DOAJ Open Access 2017

Detection of leaf structures in close-range hyperspectral images using morphological fusion

Gladys Villegas Wenzhi Liao Ronald Criollo Wilfried Philips Daniel Ochoa

Lihat Sumber DOI

Abstrak

Close-range hyperspectral images are a promising source of information in plant biology, in particular, for in vivo study of physiological changes. In this study, we investigate how data fusion can improve the detection of leaf elements by combining pixel reflectance and morphological information. The detection of image regions associated to the leaf structures is the first step toward quantitative analysis on the physical effects that genetic manipulation, disease infections, and environmental conditions have in plants. We tested our fusion approach on Musa acuminata (banana) leaf images and compared its discriminant capability to similar techniques used in remote sensing. Experimental results demonstrate the efficiency of our fusion approach, with significant improvements over some conventional methods.

Topik & Kata Kunci

Mathematical geography. Cartography Geodesy

Penulis (5)

Gladys Villegas

Wenzhi Liao

Ronald Criollo

Wilfried Philips

Daniel Ochoa

Format Sitasi

APA MLA BibTeX

Villegas, G., Liao, W., Criollo, R., Philips, W., Ochoa, D. (2017). Detection of leaf structures in close-range hyperspectral images using morphological fusion. https://doi.org/10.1080/10095020.2017.1399673

Akses Cepat

Lihat di Sumber doi.org/10.1080/10095020.2017.1399673

Informasi Jurnal

Tahun Terbit: 2017
Sumber Database: DOAJ
DOI: 10.1080/10095020.2017.1399673
Akses: Open Access ✓