Title :
Document image decoding by heuristic search
Author :
Kam, Anthony C. ; Kopec, Gary E.
Author_Institution :
MIT, USA
fDate :
9/1/1996 12:00:00 AM
Abstract :
This correspondence describes an approach to reducing the computational cost of document image decoding by viewing it as a heuristic search problem. The kernel of the approach is a modified dynamic programming (DP) algorithm, called the iterated complete path (ICP) algorithm, that is intended for use with separable source models. A set of heuristic functions are presented for decoding formatted text with ICP. Speedups of 3-25 over DP have been observed when decoding text columns and telephone yellow pages using ICP and the proposed heuristics
Keywords :
Markov processes; computational complexity; decoding; document image processing; dynamic programming; heuristic programming; image processing; iterative methods; search problems; ICP algorithm; computational cost; document image decoding; dynamic programming; heuristic functions; heuristic search; iterated complete path algorithm; telephone yellow pages; text columns; Computational efficiency; Costs; Dynamic programming; Heuristic algorithms; Hyperspectral imaging; Image segmentation; Iterative closest point algorithm; Iterative decoding; Kernel; Viterbi algorithm;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
