Scanned leaves boundary detection based on the consistent one-class segmentation

The accurate segmentation of the leaf area on scanned digital images plays a crucial role in the automated evaluation of its morphological characteristics. We propose here a new algorithm for extracting leaf area from the digital images based on a combination of a parametric description of shadow and background areas in the color space by support vector data description (SVDD) and the structure transfer filtering method based on the gamma-normal probabilistic model. The combination of these methods allows us to consider color information as well as sharp changes in image intensity at the edges of a leaf.