The bag-of-features algorithm for practical applications using the MySQL database

Abstract

This article presents a modification of the Bag-of-Features method (also known as a Bag-of-Words or Bag-of-Visual-Words method) used for image recognition in practical applications using a relational database. Our approach utilises a modified k-means algorithm, owing to which the number of clusters is automatically selected, and also the majority votes method when making decisions in the classification process. The algorithm can be used both methods in an SQL Server database or a commonly-used MySQL one. The proposed approach minimises the necessity to use additional algorithms and/or classifiers in the image classification process. This makes it possible to significantly simplify computations and use the SQL language.