Computational Intelligence in Image Processing - Tapa blanda

Acerca del autor

Amitava Chatterjee is an Associate Professor in the Dept. of Electrical Engineering of Jadavpur University in Kolkata, India. He teaches electrical engineering and his research interests include fuzzy control, image processing, robotics, signal processing and stochastic optimization. He has visited overseas on prestigious scholarships and fellowships and has given invited lectures in India, Japan and France. He presently serves as an Associate Editor of the IEEE Transactions on Vehicular Technology. Patrick Siarry is a Professor of Automatics and Informatics at the University of Paris-Est Créteil, where he leads the Image and Signal Processing team in the Laboratoire Images, Signaux et Systèmes Intelligents (LiSSi). He has considerable teaching and research experience in the areas of signal processing, control, artificial intelligence, operations research, and optimization. He presently serves as an Associate Editor of the journal Information Sciences and the journal Engineering Applications of Artificial Intelligence.

De la contraportada

Computational intelligence based techniques have firmly established themselves as viable, alternate, mathematical tools for more than a decade. They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consumer electronics, robotics, finance, manufacturing systems, electric power systems, and power electronics. Image processing is also an extremely potent area which has attracted the atten­tion of many researchers who are interested in the development of new computational intelligence-based techniques and their suitable applications, in both research prob­lems and in real-world problems.

Part I of the book discusses several image preprocessing algorithms; Part II broadly covers image compression algorithms; Part III demonstrates how computational intelligence-based techniques can be effectively utilized for image analysis purposes; and Part IV shows how pattern recognition, classification and clustering-based techniques can be developed for the purpose of image inferencing. The book offers a unified view of the modern computational intelligence tech­niques required to solve real-world problems and it is suitable as a reference for engineers, researchers and graduate students.