Detalhes bibliográficos
Ano de defesa: |
2021 |
Autor(a) principal: |
Maciel, Roberto Wagner Santos |
Orientador(a): |
Dantas, Daniel Oliveira |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
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Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Não Informado pela instituição
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Programa de Pós-Graduação: |
Pós-Graduação em Ciência da Computação
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: |
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Palavras-chave em Inglês: |
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Área do conhecimento CNPq: |
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Link de acesso: |
https://ri.ufs.br/jspui/handle/riufs/19546
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Resumo: |
Medical imaging is used in clinics to support the diagnosis and treatment of disease. Developing effective computer vision algorithms for image processing is a challenging task that requires a significant amount of time invested in the prototyping phase. There are visual programming systems that seek to facilitate prototyping. Other systems that allow parallel processing try to make it possible to handle very large image datasets that demand a high execution time. Workflow systems, on the other hand, have become popular tools because they allow you to develop algorithms as a collection of function blocks that can be graphically linked to input and output pipelines. This helps to reduce the learning curve for beginning programmers. Finally, there are systems that make programming easier and increase productivity through automatic code generation. VisionGL is an open source library that facilitates programming through automatic generation of C++ wrapper code. The wrapper code is responsible for calling parallel image processing functions or shaders on CPUs using OpenCL and on GPUs using OpenCL, GLSL and CUDA. VGLGUI is a graphical user interface for image processing that will allow visual workflow programming for parallel image processing, through VisionGL functions for automatic wrapper code generation and optimization of image transfers between RAM and GPU. This research aims to present the architecture description of VGLGUI in multiple views, using the ISO / IEC / IEEE 42010: 2011 architectural standard, the 4 + 1 View Model of Software Architecture and the Unified Modeling Language (UML). It also aims to describe and create the VGLGUI workflow interpreter, and demonstrate the results of two image processing pipelines on two different platforms: with the Python language using the OpenCV library running on the CPU, and; with the VGLGUI interpreter running on the GPU. |