Complex wavelet features for fast texture image retrieval
Digital libraries and multimedia databases are being rapidly developed and efficient search algorithms must now be developed. Gabor features have been experimentally shown to be the most accurate but have the disadvantage of slow computation. This paper shows how a new complex wavelet transform can be used to approximate the Gabor features and derives a distance metric based on statistical hypothesis testing that gives a better performance than the usual metric. The new features are experimentally compared with both Gabor and standard wavelet techniques.