Centro UTN CInApTIC (Centro de Investigación Aplicada a las TIC)

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Author: search.filters.author.Rodrigues da Fonseca, ClaudioSubject: search.filters.subject.image processing

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    Low-cost image and video processing using high-performance middleware in single-board computers with open internet standards
    (2020-02-03) Pérez, Carlos Alejandro; Cleva, Mario Sergio; Liska, Diego Orlando; Rodrigues da Fonseca, Claudio; Aquino, Dominga Concepción
    Image processing is becoming ubiquitous in many activities. This kind of systems use industry-standard libraries, such as OpenCV, and GPGPU techniques such as CUDA and OpenCL. Nowadays, these are being ported to many computing platforms, offering significant processing power even in devices with limited resources. However, the only model that is truly ubiquitous, is the web itself. Modern browsers feature quite complex internals and offer sophisticated development and profiling tools, in order to offer the best user experience. Introduction of HTML5 allows Realtime video and image manipulation, in browser space, without any plugin. In addition, Wasm (web assembly) Javascript execution engine provides fastest possible performance by means of highly customized compiler and runtime, in almost any browser, including embedded ones. This paper presents an image processing system, architected as a modular web application, using only Raspberry PIs with a compact but fast middleware server, that performs all image operations in browser space by means of web assemblies. All components, including database support, can run in a single board, providing image and video processing speeds that match, or surpass, their native compiled C counterparts on the same platform. This solution has a very low cost, that fits with emerging markets, making it ideal for LATAM scenarios.
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    A cloud-based and flexible architecture for beans images processing
    (2023-06-04) Villaverde, Jorge; Aquino, Dominga Concepción; Rodrigues da Fonseca, Claudio
    Food quality is a paramount feature in agriculture technology, analyzing and classifying properly grains requires specialized work (Gomes and Leta, 2012). Nowadays, advanced computer vision technologies are available in vast life environments, however they require a software intensive approach to acquire and process a large amount of data at an acceptable level. In parallel, cloud-based services became full featured and highly available through different types of data networks. These advances together empower the Industry 4.0 solutions to accomplish flexible needs in modern factories. In this work we present an extensible architecture that allows decentralization of the digital image processing suitable in food quality context. We integrate modern computer technologies to decrease the latency between the Edge of image acquisition and Data Centers, leveraging IIoT technologies into the food quality control systems. This approach lets the end user capture images using low or high technology cameras and process them using cloud based technologies. The proposed approach, also, describes architectural components that allow an easy way of adding and combining new components for automatic image processing.