Comparative analysis of invariant schemes for logo classification

Logo or Trademark is of high importance because it carries the goodwill of the company and the product. Products are mostly recognized by their brand logos. Their recognition is a major problem. A number of techniques are there for logo recognition. In this paper, a number of invariant techniques are compared to find out their effectiveness on various categories of brand logos. Techniques which were investigated are Hu's Invariant Moments, Log-Polar Transform (LPT), Fourier-Mellin transform (FMT), Gradient Location-Orientation Histogram (GLOH). Experiments were performed on University of Marry Land (UMD) database. Results are given, along with recognition rate and time taken. Results show that GLOH performs the best with approximately 97% recognition rate but need a more computational time while on the other extreme FMT technique performs poorest with recognition rate with average of approx. 85% but with least computational time compared to all other techniques.