We introduce an iterative approach to recognizing

two-dimensional grammatical structure within digital

images, which we term “turbo recognition.” Inspired

by the success of turbo decoding for channel

coding of one-dimensional sequences, we develop

a recognition scheme for images based on

two independent views of the same underlying message.

These correspond to two independent image

sources, one in the horizontal direction and the other

in the vertical direction, which are driven by a single

input message. The recognition process proceeds

iteratively, first along one direction and then

the other, applying the Forward/Backward algorithm

to derive a new prior probability distribution on the

input message for the orthogonal recognition step.

This holds promise as a principled approach within

the Document Image Decoding (DID) framework

for the recognition of nontrivial 2D layout structure

such as tables.

In  IAPR Workshop on Document Layout Interpretation and its Applications

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