Feature extraction, feature selection and machine learning for image classification: A case study

Abstract

This paper presents feature extraction, feature selection and machine learning-based classification techniques for pollen recognition from images. The number of images is small compared both to the number of derived quantitative features and to the number of classes. The main subject is investigation of the effectiveness of 11 feature extraction/feature selection algorithms and of 12 machine learning-based classifiers. It is found that some of the specified feature extraction/selection algorithms and some of the classifiers exhibited consistent behavior for this dataset.