Abstract
Leaf vein is one of the most important and complex feature of the leaf used in automatic plant identification system for automatic classification and identification of plant species. Leaves of different species have different characteristic features which help in classification of specific plant species. These features help the botanists in identifying the key species of the plants from its leaf images more accurately. Vein feature is one of the most important complex features of leaf in plant species. In this paper we proposed a new feature extraction model, to extract the vein features from the leaf images. The proposed system using Hough lines stems the extraction of vein feature from the leaf images by plotting the lines over the first degree veins. Angle of lines from the primary vein to the secondary vein is considered as the input parameter for processing the extracted vein features. The centroid vein angle is considered to be the primary feature. The vein feature was given as the input to the neural network for efficient classification and the results were tested with 15 species of plants taken from “leafilia” data sets.
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Web source: Leafsnap Leafgui
Dataset: Leafilia, A semi-automatic plant recognition system developed by CDAC, Pune, India
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Sibi Chakkaravarthy, S., Sajeevan, G., Kamalanaban, E., Varun Kumar, K.A. (2016). Automatic Leaf Vein Feature Extraction for First Degree Veins. In: Thampi, S., Bandyopadhyay, S., Krishnan, S., Li, KC., Mosin, S., Ma, M. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 425. Springer, Cham. https://doi.org/10.1007/978-3-319-28658-7_49
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DOI: https://doi.org/10.1007/978-3-319-28658-7_49
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