Vehicle Logo Recognition Using Local Fisher Discriminant Analysis

This paper presents a method for localising and recognising vehicle manufacturer logos in both the front and rear views. The method assumes that the vehicle registration plate is visible and an estimate of its location is available. Features are constructed out of local histograms of gradients, in both conventional and hierarchical arrangements. The dimensionality of these vectors is then reduced using unsupervised PCA and, subsequently a supervised method based on Local Fisher Discriminant Analysis. This then provides a suitable metric for logo detection, localisation and multi-class classification. On a test set of data captured from a medium range CCTV camera, with five different manufacturers' logos, the proposed method provided a correct logo localisation rate of 97 % and a correct logo classification rate of 87.6%.