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....
When computer vision experts evaluate algorithms, they often focus on segmentation quality and optimisation of resources. On the other hand, they often neglect simplicity and interactivity....
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...
In this paper, a machine learning method was employed based on a statistical model of image pixels, learned from sample images by human training. The observation underlying to this class of segmentation methods is that image...
The objective of the present study was to develop an image analysis method to measure the area of the surface of cheese slices occupied by gas holes (or other types of mechanical openness) for use...