| 摘要 |
An image decoding and recognition system and method comprising a fast heuristic algorithm using hidden Markov models (HMM). The new search algorithm, called an "iterative complete path" (ICP) algorithm, patterned after well-known branch-and-bound (B&B) methods, significantly reduces the complexity and improves the speed of HMM image decoding without sacrificing the optimality of the straightforward procedure. An advantageous form of the heuristic functions which is useful in applying the ICP algorithm to text-like images is described. The ICP algorithm is directly applicable to the separable type of finite-state source models. Also disclosed is a technique for transforming more general source models into such a separable form.
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