Image disparity in cross-spectral face recognition: mitigating camera and atmospheric effects

Zhicheng Cao; Natalia A. Schmid; Xin Li

doi:10.1117/12.2225149

12 May 2016 Image disparity in cross-spectral face recognition: mitigating camera and atmospheric effects

Zhicheng Cao, Natalia A. Schmid, Xin Li

Proceedings Volume 9844, Automatic Target Recognition XXVI; 98440Z (2016) https://doi.org/10.1117/12.2225149
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

Matching facial images acquired in different electromagnetic spectral bands remains a challenge. An example of this type of comparison is matching active or passive infrared (IR) against a gallery of visible face images. When combined with cross-distance, this problem becomes even more challenging due to deteriorated quality of the IR data. As an example, we consider a scenario where visible light images are acquired at a short standoff distance while IR images are long range data. To address the difference in image quality due to atmospheric and camera effects, typical degrading factors observed in long range data, we propose two approaches that allow to coordinate image quality of visible and IR face images. The first approach involves Gaussian-based smoothing functions applied to images acquired at a short distance (visible light images in the case we analyze). The second approach involves denoising and enhancement applied to low quality IR face images. A quality measure tool called Adaptive Sharpness Measure is utilized as guidance for the quality parity process, which is an improvement of the famous Tenengrad method. For recognition algorithm, a composite operator combining Gabor filters, Local Binary Patterns (LBP), generalized LBP and Weber Local Descriptor (WLD) is used. The composite operator encodes both magnitude and phase responses of the Gabor filters. The combining of LBP and WLD utilizes both the orientation and intensity information of edges. Different IR bands, short-wave infrared (SWIR) and near-infrared (NIR), and different long standoff distances are considered. The experimental results show that in all cases the proposed technique of image quality parity (both approaches) benefits the final recognition performance.

Citation Download Citation

Zhicheng Cao, Natalia A. Schmid, and Xin Li "Image disparity in cross-spectral face recognition: mitigating camera and atmospheric effects", Proc. SPIE 9844, Automatic Target Recognition XXVI, 98440Z (12 May 2016); https://doi.org/10.1117/12.2225149

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available