1. A method for classifying objects from one or more images comprising the steps of: generating a trained classification process; and using the trained classification process to classify objects in said one or more images; wherein generating the trained classification process comprises the steps of: extracting features from one or more training images and clustering said features into one or more groups of features termed visual words; storing data for each of said visual words, including colour and texture information, as descriptor vectors; and generating a vocabulary tree to store clusters of visual words with common characteristics; and wherein using the trained classification process to classify objects in said one or more images comprises the steps of: extracting features from said one or more images and clustering said features into groups of features termed visual words; searching the vocabulary tree to determine the closest matching clusters of visual words; and classifying objects based on the closest matching clusters of visual words in the vocabulary tree.