A Contour Code Feature Based Segmentation For Handwriting Recognition

The purpose of this paper is to present a novel contour code feature in conjunction with a rule based segmentation for cursive handwriting recognition. A heuristic segmentation algorithm is initially used to over segment each word. Then the prospective segmentation points are passed through the rule-based module to discard the incorrect segmentation points and include any missing segmentation points. The proposed rule-based module validates every segmentation points against closed area, average character size, left character and density. During the left char validation, a contour code feature is extracted and checked weather the left of the prospective segmentation point is a character or rubbish (non-char). The neural network used for this validation was trained on character and non-character database. Following the segmentation, the contour between correct segmentation points is passed through the feature extraction module that extracts the contour code, after which another trained ...

• Type: Conference
• Year: 2003
• Where: ICDAR
• Authors: Brijesh Verma
• Keywords: Contour Code Feature, Document Analysis, ICDAR 2003, Prospective Segmentation Point, Segmentation Points