KlyachinVA KlyachinAA AI book 2021

Abstract

This article examines the problem of object recognition in photographs. Objects of historical or cultural significance were selected as objects. In the work, the research was limited to two objects. It is assumed that the pictures can be taken at different times of the day and from different angles. Based on this, for one approach to solving the problem, it is proposed to extract the contours on the image of the object and calculate its characteristics. The moments of the curves of the contours up to the third order inclusive, the central moments, the normalized moments, and also the invariant moments of Hu are used as numerical values. In addition to this, the integral of the total curvature of the contour curve is calculated, the geometric meaning of which is that this integral is equal to the total variation of the slope of the tangent line of curve. The second approach is based on splitting the original image into rectangular cells and calculating the same moments as for the contours, but for the brightness function. Finally, in the third approach, the original image is replaced by the image of the outlines themselves. The article obtained results for several machine learning models, including convolutional neural networks, the method of nearest neighbors, and also the gradient boosting method is used to improve the results. #CSOC1120.

Klyachin V., Klyachin A. (2021) Pairwise Separability in the Problem of Identifying Objects in Photographs Using the Example of Cultural and Historical Architectural Buildings. In: Silhavy R. (eds) Artificial Intelligence in Intelligent Systems. CSOC 2021. Lecture Notes in Networks and Systems, vol 229. Springer, Cham. https://doi.org/10.1007/978-3-030-77445-5_25