Weed Detection Using SVMs

  • S. Murawwat Electrical Engineering Department, Lahore College for Women University, Pakistan
  • A. Qureshi Electrical Engineering Department, Lahore College for Women University, Lahore, Pakistan
  • S. Ahmad Electrical Engineering Department, Lahore College for Women University, Lahore, Pakistan
  • Y. Shahid Electrical Engineering Department, Lahore College for Women University, Lahore, Pakistan
Keywords: image segmentation, colour segmentation, binarization, morphological features, support vector machines

Abstract

The major concern in Pakistani agriculture is the reduction of growing weed. This research aims to provide a weed detection tool for future agri-robots. The weed detection tool incorporates the use of machine-learning procedure explicitly implementing Support Vector Machines (SVMs) and blob analysis for the effective classification of crop and weed. Weed revealing is based on characteristic features i.e. red green blue (RGB) components which differentiate soil and plant. Morphological features—centroidand length aid to distinguish shape of crop and weed leaves. Following feature extraction, the positive and negative margins are separated by a hyper-plane. The separating hyper-plane acts as the decision surface. Sample input consists of multiple digital field images of carrot crops. Training samples of seventy two images are taken. Accuracy of the outcomes discloses that SVM and blob analysis attain above 50-95% accuracy.

Author Biographies

S. Murawwat, Electrical Engineering Department, Lahore College for Women University, Pakistan

Electrical Engineering Department, Lahore College for Women University, Satellite Town Naya Shehar, Jhang, Lahore, Pakistan

A. Qureshi, Electrical Engineering Department, Lahore College for Women University, Lahore, Pakistan
Electrical Engineering Department, Lahore College for Women University, Lahore, Naya Shehar, Pakistan
S. Ahmad, Electrical Engineering Department, Lahore College for Women University, Lahore, Pakistan
Electrical Engineering Department, Lahore College for Women University, Lahore, Naya Shehar, Pakistan
Y. Shahid, Electrical Engineering Department, Lahore College for Women University, Lahore, Pakistan
Electrical Engineering Department, Lahore College for Women University, Lahore, Naya Shehar, Pakistan

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References

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How to Cite
[1]
S. Murawwat, A. Qureshi, S. Ahmad, and Y. Shahid, “Weed Detection Using SVMs”, Eng. Technol. Appl. Sci. Res., vol. 8, no. 1, pp. 2412-2416, Feb. 2018.

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