An Algorithm for Adaptive Mean Filtering and Its Hardware Implementation

Noise due to the sensor and the electronics of a camera is an undesirable issue in any machine vision application. Such noise tends to corrupt images and to obstruct any further analysis. An algorithm to detect and cancel such noise, using statistical methods, is presented in this paper. The proposed algorithm is an adaptive mean filter, which filters out image regions that are found to be noise corrupted. The efficiency of the proposed filter was examined both qualitatively and quantitatively, by software simulation in several noisy conditions. The main advantage of the filter in hand is that it is appropriate for hardware implementation and can be easily incorporated to smart cameras. The hardware implementation of the filter is also presented in this paper. This implementation aims at time critical applications such as machine vision, inspection and visual surveillance. Ioannis Gasteratos holds a Diploma in Electrical Engineering from the Department of Electrical and Computer Engineering, Democritus University of Thrace, Greece, 2004. His research interests include digital VLSI design, computer architectures and artificial intelligence. He is a member of the IEEE, and a member of the Technical Chamber of Greece (TEE). Antonios Gasteratos is a Lecturer of Robotics in the Department of Production and Management, Democritus University of Thrace, Greece. He holds a PhD from the Department of Electrical and Computer Engineering, Democritus University of Thrace, Greece, 1999. During 2001–2003 he was a visiting Assistant Professor in the Department of Electrical and Computer Engineering, Democritus Univesrsity of Thrace. He serves as a reviewer to numerous of Scientific Journals and International Conferences. His research interests are mainly in computer and robot vision and sensory data fusion. He is a member of the IEEE, the IAPR, the EURASIP, the Hellenic Society of Artificial Intelligence (SETN) and the Technical Chamber of Greece (TEE). Ioannis Andreadis received the Diploma Degree from the Department of Electrical & Computer Engineering, DUTH, Greece, in 1983 and the MSc and PhD Degrees from the University of Manchester Institute of Science & Technology, UK, in 1985 and 1989, respectively. His research interests are mainly in Intelligent Systems, Machine Vision and VLSI based computing architectures. He joined the Department of Electrical & Computer Engineering, DUTH in 1993. He is a member of the Editorial Board of the Pattern Recognition Journal, TEE and IEEE.