This thesis compares two machine learning models : the active basis model and the AdaBoost model for image representation. It also implements these two models on eight different categories of example images to create the respective active basis template and adaboost classifier. The results of this experiment show that the active basis template could create a more representative model of a specific category with less Gabor wavelet elements than the adaboost classifier.