A pinboard by
Vivek Venugopal

Research Scholar, Indian Institute of Technology, Guwahati


The objective is to decide the authorship of a handwritten document from a set of enrolled writers.

Biometrics refers to identification of a person based on their physical or behavioral characteristics. A physical biometric utilize data obtained from direct measurements of a part of the individual where as, behavioral characteristic consider the measurements and data derived from an action performed by the user, and thus indirectly measure some characteristics of the individual. Writer identification falls into the latter category and falls under the broader domain of automatic handwriting recognition. In writer identification, given a document of unknown authorship, we rank a list of likely writers, from the reference set. Person identification through handwriting is accepted in many government, legal and commercial transactions as a method of personal authentication. As such, it is a non-invasive and non-threatening process, and can overcome some of the privacy problems present in other biometric systems such as passwords, and fingerprints. The research works in writer identification can be divided into two approaches: (i) text dependent and (ii) text independent. The former require handwriting based on a specific text or assume the availability of handwriting recognizer for identifying the writer. The problem of signature verification is one such popular instance of text independent writer identification. In general, the use of knowledge of the content of the data increases the accuracy of such systems, However, they fail in scenarios where in the text documents with different contents need to be compared. In such scenarios, text independent writer identification systems capture the style information of handwriting and can identify the writer irrespective of textual content. On the basis of data acquisition, writer identification techniques can be categorized into two main techniques: off-line and online. The recent advances in technology has enabled the release of hand-held devices where in data entry is captured through an electronic pen/stylus. The recorded data captures the dynamic information present in the trace of the handwriting such as (x,y) coordinates, azimuth, and time stamp. The term 'online' handwriting refers to the data of the above nature. A document in online handwriting is represented as a set of strokes, each of which consists of a sequence of points recorded between a pen-down and a pen-up signal. On the contrary, a document in the offline setting is characterized in the form of a scanned image containing the handwritten data.