[go: up one dir, main page]

Hämmerle et al., 2016 - Google Patents

Direct derivation of maize plant and crop height from low-cost time-of-flight camera measurements

Hämmerle et al., 2016

View HTML @Full View
Document ID
793200195932773909
Author
Hämmerle M
Höfle B
Publication year
Publication venue
Plant Methods

External Links

Snippet

Background In agriculture, information about the spatial distribution of crop height is valuable for applications such as biomass and yield estimation, or increasing field work efficiency in terms of fertilizing, applying pesticides, irrigation, etc. Established methods for …
Continue reading at link.springer.com (HTML) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10032Satellite or aerial image; Remote sensing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/0063Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
    • G06K9/00657Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/02Picture taking arrangements specially adapted for photogrammetry or photographic surveying, e.g. controlling overlapping of pictures
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/60Analysis of geometric attributes
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/04Interpretation of pictures
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00Details of systems according to groups G01S13/00, G01S15/00, G01S17/00

Similar Documents

Publication Publication Date Title
Hämmerle et al. Direct derivation of maize plant and crop height from low-cost time-of-flight camera measurements
Lin et al. Quality control and crop characterization framework for multi-temporal UAV LiDAR data over mechanized agricultural fields
Liang et al. In-situ measurements from mobile platforms: An emerging approach to address the old challenges associated with forest inventories
Paulus Measuring crops in 3D: using geometry for plant phenotyping
Liang et al. Forest in situ observations using unmanned aerial vehicle as an alternative of terrestrial measurements
Stanton et al. Unmanned aircraft system-derived crop height and normalized difference vegetation index metrics for sorghum yield and aphid stress assessment
Jiménez-Brenes et al. Quantifying pruning impacts on olive tree architecture and annual canopy growth by using UAV-based 3D modelling
Arnó et al. Leaf area index estimation in vineyards using a ground-based LiDAR scanner
Guo et al. Crop 3D—a LiDAR based platform for 3D high-throughput crop phenotyping
Friedli et al. Terrestrial 3D laser scanning to track the increase in canopy height of both monocot and dicot crop species under field conditions
Chu et al. Cotton growth modeling and assessment using unmanned aircraft system visual-band imagery
CN108732129B (en) System and method for representing farmland soil components by images
Gruszczyński et al. Comparison of low-altitude UAV photogrammetry with terrestrial laser scanning as data-source methods for terrain covered in low vegetation
Müller-Linow et al. The leaf angle distribution of natural plant populations: assessing the canopy with a novel software tool
Moorthy et al. Field characterization of olive (Olea europaea L.) tree crown architecture using terrestrial laser scanning data
Jay et al. In-field crop row phenotyping from 3D modeling performed using Structure from Motion
Kalisperakis et al. Leaf area index estimation in vineyards from UAV hyperspectral data, 2D image mosaics and 3D canopy surface models
Bendig et al. UAV-based imaging for multi-temporal, very high resolution crop surface models to monitor crop growth variability
Gil-Docampo et al. Above-ground biomass estimation of arable crops using UAV-based SfM photogrammetry
US20100322477A1 (en) Device and method for detecting a plant
Guan et al. Modeling strawberry biomass and leaf area using object-based analysis of high-resolution images
Cheein et al. Real-time approaches for characterization of fully and partially scanned canopies in groves
Huang et al. Using terrestrial laser scanner for estimating leaf areas of individual trees in a conifer forest
Brocks et al. Toward an automated low-cost three-dimensional crop surface monitoring system using oblique stereo imagery from consumer-grade smart cameras
Crommelinck et al. Simulating an autonomously operating low-cost static terrestrial LiDAR for multitemporal maize crop height measurements