5. The method of claim 1 , further comprising: applying a sliding window for each of the plurality of regions; partitioning each window of the sliding window into one or more cells; and determining one or more local descriptors for each cell.
1. Arabic handwriting recognition method, comprising: acquiring, an input image from a document representative of a handwritten Arabic text from a user, wherein the input image is acquired with at least one selected from the group consisting of a scanner, a camera and a data storage device; partitioning, using processing circuitry of a server, the input image into a plurality of regions; determining, using the processing circuitry, a bag of features representation for each region of the plurality of regions, wherein the bag of features representation includes one or more mid-level features selected from the group consisting of a percentile of intensities, an angle, a correlation, and an energy; modeling, using the processing circuitry, each region independently by multi stream discrete Hidden Markov Model (HMM); and identifying, using processing circuitry, a recognized text based on the HMM models.