Laser & Optoelectronics Progress, Volume. 57, Issue 4, 041016(2020)

Plant Image Recognition with Complex Background Based on Effective Region Screening

Xiaoyu Song1、**, Liting Jin1、*, Yang Zhao2, Yue Sun1, and Tong Liu1
Author Affiliations
  • 1School of Electronics and Information Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China
  • 2Department of Information Engineering, Longqiao College of Lanzhou University of Finance and Economics, Lanzhou, Gansu 730101, China
  • show less

    A plant image recognition method, which is based on effective region screening through a convolutional neural network (CNN), is proposed with an aim to improve the accuracy of plant image recognition in complex backgrounds. First, image (flower, leaf) datasets are used to train an effective region-screening model through a CNN, which is designed to allow the datasets to retain effective areas such as flowers and leaves after screening through the model. Subsequently, the effective areas are extracted from the plant image data sets by Mask R-CNN. Then the effective area screening model is used to screen the effective areas that can represent the plant image categories. The effective areas are divided into training sets and test sets in a ratio of 4∶1. The CNN plant image recognition model based on effective region selection (MRC-GoogleNet) is obtained after training in GoogleNet. Finally, the recognition accuracy is obtained through the model. The experimental results and data reveal that the recognition model, which is based on effective region selection, can more effectively extract image features and improve the recognition accuracy compared with the classical CNN plant image recognition model.

    Tools

    Get Citation

    Copy Citation Text

    Xiaoyu Song, Liting Jin, Yang Zhao, Yue Sun, Tong Liu. Plant Image Recognition with Complex Background Based on Effective Region Screening[J]. Laser & Optoelectronics Progress, 2020, 57(4): 041016

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Image Processing

    Received: Jul. 8, 2019

    Accepted: Aug. 16, 2019

    Published Online: Feb. 20, 2020

    The Author Email: Song Xiaoyu (sxy9998@126.com), Jin Liting (1942861414@qq.com)

    DOI:10.3788/LOP57.041016

    Topics