicriteria function. It automatically divides the image into regions (boundaries, highly detailed, and locally stationary areas) to reduce noise while preserving the transition boundaries. To increase the processing speed, a simplification algorithm is applied while maintaining the shapes and geometry of objects. The operation includes absorbing small objects and averaging for the ranges of histograms of color gradients. Analysis of local features and the formation of anchor points is based on the use of correlation analysis. As a method of non-linear change in color balance, modified alpha-rooting methods are used. As test data, a series of images of one object obtained from different fixation points in: visible (camera with a resolution of 1920 x 1080 pixels, color depth 8 bits) and far-infrared (thermal images with a resolution of 320 x 240 pixels, grayscale). Images have at least 40% overlap area of one object. Applications for both industrial production and the analysis of objects in the open areas are considered.