Josef Kittler

Josef Kittler has been a Research Assistant in the Engineering Department of Cambridge University (1973--75), SERC Research Fellow at the University of Southampton (1975-77), Royal Society European Research Fellow, Ecole Nationale Superieure des Telecommuninations, Paris (1977--78), IBM Research Fellow, Balliol College, Oxford (1978--80), Principal Research Associate, SERC Rutherford Appleton Laboratory (1980--84) and Principal Scientific Officer, SERC Rutherford Appleton Laboratory (1985). He also worked as the SERC Coordinator for Pattern Analysis (1982), and was Rutherford Research Fellow in Oxford University, Dept. Engineering Science (1985). He joined the Department of Electrical Engineering of Surrey University in 1986 as a Reader in Information Technology, and became Professor of Machine Intelligence in 1991. He gained the title Distinguished Professor in 2004. He is the Course Organiser for the MSc Course in Signal Processing and Machine Intelligence. He teaches Machine Intelligence, Pattern Recognition and Advanced Signal Processing.| He worked on various theoretical aspects of Pattern Recognition, Image Analysis and Computer Vision, and on many applications including System Identification, Automatic Inspection, ECG diagnosis, Mammographic Image Interpretation, Remote Sensing, Robotics, Speech Recognition, Character Recognition and Document Processing, Image Coding, Biometrics, Image and Video Database Retrieval, Surveillance. Contributions to statistical pattern recognition include k-nearest neighbour methods of pattern classification, feature selection, contextual classification, probabilistic relaxation and most recently to multiple expert fusion. In computer vision the major contributions include robust statistical methods for shape analysis and detection, motion estimation and segmentation, and image segmentation by thresholding and edge detection. He has co-authored a book with the title `Pattern Recognition: a statistical approach' published by Prentice-Hall. He has published more than 500 papers.

• Website