Expert Knowledge Based Automatic Regions-of-Interest (ROI) Selection in Scanned Documents for Digital Image Encryption

Conventional image-oriented cryptographic techniques lack the flexibility needed for content-specific security features such as the concealment of confidential information within a portion of a document. Content-specific security is particularly important for digital archival systems that store sensitive documents in the form of digital images. Recently, a novel image encryption scheme utilizing multiple levels of regions-of-interest (ROI) privileges for digital document encryption was developed to address the needs of modern digital document management systems. This image encryption scheme requires the selection of regions-ofinterest for encryption. The process of manually selecting regions can be time-consuming. This paper presents an automatic, regions-of-interest selection algorithm that utilizes an expert knowledge learning system to select regions of interest in a scanned document image for the purpose of minimizing human interaction time during the encryption process. Experimental results show that a high level of accuracy and significant timesaving benefits can be achieved using the proposed algorithm.