Title :
A system for machine-written and hand-written character distinction
Author :
Kuhnke, K. ; Simoncini, L. ; Kovács-V, Zs M.
Author_Institution :
Dipartimento di Elettronica, Inf. e Sistemistica, Bologna Univ., Italy
Abstract :
In applications of character recognition where machine-printed and hand-written characters are involved, it is important to know if the character image, or the whole word, is machine- or hand-written. This is due to the accuracy difference between the algorithms and systems oriented to machine- or handwritten characters. Obviously, this type of knowledge leads to the increase of the overall system quality. In this work a classification system is presented which reads a raster image of a character and outputs two confidence values, one for “machine-written” and one for “hand-written” character classes, respectively. The proposed system features a preprocessing step, which transforms a general uncentered character image into a normalized form, then the feature extraction phase extracts relevant information from the image, and at the end, a standard classifier based on a feedforward neural network creates the final response. At the end, some results on a proprietary image database are reported
Keywords :
feature extraction; feedforward neural nets; handwriting recognition; image classification; multilayer perceptrons; optical character recognition; visual databases; accuracy difference; character classes; character recognition; classification system; confidence values; feature extraction; feedforward neural network; handwritten character distinction; image database; machine-written character distinction; normalized form; preprocessing step; raster image processing; system quality; Character recognition; Data mining; Data preprocessing; Feature extraction; Feedforward neural networks; Feedforward systems; Handwriting recognition; Neural networks; Optical character recognition software; Writing;
Conference_Titel :
Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-8186-7128-9
DOI :
10.1109/ICDAR.1995.602025