Wavelet transforms and neural networks applied to image retrieval

  • Authors:

  • Alain C. Gonzalez;Juan H. Sossa;Edgardo. M. Felipe;Oleksiy Pogrebnyak

  • Affiliations:

  • Toluca, Electronics and Electrical Engineering Department Metepec, MEXICO;Computing Research Center, National Polytechnic Institute Mexico, D.F. MEXICO;Computing Research Center, National Polytechnic Institute Mexico, D.F. MEXICO;Computing Research Center, National Polytechnic Institute Mexico, D.F. MEXICO

  • Venue:
  • ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
  • Year:
  • 2006

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Abstract

We face the problem of retrieving images from a database. During training a wavelet-based description of each image is first obtained using a Daubechies 4- wavelet transformation. Resulting coefficients are used to train a neural network (NN). During retrieval, a given image is presented to the already trained NN. The system responds with the most similar images. Three different ways to obtain the coefficients of the wavelet transform are tested: From the entire image, from the histogram of the biggest circular window inside the image color channels, and from the histograms of square sub-images in the image channels of the original image. 120 color images of airplanes were used for training and 240 for testing. The best efficiency of 88% was obtained with the third description method.