Unsupervised segmentation of greenhouse plant images based on modified Latent Dirichlet Allocation

PeerJ. 2018 Jun 28:6:e5036. doi: 10.7717/peerj.5036. eCollection 2018.

Abstract

Agricultural greenhouse plant images with complicated scenes are difficult to precisely manually label. The appearance of leaf disease spots and mosses increases the difficulty in plant segmentation. Considering these problems, this paper proposed a statistical image segmentation algorithm MSBS-LDA (Mean-shift Bandwidths Searching Latent Dirichlet Allocation), which can perform unsupervised segmentation of greenhouse plants. The main idea of the algorithm is to take advantage of the language model LDA (Latent Dirichlet Allocation) to deal with image segmentation based on the design of spatial documents. The maximum points of probability density function in image space are mapped as documents and Mean-shift is utilized to fulfill the word-document assignment. The proportion of the first major word in word frequency statistics determines the coordinate space bandwidth, and the spatial LDA segmentation procedure iteratively searches for optimal color space bandwidth in the light of the LUV distances between classes. In view of the fruits in plant segmentation result and the ever-changing illumination condition in greenhouses, an improved leaf segmentation method based on watershed is proposed to further segment the leaves. Experiment results show that the proposed methods can segment greenhouse plants and leaves in an unsupervised way and obtain a high segmentation accuracy together with an effective extraction of the fruit part.

Keywords: Latent Dirichlet Allocation; Mean-shift; Optimal bandwidth search; Plant segmentation; Word-document assignment.

Grants and funding

This research was supported by the National High-Tech R&D Program of China under Grant 2013AA102305, the National Natural Science Foundation of China under Grants 61573258, and the US National Science Foundation’s BEACON Center for the Study of Evolution in Action, under cooperative agreement DBI-0939454. There was no additional external funding received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.