Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods

The work is intended to study the following important aspects of document image processing and develop new methods. (1) Segmentation ofdocument images using adaptive interval valued neuro-fuzzy method. (2) Improving the segmentation procedure using Simulated Annealing technique. (3) Development of optimized compression algorithms using Genetic Algorithm and parallel Genetic Algorithm (4) Feature extraction of document images (5) Development of IV fuzzy rules. This work also helps for feature extraction and foreground and background identification. The proposed work incorporates Evolutionary and hybrid methods for segmentation and compression of document images. A study of different neural networks used in image processing, the study of developments in the area of fuzzy logic etc is carried out in this work

Parallel Genetic Algorithm for Document Image Compression Optimization

This work proposes a parallel genetic algorithm for compressing scanned document images. A fitness function is designed with Hausdorff distance which determines the terminating condition. The algorithm helps to locate the text lines. A greater compression ratio has achieved with lesser distortion

Building Digital. Repository Of Project Reports: A Proposal for cusat

The effective organization and utilisation of resources produced by the students, faculty and research scholars in university departments assume greater significance. Institutional repositories are developed by many institutions to provide resources and materials that support students in their studies. The present study recognizes the value of such a repository in the Engineering and Technology discipline in Cochin University of Science and Technology. The paper explains the need for a digital repository ofproject reports. The authors present a modelfor digital repository, and the organization.and administration of such a repository. The study also analyses the various other factors associated with the proposed depository.