Paper infrared image retrieval of power equipment based on perceptual hash and SURF

Zhou, Guohui; Xiao, Lixin; Pei, Xingyu; Li, Chenxi; Qin, Huiping; Zhang, Jinpeng; Fang, Zhiyu

doi:10.1109/icait.2017.8388951

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…The perceptual picture hashing plan (Wang et al, 2015) incorporates a hash age calculation, an altering discovery calculation and an altering limitation algorithm. 1) Hash age calculation: The hash age calculation comprises of two phases (Zhou et al, 2017) include extraction and pressure and coding. The procedure is appeared in Figure 4.…”

Section: Perceptual Image Hashingmentioning

confidence: 99%

An Innovative Approach to Solve Healthcare Issues Using Big Data Image Analytics

Ramésh¹,

Udayakumar²,

Srihari³

et al. 2021

International Journal of Big Data and Analytics in Healthcare

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The increasing adoption of transmission of medical images through internet in healthcare has led to several security threats to patient medical information. Permitting quiet data to be in peril may prompt hopeless harm, ethically and truly to the patient. Accordingly, it is important to take measures to forestall illicit access and altering of clinical pictures. This requests reception of security components to guarantee three fundamental security administrations – classification, content-based legitimacy, and trustworthiness of clinical pictures traded in telemedicine applications. Right now, inside created symmetric key cryptographic capacities are utilized. Pictorial model-based perceptual image hash is used to provide content-based authentication for malicious tampering detection and localization. The presentation of the projected algorithm has been evaluated using performance metrics such as PSNR, normalized correlation, entropy, and histogram analysis, and the simulation results show that the security services have been achieved effectively.

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Section: Perceptual Image Hashingmentioning

confidence: 99%