Color and Edge-Aware Adversarial Image Perturbations
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Authors
Bassett, Robert
Graves, Mitchell
Reilly, Patrick
Subjects
Advisors
Date of Issue
2021-03-22
Date
22 March 2021
Publisher
ArXiv
Language
Abstract
Adversarial perturbation of images, in which a source image is deliberately modified with the intent of causing a classifier to misclassify the image, provides important insight into the robustness of image classifiers. In this work we develop two new methods for constructing adversarial perturbations, both of which are motivated by minimizing human ability to detect changes between the perturbed and source image. The first of these, the Edge-Aware method, reduces the magnitude of perturbations permitted in smooth regions of an image where changes are more easily detected. Our second method, the Color-Aware method, performs the perturbation in a color space which accurately captures human ability to distinguish differences in colors, thus reducing the perceived change. The Color-Aware and Edge-Aware methods can also be implemented simultaneously, resulting in image perturbations which account for both human color perception and sensitivity to changes in homogeneous regions. Because Edge-Aware and Color-Aware modifications exist for many image perturbations techniques, we also focus on computation to demonstrate their potential for use within more complex perturbation schemes. We empirically demonstrate that the Color-Aware and Edge-Aware perturbations we consider effectively cause misclassification, are less distinguishable to human perception, and are as easy to compute as the most efficient image perturbation techniques. Code and demo
available at https://github.com/rbassett3/Color-and-Edge-Aware-Perturbations.
Type
Preprint
Description
Series/Report No
Department
Organization
Identifiers
NPS Report Number
Sponsors
Office of Naval Research’s Science of Autonomy Program
Funder
N0001420WX01523
Format
11 p.
Citation
Bassett, Robert, Mitchell Graves, and Patrick Reilly. "Color and Edge-Aware Adversarial Image Perturbations." arXiv preprint arXiv:2008.12454 (2020).
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.