Multiple Class Machine Learning Approach for an Image Auto-Annotation Problem

Image auto-annotation problem becomes more and more popular research topic. Possible applications of auto-annotation methods range from Internet search engines to medical analysis software. The important aspect is that efficient image auto-annotation systems can eliminate the need of annotating huge image collections manually, which is the only solution today. Most of methods available in the literature do not use supervised machine learning as the key component. Recent researches show that supervised machine learning can successfully compete with existing approaches. This paper presents a novel image auto-annotation algorithm based of supervised machine learning with the use of C4.5 classifiers