
We present an hierarchical approach to segment images of yeast cells based on watershed and space-scale analysis. Yeasts belong to an important fungi class and the performance of bioreactors and other chemical processes are greatly influenced by their morphological character. The method proposed is capable of segmenting yeast cells based on the analysis of survival time, shape and gray-scale features of the Tree of Critical Lakes. We show experimental results for one group of yeast images obtained from the School of Food Engineering at Unicamp, Brazil. Preliminary comparison shows that the proposed method provides cells with area 10% lower than traditional approach, as well as its contours preserved.
[INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL]
[INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL]
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
