We propose a simple segmentation framework based on classification and supervised incremental learning. A statistical model of pixel classes is learnt by incrementally adding new sample image patches to automatically-learned probability functions....
The objective of this study was to assess the association of particle size in TMR estimated using the Penn State Particle Separator with production of milk, fat, and protein on a representative sample of Ragusa...
The main problem of classi cation approaches is the long, tedious, human-intensive training phase. In our experience, an accurate image labelling can take several hours to an expert operator....
In this paper, we propose a fast approximate level set algorithm for the detection of microstructural features in food micrographs. Our approximation method is in the spirit of. Hence, we chose a user-assisted approach. Approximating...