The bag-of-words method with dictionary analysis by evolutionary algorithm

In this paper we present innovative solutions improving general operational efficiency of the Bag-of-Words algorithm (BoW). The first innovation which we put forward is creating a visual words’ dictionary using the clustering algorithm which in itself is responsible for selecting the appropriate number of clusters. This solution results in significant automation of image database creation. Another innovation is adding to the BoW model an analytical module whose task is to analyse the visual words’ dictionary and to modify histogram values before storing them in a database. This algorithm is operated with the use of the evolutionary algorithm. The modifications of the BoW algorithm significantly improve the efficiency of image search and classification, which has been presented in a variety of experiments.