On Appearance-Based Feature Extraction Methods for Writer-Independent Handwritten Text Recognition

Fink GA, Plötz T. On Appearance-Based Feature Extraction Methods for Writer-Independent Handwritten Text Recognition. In: Proc. Int. Conf. on Document Analysis and Recognition. Vol 2. Seoul, Korea: IEEE; 2005: 1070-1074.Most successful systems for the recognition of unconstrained handwriting currently rely on expert-crafted feature sets that compute local geometric properties from text images. However, by applying appearance based analysis techniques appropriate features could be derived from training data automatically. Therefore, in this paper several different methods for computing appearance based feature representations were investigated and compared to the performance of a state-of-the-art writer-independent recognition system based on geometric features. In extensive experiments promising results were obtained on a challenging recognition task

On Appearance-Based Feature Extraction Methods for Writer-Independent Handwritten Text Recognition

Most successful systems for the recognition of unconstrained handwriting currently rely on expert-crafted feature sets that compute local geometric properties from text images. However, by applying appearance based analysis techniques appropriate features could be derived from training data automatically. Therefore, in this paper several different methods for computing appearance-based feature representations are investigated and compared to the performance of a state-of-the-art writer-independent recognition system based on geometric features. In extensive experiments promising results were obtained on a challenging recognition task. 1

Pattern Recognition

Pattern recognition is a very wide research field. It involves factors as diverse as sensors, feature extraction, pattern classification, decision fusion, applications and others. The signals processed are commonly one, two or three dimensional, the processing is done in real- time or takes hours and days, some systems look for one narrow object class, others search huge databases for entries with at least a small amount of similarity. No single person can claim expertise across the whole field, which develops rapidly, updates its paradigms and comprehends several philosophical approaches. This book reflects this diversity by presenting a selection of recent developments within the area of pattern recognition and related fields. It covers theoretical advances in classification and feature extraction as well as application-oriented works. Authors of these 25 works present and advocate recent achievements of their research related to the field of pattern recognition