Analysis of morphology-based features for classification of crop and weeds in precision agriculture

Bosilj, Petra and Duckett, Tom and Cielniak, Grzegorz (2018) Analysis of morphology-based features for classification of crop and weeds in precision agriculture. IEEE Robotics and Automation Letters . ISSN 2377-3774

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Analysis of morphology-based features for classification of crop and weeds in precision agriculture

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Abstract

Determining the types of vegetation present in an image is a core step in many precision agriculture tasks. In this paper, we focus on pixel-based approaches for classification of crops versus weeds, especially for complex cases involving overlapping plants and partial occlusion. We examine the benefits of multi-scale and content-driven morphology-based descriptors called Attribute Profiles. These are compared to state-of-the art keypoint descriptors with a fixed neighbourhood previously used in precision agriculture, namely Histograms of Oriented Gradients and Local Binary Patterns. The proposed classification technique is especially advantageous when coupled with morphology-based segmentation on a max-tree structure, as the same representation can be re-used for feature extraction. The robustness of the approach is demonstrated by an experimental evaluation on two datasets with different crop types. The proposed approach compared favourably to state-of-the-art approaches without an increase in computational complexity, while being able to provide descriptors at a higher resolution.

Keywords:precision agriculture, classification, attribute morphology
Subjects:H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
ID Code:32371
Deposited On:26 Jun 2018 20:13

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