In this paper, we propose and implement the data mining techniques for verification of hand-writing recorded in an image. The captured images are considered independent of writing material in this system. This system consists of six submodules. Namely, i) Sample image data acquisition and preprocessing; ii) Vectors generation; iii) Computation of clusters; iv) Cluster Head Computation v) Pattern Parameter Extraction; vi) Result. The first sub-module captures and categorizes the image for preprocessing. These preprocessed images are vectored and a cluster is computed based on thea) degree of entropy in the vectors. Therefore, these bunch of clusters represent themselves with the degree of entropy, type of cluster by choosing a cluster head. Finally, the parameters such as the distance, entropy, confidence, are extracted from the clustering; and a result is generated for the given set of samples.
Dr. Tripty Singh and Mishra, S., “Image Vector Classification Algorithm for Hand-Writing Verification”, in International Conference on Advances in Computing, Communications and Informatics (ICACCI), Greater Noida, India., 2014.