Sensitivity Study of Feature Vectors Formed on the Basis of Multiple Scale Transformations of Processed Images

Abstract

Introduction. Under the conditions of globalization, transportation of oil products by tanker fleets becomes one of the causes of man-made disasters in the water areas of seas and oceans. In this context, environmental monitoring acquires particular significance as a tool for ensuring timely detection of negative consequences of man-made disasters. This task is facilitated by recognition of images obtained from unmanned aerial vehicles with selection of those depicting the traces of man-made accidents or their consequences.Aim. To develop approaches for carrying out automatic selection of input data obtained from unmanned aerial vehicles in the form of photo and video images at the preliminary stage of image recognition.Materials and methods. The theoretical part of the study employed a classification method based on pattern recognition theory. Mathematical processing and calculation were carried out in the MATLAB environment. Simulation was conducted using the MathCAD environment.Results. A series of experiments was conducted to select a basis for discrete wavelet transforms. Modeling was conducted using the study results of the sensitivity of the feature vectors of images formed on the basis of different types of wavelet transforms. A concept of image construction for the purposes of feature vector formation was developed.Conclusion. An approach to the formalization of images for the purposes of feature vector formation is proposed. A metric of their contrast estimation is substantiated. It was established that the sensitivity of a recognition system based on the representation of images in the form of discrete wavelet transform matrices depends not only on the type of the mother wavelet, but also on the value of the scale parameter.

Keywords

• algorithm for recognizing feature vectors
• wavelet transform of signals
• contrast of feature spaces