Identification of Idealized Leaf Types Using Simple Dimensionless Shape Factors by Image Analysis

@article{Yonekawa1996IdentificationOI,
  title={Identification of Idealized Leaf Types Using Simple Dimensionless Shape Factors by Image Analysis},
  author={Satoshi Yonekawa and Naoki Sakai and Osamu Kitani},
  journal={Transactions of the ASABE},
  year={1996},
  volume={39},
  pages={1525-1533}
}
Identification of plants is important to develop robotics for pest, disease, and weed control with machine vision. Leaf shape is a common source of information used to identify plants. Intelligent vision systems are the next generation in machine vision. The addition of intelligence into vision systems requires an understanding and structuring of human visual techniques. 
Machine vision detection parameters for plant species identification
Machine vision based on classical image processing techniques has the potential to be a useful tool for plant detection and identification. Plant identification is needed for weed detection,
Supervised Locally Linear Embedding for Plant Leaf Image Feature Extraction
TLDR
This paper gives one recognition approach based on supervised locally linear embedding (LLE) and K-nearest neighbors and demonstrated the proposed method is effective in advancing the recognition rate.
Research on Automatic Counting Soybean Leaf Aphids System Based on Computer Vision Technology
TLDR
In the experimentation, the computer vision technology used in this experimentation can automatically count aphids and showed that this method counts aphids accurately, rapidly and effectively.
Classification of images of wheat, ryegrass and brome grass species at early growth stages using principal component analysis
TLDR
A framework to differentiate early narrow-leaf wheat from two common weeds from their digital images is developed using a combination of colour, texture and shape features reduced to three descriptors using Principal Component Analysis.
A Survey of Plant Recognition Method Based on Image Processing
TLDR
This paper overviews the study of automatic plant recognition by use of computer from plant leaves and flowers, and analyses the limitations exist in the present study.
An individual grape leaf disease identification using leaf skeletons and KNN classification
  • N. Krithika, A. Selvarani
  • Computer Science
    2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS)
  • 2017
The most challenging process in agricultural applications is identification of leaf individually. In this paper, the classification of grape leaf diseases is proposed along with the leaf
Field pest identification by an improved Gabor texture segmentation scheme
TLDR
The results showed that the GaborBoostSVM method is capable of performing texture‐based pest and background classification consistently high, effectively and with high classification accuracy.
Weed removal in cultivated field by autonomous robot using LABVIEW
  • A. Patnaik, R. Narayanamoorthi
  • Computer Science
    2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS)
  • 2015
TLDR
The proposed idea emphasizes on the removal of weeds in a semi-structured cultivated field by using image processing to cut the weeds precisely which is present near to the cultivated plant and collect it separately.
...
...