Implementation of Blur Image to Sharp Image Conversion using Laplacian Approach

Aravinth, S. S.; Gopi, Arepalli Peda; Chowdary, Gummadi Likhith; Bhagavath, Kvr; Srinivas, Desaboina Rahul

doi:10.1109/icosec54921.2022.9952148

Search citation statements

Order By: Relevance

Paper Sections

Select...

Photographic and Pose-specific Tests1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

2024

Publication Types

Select...

Article1

Other1

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Laplacian-based approaches are popular for blur detection [36,37]. We have used a variance of the Laplacian values across the entire image to detect blur values [38].…”

Section: Photographic and Pose-specific Testsmentioning

confidence: 99%

An Open-Source Face-Aware Capture System

Sarker,

Hossain,

Venkataswamy

et al. 2024

Electronics

View full text Add to dashboard Cite

Poor-quality facial images pose challenges in biometric authentication, especially in passport photo acquisition and recognition. This study proposes a novel and open-source solution to address these issues by introducing a real-time facial image quality analysis utilizing computer vision technology on a low-power single-board computer. We present an open-source complete hardware solution that consists of a Jetson processor, a 16 MP autofocus RGB camera, a custom enclosure, and a touch sensor LCD for user interaction. To ensure the integrity and confidentiality of captured facial data, Advanced Encryption Standard (AES) is used for secure image storage. Using the pilot data collection, the system demonstrated its ability to capture high-quality images, achieving 98.98% accuracy in storing images of acceptable quality. This open-source, readily deployable, secure system offers promising potential for diverse real-time applications such as passport verification, security systems, etc.

show abstract

“…Laplacian-based approaches are popular for blur detection [36,37]. We have used a variance of the Laplacian values across the entire image to detect blur values [38].…”

Section: Photographic and Pose-specific Testsmentioning

confidence: 99%