Leaf segmentation through the classification of edges

04/05/2019
by   Jonathan Bell, et al.
0

We present an approach to leaf level segmentation of images of Arabidopsis thaliana plants based upon detected edges. We introduce a novel approach to edge classification, which forms an important part of a method to both count the leaves and establish the leaf area of a growing plant from images obtained in a high-throughput phenotyping system. Our technique uses a relatively shallow convolutional neural network to classify image edges as background, plant edge, leaf-on-leaf edge or internal leaf noise. The edges themselves were found using the Canny edge detector and the classified edges can be used with simple image processing techniques to generate a region-based segmentation in which the leaves are distinct. This approach is strong at distinguishing occluding pairs of leaves where one leaf is largely hidden, a situation which has proved troublesome for plant image analysis systems in the past. In addition, we introduce the publicly available plant image dataset that was used for this work.

READ FULL TEXT

page 4

page 7

research
11/21/2016

The subset-matched Jaccard index for evaluation of Segmentation for Plant Images

We describe a new measure for the evaluation of region level segmentatio...
research
04/12/2021

Volume and leaf area calculation of cabbage with a neural network-based instance segmentation

Fruit size and leaf area are important indicators for plant health and a...
research
05/18/2020

A Novel Technique Combining Image Processing, Plant Development Properties, and the Hungarian Algorithm, to Improve Leaf Detection in Maize

Manual determination of plant phenotypic properties such as plant archit...
research
06/18/2013

An Overview of the Research on Texture Based Plant Leaf Classification

Plant classification has a broad application prospective in agriculture ...
research
11/15/2017

A Public Image Database for Benchmark of Plant Seedling Classification Algorithms

A database of images of approximately 960 unique plants belonging to 12 ...
research
06/01/2020

An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture

A lack of sufficient training data, both in terms of variety and quantit...
research
11/16/2014

Combining contextual and local edges for line segment extraction in cluttered images

Automatic extraction methods typically assume that line segments are pro...

Please sign up or login with your details

Forgot password? Click here to reset