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Publication detail
DVOŘÁČEK, P. SEKANINA, L.
Original Title
Evolutionary Approximation of Edge Detection Circuits
Type
conference paper
Language
English
Original Abstract
Approximate computing exploits the fact that many applications are inherently error resilient which means that some errors in their outputs can safely be exchanged for improving other parameters such as energy consumption or operation frequency. A new method based on evolutionary computing is proposed in this paper which enables to approximate edge detection circuits. Rather than evolving approximate edge detectors from scratch, key components of existing edge detector are replaced by their approximate versions obtained using Cartesian genetic programming (CGP). Various approximate edge detectors are then composed and their quality is evaluated using a database of images. The paper reports interesting edge detectors showing a good tradeoff between the quality of edge detection and implementation cost.
Keywords
Edge detection circuits, Cartesian genetic programming, Evolutionary computation
Authors
DVOŘÁČEK, P.; SEKANINA, L.
Released
30. 3. 2016
Publisher
Springer International Publishing
Location
Berlin
ISBN
978-3-319-30667-4
Book
19th European Conference on Genetic programming
Edition
Lecture Notes in Computer Science
Pages from
19
Pages to
34
Pages count
16
URL
https://www.fit.vut.cz/research/publication/10998/
BibTex
@inproceedings{BUT130921, author="Petr {Dvořáček} and Lukáš {Sekanina}", title="Evolutionary Approximation of Edge Detection Circuits", booktitle="19th European Conference on Genetic programming", year="2016", series="Lecture Notes in Computer Science", volume="9594", pages="19--34", publisher="Springer International Publishing", address="Berlin", doi="10.1007/978-3-319-30668-1\{_}2", isbn="978-3-319-30667-4", url="https://www.fit.vut.cz/research/publication/10998/" }