Histograms, wavelets and neural networks applied to image retrieval

Authors:
Alain C. Gonzalez;Juan H. Sossa;Edgardo Manuel Felipe Riveron;Oleksiy Pogrebnyak
Affiliations:
Electronics and Electrical Engineering Department, Technologic Institute of Toluca, Metepec, México;Computing Research Center, National Polytechnic Institute, México D.F.;Computing Research Center, National Polytechnic Institute, México D.F.;Computing Research Center, National Polytechnic Institute, México D.F.
Venue:
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Year:
2006

Citing 12
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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.