Methods for identifying informative features in agricultural images

Abstract

The paper deals with informative aspects of images, their scope and extraction methods. The research addresses numerous different types of features such as texture, color, geometric and structural features that play an important role in the field of image analysis and recognition. Contemporary extraction methods based on machine learning algorithms and fractal dimension are explained. The possibility of usage of these methods in real-life problems such as medical imaging, biometrics, remote sensing images processing and agriculture is considered. Successful implementation examples of information functions in real-life problems are presented and opportunities for further research on the topic are considered.