Alain C. Gonzalez, Toluca, Electronics and Electrical Engineering Department Metepec, MEXICO
Juan H. Sossa, Computing Research Center, National Polytechnic Institute Mexico, D.F. MEXICO
Edgardo. M. Felipe, Computing Research Center, National Polytechnic Institute Mexico, D.F. MEXICO
Oleksiy Pogrebnyak, Computing Research Center, National Polytechnic Institute Mexico, D.F. MEXICO
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.
Citation:
Alain C. Gonzalez, Juan H. Sossa, Edgardo. M. Felipe, Oleksiy Pogrebnyak, "Wavelet transforms and neural networks applied to image retrieval," icpr, vol. 2, pp.909-912, 18th International Conference on Pattern Recognition (ICPR'06) Volume 2, 2006