Cheng, Hui, Ph.D., Purdue University, August, 1999. Document Image Segmentation and Compression. Major Professor: Charles A. Bouman. In the first part of this research, we propose an image segmentation algorithm called the trainable sequential MAP (TSMAP) algorithm. The TSMAP algorithm is based on a multiscale Bayesian approach. It has a novel multiscale context model which can capture complex ...

Watermarking is an important copyright protection technology which generally embeds the identity information into carrier imperceptibly. Then can be extracted to prove from watermarked even after suffering various attacks. Most of existing watermarking technologies take nature images as carriers. Different natural images, document are not so rich in color and texture, thus have less redundant c...

Document Image Decoding (DID) refers to the process of document recognition within a communication theory framework. In this framework, a logical document structure is a message communicated by encoding the structure as an ideal image, transmitting the ideal image through a noisy channel, and decoding the degraded image into a logical structure as close to the original message as possible, on a...

In this paper we present an image mosaicing method for camera-captured document images. Our method is unique in not restricting the camera position, thus allowing greater flexibility than scanner-based or fixed-camera-based approaches. To accommodate for the perspective distortions introduced by varying poses, we implement a two-step image registration process that relies on accurately computin...

This paper presents a new adaptive approach for the binarization and enhancement of degraded documents. The proposed method does not require any parameter tuning by the user and can deal with degradations which occur due to shadows, non-uniform illumination, low contrast, large signal-dependent noise, smear and strain. We follow several distinct steps: a pre-processing procedure using a low-pas...

A system was developed able to retrieve specific documents from a document collection. In this system the query is given in text by the user and then transformed into image. Appropriate features were in order to capture the general shape of the query, and ignore details due to noise or different fonts. In order to demonstrate the effectiveness of our system, we used a collection of noisy docume...