Distinctive Feature Analysis of Natural Landmarks as a Front end for SLAM applications

This paper presents a method for extracting distinctive textural features from images taken from natural scenes. The aim is to use natural landmarks for navigation in an unexplored environment. Natural features are all different and complex in shape. To be able to use them for navigation, informative representation of these features and a careful selection process is required. The present method is termed as ‘Distinctive Texture Analysis’. It has three parts. Firstly, a method of selecting Interest Points from the filtered images is presented. Secondly, Texture Analysis of the local properties of Interest Points are applied and stored as descriptors. Thirdly, to reduce the number of landmarks selected for storage and comparison purposes, Distinctness Analysis is applied. Current results have shown that the most distinctive features as concurred by viewing the simple images are able to be selected and correctly matched. Results provided for the complex underwater images illustrated the difficulty and limitation. However, when this method is applied with multiple numbers of landmarks such that correlation of landmark positions is considered, certainty for SLAM can increase. Future works can include consideration of such correlation.