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Boostlet.js: Image processing plugins for the web via JavaScript injection

Authors :
Gaibor, Edward
Varade, Shruti
Deshmukh, Rohini
Meyer, Tim
Geshvadi, Mahsa
Kim, SangHyuk
Narayanappa, Vidhya Sree
Haehn, Daniel
Publication Year :
2024

Abstract

Can web-based image processing and visualization tools easily integrate into existing websites without significant time and effort? Our Boostlet.js library addresses this challenge by providing an open-source, JavaScript-based web framework to enable additional image processing functionalities. Boostlet examples include kernel filtering, image captioning, data visualization, segmentation, and web-optimized machine-learning models. To achieve this, Boostlet.js uses a browser bookmark to inject a user-friendly plugin selection tool called PowerBoost into any host website. Boostlet also provides on-site access to a standard API independent of any visualization framework for pixel data and scene manipulation. Web-based Boostlets provide a modular architecture and client-side processing capabilities to apply advanced image-processing techniques using consumer-level hardware. The code is open-source and available.<br />Comment: 5 pages, 5 figures

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2405.07868
Document Type :
Working Paper