DocumentCode
2415620
Title
Implementing the grayscale wave metric on a cellular array processor chip
Author
Hillier, Dániel ; Dudek, Piotr
Author_Institution
Jedlik Lab., Peter Pazmany Catholic Univ., Budapest
fYear
2008
fDate
14-16 July 2008
Firstpage
120
Lastpage
124
Abstract
Algorithms designed for machine vision applications such as medical imaging, surveillance, etc., very often require some kind of comparison between images. The non-linear wave metric can measure both the shape and the area difference between two objects in one single operation. We present the implementation of the wave metric on the SCAMP chip that combines the benefits of a highly selective metric with high speed, efficient execution.
Keywords
cellular neural nets; computer vision; microprocessor chips; neural chips; SCAMP chip; cellular array processor chip; cellular nonlinear network; grayscale wave metric; machine vision; wave computing; Area measurement; Biomedical imaging; Cellular networks; Cellular neural networks; Gray-scale; Image processing; Machine vision; Pixel; Shape measurement; Surveillance; Cellular Nonlinear Networks; SCAMP; wave computing; wave metric;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and Their Applications, 2008. CNNA 2008. 11th International Workshop on
Conference_Location
Santiago de Compostela
Print_ISBN
978-1-4244-2089-6
Electronic_ISBN
978-1-4244-2090-2
Type
conf
DOI
10.1109/CNNA.2008.4588662
Filename
4588662
Link To Document