A two-stage approach for leaf vein extraction

Hong FU, Zheni CHI

Research output: Chapter in Book/Report/Conference proceedingChapters

28 Citations (Scopus)

Abstract

Living plant recognition is a promising but challenging task in the fields of pattern recognition and computer vision. As an inherent trait, the leaf vein definitely contains the important information for plant species recognition despite of its complex modality. In this paper, an efficient two-stage approach is presented for leaf vein extraction. At the first stage, a preliminary segmentation based on the intensity histogram of the leaf image is carried out to estimate the rough regions of vein pixels. This is followed at the second stage by a fine checking using a trained artificial neural network (ANN) classifier. Ten features distilled from a window centered at the pixel are used as the input to train the ANN classifier. Compared with conventional edge detection methods, experimental results show that the proposed method is capable of extracting more precise venation modality of the leaf for the subsequent leaf recognition. Copyright © 2003 IEEE.
Original languageEnglish
Title of host publicationProceedings of 2003 International Conference on Neural Networks and Signal processing, ICNNSP'03
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages208-211
Volume1
ISBN (Print)0780377028, 9780780377028
DOIs
Publication statusPublished - 2003

Citation

Fu, H., & Chi, Z. (2003). A two-stage approach for leaf vein extraction. In Proceedings of 2003 International Conference on Neural Networks and Signal processing, ICNNSP'03 (Vol. 1, pp. 208-211). Piscataway, NJ: IEEE.

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