New object-oriented segmentation algorithm based on the CNN paradigm
Giuseppe Grassi, Eugenio Di Sciascio, Luigi Alfredo Grieco, Pietro Vecchio · IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing · 2006
This paper illustrates a new object-oriented segmentation algorithm based on the cellular neural network (CNN) paradigm. The approach, which exploits rigorous model of the image contours, presents two remarkable features: 1) it provides more accurate segmented objects than the ones obtained by other CNN-based techniques; 2) it makes use of CNN templates that take into account the hardware characteristics imposed by the CNNUM. Results carried out for benchmark video sequences highlight the capabilities of the proposed technique.