The semisynthetic ground truth generation consists of the following stages: (1) dirt particle segmentation and database generation, (2) background generation to fill the holes left by removed dirt particles, and (3) random scattering of the dirt particle images and creation of the corresponding ground truth image.
Mar 6, 2013
semisynthetic method for generating the ground truth was developed. This paper introduces the algorithm for the purpose. It is shown how the background for dirt.
In the evaluation of dirt inclusions in paper, the attention is paid not only to the quantity of dirt but also to the type of dirt particles.
Aug 6, 2017 · In the evaluation of dirt inclusions in paper, the attention is paid not only to the quantity of dirt but also to the type of dirt particles.
Automatic classification methods can be designed for the task, but there should also exist proper evaluation data to truthfully compare the methods. For such ...
Publications · Semisynthetic ground truth for dirt particle counting and classification methods ...
To avoid manual annotation, dry pulp sheets with a single dirt type in each were exploited to generate semisynthetic images with the ground truth information.
Semisynthetic ground truth for dirt particle counting and classification methods. Semisynthetic ground truth for dirt particle counting and classification ...
2020. Framework for developing image-based dirt particle classifiers ... Semisynthetic Ground Truth for Dirt Particle Counting and Classification Methods.
... after Trump's dirt ... 2016. Semisynthetic ground truth for dirt particle counting and classification methods. Peer-reviewed. 2011. Previous. 1 2