Abstract: Image analysis can be used to characterize granular populations in many processes in food industry or in agricultural engineering. Either global or individual parameters can be extracted from the image. However, granular products may appear agglomerate on the image, bringing biasing on individual parameters. Combining statistical and neural network technics enables the build of a system which can recognize if products are agglomerate or not. To process images after agglomerates detection, two approaches have been studied: the first is based on erosion, followed by conditional dilation with the original image; the second takes advantage of the graph's properties of the agglomerate's skeleton.!12
展开▼
