|Title||Expert knowledge based automatic regions-of-interest (ROI) selection in scanned documents for digital image encryption|
|Publication Type||Conference Paper|
|Year of Publication||2006|
|Authors||Wong, A., and W. Bishop|
|Conference Name||3rd Canadian Conference on Computer and Robot Vision|
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.