Character Spotting Using Image-Based Stochastic Models

Seon-Kyu Kim, Bong-Kee Sin, Seong-Whan Lee

Abstract: This paper concerns the modeling of character images by a Markov-like stochastic template that is constructed in the form of the pseudo 2D HMM. Being constructed directly from the image templates, the models can be composed in real time. Preliminary test results in digit recognition and Korean Hangul character spotting show the feasibility of the proposed method, especially in the context of incremental location of keywords.