Offline Handwritten English Script Recognition: A Survey

OFFLINE handwriting recognition is the task of determining what letters or words are present in a digital image of handwritten text. It is of significant benefit to man-machine communication and can assist in the automatic processing of handwritten documents. It is a subtask of Optical Character Recognition (OCR), whose domain can be machine-print or handwriting but is more commonly machine-print. The recognition of English handwriting presents unique challenges and benefits and has been approached more recently than the recognition of text in other scripts. This paper describes the state of the art of this field. Handwritten recognition is usually classified into two groups which are online and offline. Online character recognition deals with information about writing dynamics as the text is being written while offline character recognition deals with static Information in which acquisition is done after all the text is written. Offline character recognition usually uses other medium of written text such as papers. One of the main issues in handwritten text recognition is that its accuracy, in human depends on knowledge about which language the text is written. Same text of the same corpus but written in different language can result in different accuracy [1]. It is “offline” if it is applied to previously written text, such as any images scanned in by a scanner. The online problem is usually easier than the offline problem since more information is available. This survey is restricted to offline systems. Standard database is also important for handwriting recognition research. The database is used in the development, evaluation, and comparison of different handwriting recognition algorithms [2]. Many databases have been developed in the character recognition community ranging from printed, handwritten, isolated or cursive, and also in various scripts. Some of them are publicly available such as IAM [2-3] and IRONOFF [4].