Probabilistic Indexing (PrIx) Framework

The proposed PrIx framework is formally presented in this chapter. In short, PrIx aims at processing each text image in such away that all the sets of strokes in the image which can be reasonably interpreted as text elements, such as characters and words, become symbolically represented; that is, represented like electronic text. However, the primary concern of PrIx is to retain all the information needed to also represent the intrinsic uncertainty which underlies text images, and more specifically handwritten text images. A dual presentation is given. First, a “pure” image processing viewpoint is adopted, where each text element in the images is treated just as a small object that has to be somehow detected and identified. This presentation will make it clear that PrIx, and KWS alike, essentially boil down to an object recognition process, where the class’ posterior probability of each object has to be estimated at each image location. Then PrIx will be developed in full detail from another equivalent viewpoint where the underlying object recognition problem is equated to HTR, thereby considering PrIx as a form of HTR which explicitly retains image interpretation uncertainty.