The article proposes a fusion technique and an algorithm for combining images recorded in the IR and visible spectrum in relation to the problem of processing products by robotic complexes in dust and fog. Primary data processing is based on the use of a multi-criteria processing criterion with complex data analysis and cross-change of the filtration coefficient for different types of data. The search for base points is based on the application of the technique of reducing the range of clusters (image simplification) and searching for transition boundaries using the approach of determining the slope of the function in local areas. As test data used to evaluate the effectiveness, pairs of test images obtained by sensors with a resolution of 1024x768 (8-bit, color image, visible range) and 1024x768 (8 bit, color, IR image) are used. Images of simple shapes are used as analyzed objects.
The display of information characterizing the distribution of thermal gradients is associated with the formation of a twodimensional image. A thermal image is most often a group of objects with varying intensities. This picture is due to physical aspects. Most often, the thermal background does not have a clear boundary, and therefore the use of conventional methods for detecting special features in the form of angles or borders is not applicable. In the previously described works, a method was proposed for identifying special features based on the search for the midline, for closed objects. This approach did not take into account the possibility of changing the degree of growth of the line displacement, which may be correct provided that a pair of objects of different temperatures adjoin each other and there is information about this. The article proposes to develop a modification of the search method an equidistant curve that allows you to introduce a curve growth function. The difference from the original approach is the possibility of regulating the degree of movement of the internal or external borders in the direction of the neighbor. The approach proposed in the work includes the operations of filtering, changing the color space, changing the color range, and searching for stable signs. The task is relevant and may also be applicable in tasks: increasing the clarity of x-ray images; eliminate blur in photos; preprocessing images obtained in the visible spectrum; deblurring images obtained in motion, etc. In the article on a set of test data shows the applicability of the proposed approach for identifying stable features in thermal imaging images. The data obtained by FLIR C2 and SEEK thermal imaging cameras cover a wide range of possible applications from analysis of data obtained outside buildings, as well as technical processes occurring inside mechanisms.
Modern devices based on the analysis of thermal images are used in the construction of technical systems and the analysis of processes occurring into objects. In the modern world, the analysis of information about temperature changes allows you to solve many problems, drive a car in poor visibility conditions (fog, smog, twilight or night), create security systems and control access to objects, analyze internal processes, including such as: chemical reactions; friction analysis; checking the operation of complex technical systems (bearings, electrical, lubrication, cooling); living organisms (analysis of processes tissue death); temperature audit of buildings; analysis of the operation of internal combustion engines; braking and friction analysis systems; other. The image formed by the thermal imager has a low resolution. In order to analyze complex processes, it is necessary to develop methods and algorithms for combining images into a single information field. The problem of stitching images is encountered in many areas of technology, but for IR it is the most difficult. The article proposes an approach that allows you to identify local features in IR images, which allows you to increase the accuracy of stitching pairs of images into a single composition. The proposed algorithm based on layer-by-layer image analysis. The analysis is based on the search for local features, followed by a change in the bitrate of the image and the study of stationary edges. An example of highlighting local features is shown on a set of test images captured by a thermal imaging camera. The scope of this approach is the task of combining images obtained only in the infrared range.
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