Extraction of features in images based on integral transformations in solving problems of classification of fragments of photographs

Abstract

The article proposes a method for calculating features in an image to form a training data set for solving various problems of video image classification. This method involves the use of well-known integral transformations — the Radon transform and the Steklov function. The proposed method is compared with convolutional neural networks both in terms of the percentage of correct prediction and in terms of its execution time. As a test task, the problem of finding a fragment of a photograph containing an image of a car is considered.

Keywords

• radon transform
• steklov functions
• convolutional neural network
• machine learning methods