Computational methods for image processing understanding and recognition

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In today's world there is an increasing demand for digital image processing and understanding for the purpose of automation of information systems such as extraction, classification, search, and retrieval. In the sub-discipline of digital document processing, the amount of paper documents that must be processed by human in many organizations both commercial and governmental offices for archival purposes is huge and growing every day. There is an urgent need for automation of this process. For clean printed documents, the problem could be considered as already solved at least in theory. However, the difficulty is in dealing with unstructured, unconstrained handwritten documents that could be subjected to degradation over time or noise and artifacts due to the scanning process. Thus, the research on document image processing and understanding spans a wide range of sub-disciplines of computer science including image processing, pattern recognition, natural language processing, machine learning, database systems, and information retrieval. The objective of this research is to study the general problem of computational methods for digital image processing and understanding. This includes digital document processing as a major component as well as medical imaging, biometrics, and related topics. New generation of techniques for computational image processing should combine new development in image modeling with intelligent approaches based on human vision principle, learning based methods, and pattern recognition techniques to develop intelligent tools. Recently, computational intelligence techniques such as neural networks or evolutionary algorithms have been employed in various applications in the area of medical imaging. Approaches based on computational intelligence have been shown to be advantageous compared to classical approaches. Examples where this research would be useful are in document image processing, medical imaging, security, and biometric applications.