Markov Models for Handwriting Recognition (Paperback)

Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden Markov models and Markov-chain or n-gram models. First, the text introduces the typical architecture of a Markov model-based handwriting recognition system, and familiarizes the reader with the essential theoretical concepts behind Markovian models. Then, the text reviews proposed solutions in the literature for open problems in applying Markov model-based approaches to automatic handwriting recognition.

自從它們首次出現以來，自動閱讀系統已經有了很大的發展，但由於手寫的外觀變化很大，手寫識別仍然是一個開放的研究問題。隨著馬可夫模型引入該領域，為自動手寫識別建立了一個有前途的建模和識別範式。然而，目前尚未建立基於馬可夫模型的識別器的標準程序。本文全面介紹了馬可夫模型在手寫識別領域的應用，包括隱藏馬可夫模型和馬可夫鏈或n-gram模型。首先，本文介紹了基於馬可夫模型的手寫識別系統的典型架構，並使讀者熟悉馬可夫模型背後的基本理論概念。然後，本文回顧了文獻中提出的解決方案，以應用基於馬可夫模型的方法解決自動手寫識別中的開放問題。