An Unsupervised Intelligent System to Detect Fabrication in Photocopy Document using Geometric Moments and Gray Level Co-Occurrence Matrix

Photocopy documents are very common in our normal life. People are permitted to carry and produce photocopied documents frequently, to avoid damages or losing the original documents. But this provision is misused for temporary benefits by fabricating fake photocopied documents. When a photocopied document is produced, it may be required to check for its originality. An attempt is made in this direction to detect such fabricated photocopied documents. This paper proposes an unsupervised two level classification system to detect fabricated photocopied document using Geometric moments and Gray Level Co-Occurrence Matrix features. The work in this paper mainly focuses on detecting fabrication of photocopied document in which some contents are manipulated by smearing whitener over the original content and writing new contents above it. A detailed experimental study has been performed using a collected sample set of considerable size and a decision model is developed for classification. Testing is performed with a different set of collected testing samples resulted in an average detection rate of 94.59%.