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In this paper, the problem of automatic Gabor wavelet selection for facerecognition is tackled by introducing an automatic algorithm based on ParallelAdaBoosting method. Incorporating mutual information into the algorithm leadsto the selection procedure not only based on classification accuracy but alsoon efficiency. Effective image features are selected by using properly chosenGabor wavelets optimised with Parallel AdaBoost method and mutual informationto get high recognition rates with low computational cost. Experiments areconducted using the well-known FERET face database. In proposed framework,memory and computation costs are reduced significantly and high classificationaccuracy is obtained.

Parallel AdaBoost Algorithm for Gabor Wavelet Selection in Face Recognition