Handwritten Character Recognition from Digital Image: Recent Advancements

This paper presents an overview of feature extraction methods for off-line recognition of segmented (isolated)
digit/chratchter. Selection of a feature extraction method is probably the single most important factor in
achieving high recognition performance in character recognition systems. Different feature extraction methods
are designed for different representations of the digit/characters, such as solid binary characters, skeletons
(thinned digit /characters), or gray level sub images of each individual character. Latest research in this area has
been able to grown some new methodologies to overcome the complexity of Guajarati digit writing style. The
recognition of handwritten digits which are written in proper way to easily readable. The problem is human can
write digit in different styles so it is not identified by the computer but the some feature extraction
methodologies like end point, junction point; straight lines etc. For features identification and character
classification studied different algorithm and technique.