Image-based automatic segmentation of leaf using clustering algorithm
Source abstract
Abstract
This paper proposes a productive strategy to separate the leaf area from different plant images. The image analysis in plants plays a critical job in reasonable and gainful farming. Plant image analysis is mainly used to record the plant development plant area and leaf zone etc. Plant leaf segmentation has become a significant task to be examined among these plant characters. For this reason, a strategy for leaf area segmentation from different plant images is made. In this paper we have proposed an algorithm which will segment plant on the basis of L*a*b colour spaces and cluster formation. When our proposed technique is compared to rosette tracker it was found that our proposed algorithm was more efficient in plant leaf segmentation. The results of our proposed algorithm are, accuracy is 79.23%, sensitivity is 85.84%, and specificity is 97.40%.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Leaf Properties and Growth Measurement · Smart Agriculture and AI · Greenhouse Technology and Climate Control
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References
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