A handwritten character recognition system using directional element feature and asymmetric Mahalanobis distance
IEEE transactions on pattern analysis and machine intelligence, 1999•ieeexplore.ieee.org
This paper presents a precise system for handwritten Chinese and Japanese character
recognition. Before extracting directional element feature (DEF) from each character image,
transformation based on partial inclination detection (TPID) is used to reduce undesired
effects of degraded images. In the recognition process, city block distance with deviation
(CBDD) and asymmetric Mahalanobis distance (AMD) are proposed for rough classification
and fine classification. With this recognition system, the experimental result of the database …
recognition. Before extracting directional element feature (DEF) from each character image,
transformation based on partial inclination detection (TPID) is used to reduce undesired
effects of degraded images. In the recognition process, city block distance with deviation
(CBDD) and asymmetric Mahalanobis distance (AMD) are proposed for rough classification
and fine classification. With this recognition system, the experimental result of the database …
This paper presents a precise system for handwritten Chinese and Japanese character recognition. Before extracting directional element feature (DEF) from each character image, transformation based on partial inclination detection (TPID) is used to reduce undesired effects of degraded images. In the recognition process, city block distance with deviation (CBDD) and asymmetric Mahalanobis distance (AMD) are proposed for rough classification and fine classification. With this recognition system, the experimental result of the database ETL9B reaches to 99.42%.
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