A high throughput system for intelligent watermarking of bi-tonal images
Applied Soft Computing
Gaussian mixture modeling for dynamic particle swarm optimization of recurrent problems
Proceedings of the 14th annual conference on Genetic and evolutionary computation
| Hi-index | 0.00 |
In our society, large volumes of documents are exchanged on a daily basis. Since documents can easily be scanned, modified and reproduced without any loss in quality, unauthorized use and modification of documents is of major concern. An authentication watermark embedded into a document as an invisible, fragile mark can be used to detect illegal document modification. However, the authentication watermark can only be used to determine whether documents have been tampered with, and additional protection may be needed to prevent unauthorized use and distribution of those documents. A solution to this problem is a two-level, multipurpose watermark. The first level watermark is an authentication mark used to detect document tampering, while the second level watermark is a robust mark, which identifies the legitimate owner and/or user of specific document. This dissertation introduces a new adaptive two-level multipurpose watermarking scheme suitable for binary document images, such as scanned text, figures, engineering and road maps, architectural drawings, music scores, and handwritten text and sketches. This watermarking scheme uses uniform quantization and overlapped embedding to add two watermarks, one robust and the other fragile, into a binary document image. The two embedded watermarks serve different purposes. The robust watermark carries document owner or document user identification, and the fragile watermark confirms document authenticity and helps detect document tampering. Both watermarks can be extracted without accessing the original document image. The proposed watermarking scheme adaptively selects an image partitioning block size to optimize the embedding capacity, the image permutation key to minimize watermark detection error, and the size of local neighborhood in which modification candidate pixels are scored to minimize visible distortion of watermarked documents. Modification candidate pixels are scored using a novel, objective metric called the Structural Neighborhood Distortion Measure (SNDM). Experimental results confirm that this watermarking scheme, which embeds watermarks by modifying image pixels based on their SNDM scores, creates smaller visible document distortion than watermarking schemes which base watermark embedding on any other published pixel scoring method. Document tampering is detected successfully and the robust watermark can be detected even after document tampering renders the fragile watermark undetectable.