DocumentCode
2560686
Title
A new object-oriented segmentation algorithm based on CNNs - part I: edge extraction
Author
Grass, Giuseppe ; Di Sciascio, Eugenio ; Grieco, Alfredo L. ; Vecchio, Pietro
Author_Institution
Dipt. Ingegneria Innovazione, Univ. di Lecce, Italy
fYear
2005
fDate
28-30 May 2005
Firstpage
158
Lastpage
161
Abstract
By using the CNN paradigm, this paper and the companion one (Grasi et al., 2005) present a new object-oriented segmentation algorithm, which takes into account the hardware characteristics imposed by the CNNUM. In particular, by exploiting a rigorous model of the image contours, this paper focuses on CNN algorithms for edge extraction. Simulation results show that the approach provides more accurate edge extractions than the ones obtained by other CNN-based techniques.
Keywords
cellular neural nets; edge detection; image segmentation; object detection; cellular neural networks universal machine; edge extraction; hardware characteristics; image contours; object-oriented segmentation; Cellular neural networks; Computer networks; Engines; Hardware; Image processing; Image segmentation; MPEG 4 Standard; Object oriented modeling; Turing machines; Video sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and Their Applications, 2005 9th International Workshop on
Print_ISBN
0-7803-9185-3
Type
conf
DOI
10.1109/CNNA.2005.1543185
Filename
1543185
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