13. The system according to claim 12 , said word model comprising a Hidden Markov Model (HMM) and said background model comprising a Gaussian Mixture Model (GMM).
12. A system comprising: an input/output device receiving an image of a handwritten item; a word segmenter operatively connected to said input/output device, said word segmenter segmenting said image to produce a sub-image; an extractor operatively connected to said word segmenter, said extractor extracting a set of feature vectors from said sub-image; a processor operatively connected to said extractor, said processor performing the following: computing a first log-likelihood score of said feature vectors using a word model having a first structure; computing a second log-likelihood score of said feature vectors using a background model having a second structure different than said first structure; and computing a final score for said sub-image by subtracting said second log-likelihood score from said first log-likelihood score; and a comparator operatively connected to said processor, said comparator comparing said final score against a predetermined standard to produce a word identification result, said input/output device further being operatively connected to said comparator, said input/output device outputting said word identification result.