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Histograms, Wavelets and Neural Networks Applied to Image Retrieval

  • Alain C. Gonzalez
  • Juan H. Sossa
  • Edgardo Manuel Felipe Riveron
  • Oleksiy Pogrebnyak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4293)

Abstract

We tackle the problem of retrieving images from a database. In particular we are concerned with the problem of retrieving images of airplanes belonging to one of the following six categories: 1) commercial planes on land, 2) commercial planes in the air, 3) war planes on land, 4) war planes in the air, 5) small aircrafts on land, and 6) small aircrafts in the air. During training, a wavelet-based description of each image is first obtained using Daubechies 4-wavelet transformation. The resulting coefficients are then used to train a neural network. During classification, test images are presented to the trained system. The coefficients are obtained from the Daubechies transform from histograms of a decomposition of the image into square sub-images of each channel of the original image. 120 images were used for training and 240 for independent testing. An 88% correct identification rate was obtained.

Keywords

Image Retrieval Wavelet Coefficient Pattern Recognition Letter Neural Network Apply Correct Identification Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Alain C. Gonzalez
    • 1
    • 2
  • Juan H. Sossa
    • 2
  • Edgardo Manuel Felipe Riveron
    • 2
  • Oleksiy Pogrebnyak
    • 2
  1. 1.Electronics and Electrical Engineering DepartmentTechnologic Institute of TolucaMetepecMéxico
  2. 2.Computing Research CenterNational Polytechnic InstituteMéxico D.F.

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