Automated High-Resolution Structure Analysis of Plant Root with a Morphological Image Filtering Algorithm

Research on rice (Oryza sativa) roots demands the automatic analysis of root architecture during image processing. It is challenging for a digital filter to identify from obscure and cluttered background. The original Frangi algorithm, presented by Alejandro F. in 1998, successful low-pass dedicated blood vessel enhancement. Considering similarity between vessels roots, algorithm applied outline roots. However, only enhances tube-like primary but erases lateral filtering. In this paper, an improved filtering (IFFA), designed plant proposed. Firstly, phenotyping system fulfill high-throughput acquisition. Secondly, multilevel thresholding, connected components labeling, width correction are used optimize output binary image. Thirdly, enhance local structure, Gaussian operator redesigned with truncated kernel, resulting more discernible Compared commercially available software, IFFA faster accurate, achieving pixel accuracy 97.48%. effective morphological approach segmentation further biological research. convincing that suitable different 2-D processing analysis.