A feedback-based approach for segmenting handwritten legal amounts on bank cheques
Abstract
The proposed feedback-based approach is implemented in two steps. In the first step, segmentation is done according to the structural features between the connected components in the legal amounts. In the second step, a feedback process is introduced to re-segment the parts that could not be identified in the first step. Then a multiple neural network classifier is used to verify the re-segmentation result. The confidence value produced by the classifier is used to determine the best segmentation points. This approach is tested on a CENPARMI database and the result indicates that the correct segmentation rate increased by 13.4% from the previous approach.
Copyright Statement
Copyright 2001 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Subject
Pattern Recognition and Data Mining