Boostlet.js: Image processing plugins for the web via JavaScript injection
This addresses the problem of time-consuming integration for developers and users of web-based image processing tools, though it appears incremental as a modular extension of existing web technologies.
The researchers tackled the challenge of integrating web-based image processing tools into existing websites by developing Boostlet.js, an open-source JavaScript framework that enables additional functionalities like kernel filtering, image captioning, and segmentation through a browser bookmark injection system.
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.