HMM for perspective estimation in document image, can't understand the algorithm
- by maximus
Hello!
Here is a paper, it is about estimating the perspective of binary image containing text and some noise or non text objects.
PDF document
The algorithm uses the Hidden Markov Model: actually two conditions
T - text
B - backgrouond (i.e. noise)
It is hard to understand the algorithm itself. The question is that
I've read about Hidden Markov Models and I know that it uses probabilities that must be known.
But in this algorithm I can't understand, if they use HMM, how do they get those probabilities (probability of changing the state from S1 to another state for example S2)?
I didn't find anything about training there also in that paper.
So, if somebody understands it, please tell me.
Also is it possible to use HMM without knowing the state change probabilities?