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Forensic Reconstruction of Severely Degraded License Plates

NCJ Number
309857
Journal
Electronic Imaging Volume: 31 Dated: 2019 Pages: 529-1 - 529-7
Date Published
January 2019
Length
7 pages
Annotation

This paper presents a convolutional neural network-based approach to identify the contents of low-quality images of license plates, with implications for criminal forensics investigations.

Abstract

Forensic investigations often have to contend with extremely low-quality images that can provide critical evidence. Recent work has shown that, although not visually apparent, information can be recovered from such low-resolution and degraded images. The authors present a CNN-based approach to decipher the contents of low-quality images of license plates. Evaluation on synthetically-generated and real-world images, with resolutions ranging from 10 to 60 pixels in width and signal-to-noise ratios ranging from –3:0 to 20:0 dB, shows that the proposed approach can localize and extract content from severely degraded images, outperforming human performance and previous approaches. (Published Abstract Provided)

Date Published: January 1, 2019