Fast evaluation of segmentation quality with parallel computing
Abstract:
In digital image processing and computer vision, a fairly frequent task is the performance comparison of different algorithms on enormous image databases. This task is usually time-consuming and tedious, such that any kind of tool to simplify this work is welcome. To achieve an efficient and more practical handling of a normally tedious evaluation, we implemented the automatic detection system, with the help of MATLAB®’s Parallel Computing Toolbox™. The key parts of the system have been parallelized to achieve simultaneous execution and analysis of segmentation algorithms on the one hand and the evaluation of detection accuracy for the nonforested regions, such as a study case, on the other hand. As a positive side effect, CPU usage was reduced and processing time was significantly decreased by 68.54% compared to sequential processing (i.e., executing the system with each algorithm one by one).
Año de publicación:
2017
Keywords:
Fuente:
Tipo de documento:
Other
Estado:
Acceso abierto
Áreas de conocimiento:
- Visión por computadora
- Ciencias de la computación
Áreas temáticas:
- Ciencias de la computación