JOURNAL ARTICLE

Off-line Recognition of Unconstrained Handwritten Numerals Using Fuzzy Hough Transform

Mohammed Z. KhedherGhayda Al-TalibShayma Al mashhadany

Year: 2009 Journal:   Maǧallaẗ al-rāfidayn li-ʿulūm al-ḥāsibāt wa-al-riyāḍiyyāẗ/˜Al-œRafidain journal for computer sciences and mathematics Vol: 6 (3)Pages: 211-226

Abstract

A fuzzy system for handwritten numerals recognition using a fuzzy Hough transform technique is presented. The system is an off-line system since the data processed was written before the time of recognition. A data base of 480 patterns of unconstrained (free) handwritten numerals was used in the proposed system. Membership values are determined as fuzzy sets which are defined on the standard Hough transform vector. Manhattan distance measurement has been used to measure the similarity of an input feature vector to a number of numeral pattern classes. The overall recognition accuracy of the system for the ten numerals is 95%.

Keywords:
Numeral system Hough transform Pattern recognition (psychology) Artificial intelligence Computer science Fuzzy logic Line (geometry) Feature (linguistics) Similarity (geometry) Feature vector Similarity measure Speech recognition Mathematics Image (mathematics)

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Topics

Handwritten Text Recognition Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Hand Gesture Recognition Systems
Physical Sciences →  Computer Science →  Human-Computer Interaction

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