Image similarity based on Discrete Wavelet Transform for robots with low-computational resources

This paper describes a similarity measure for images which can be used in image-based topological localization and topological SLAM problems by autonomous robots with low computational resources. Instead of storing the images in the robot’s memory, we propose a compact signature to be extracted from the images. The signature is based on the calculation of the 2D Haar Wavelet Transform of the gray-level image and its size is only 170 bytes. We called this signature the DWT-signature. We exploit the frequency and space localization property of the wavelet transform to match the images grabbed by the perspective camera mounted on board the robot and the reference panoramic images built using an automatic image stitching procedure. The proposed signature allows, at the same time, memory saving and fast and efficient similarity calculation. For the topological SLAM problem we also present a simple implementation of a loop-closure detection based on the proposed signature. We report experiments showing the effectiveness of the proposed image similarity measure using two kinds of small robots: an AIBO ERS-7 robot of the RoboCup Araibo Team of the University of Tokyo and a Kondo KHR-1HV humanoid robot of the IAS-Lab of the University of Padua.