Stochastic Edge Detection for Fine-Grained Progressive Precision

Author

Youngwook Lee
Kyung Ki Kim
Yong Bin Kim
Minsu Choi, Missouri University of Science and TechnologyFollow

Abstract

Stochastic Computing (SC) is a method of performing an operation by expressing a probability in a bitstream. This format is simpler than the format of conventional binary computing and can be implemented in hardware with fewer resources. In addition, by using a Low-Discrepancy (LD) sequence, faster convergence can be derived. This paper shows the experimental results of applying SC using LD sequence to edge detection algorithms including Sobel and Roberts Cross to analyze the progressive precision performance and scalability.

Recommended Citation

Y. Lee et al., "Stochastic Edge Detection for Fine-Grained Progressive Precision," Proceedings - International SoC Design Conference 2021, ISOCC 2021, pp. 119 - 120, Institute of Electrical and Electronics Engineers, Jan 2021.

The definitive version is available at https://doi.org/10.1109/ISOCC53507.2021.9614036

Department(s)

Electrical and Computer Engineering

Comments

Ministry of Trade, Industry and Energy, Grant P0008751

Keywords and Phrases

edge detectors; low discrepancy sequence; progressive precision; Stochastic computing

International Standard Book Number (ISBN)

978-166540174-6

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Jan 2021