Weed Detection and Removal based on Image Processing
Rincy Johnson1, Thomas Mohan2, Sara Paul3
1Rincy Johnson, M.Tech Student, Department of Electronics and Communication Engineering, Mar Athanasius College of Engineering, Kothamangalam, India.
2Thomas Mohan, Assistant Professor, Department of Electronics and Communication Engineering, Mar Athanasius College of Engineering, Kothamangalam, India.
3Sara Paul, Assistant Professor, Department of Electronics and Communication Engineering, Mar Athanasius College of Engineering, Kothamangalam, India.
Manuscript received on February 12, 2020. | Revised Manuscript received on February 21, 2020. | Manuscript published on March 30, 2020. | PP: 347-352 | Volume-8 Issue-6, March 2020. | Retrieval Number: B3679078219 /2020©BEIESP | DOI: 10.35940/ijrte.B3679.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Agriculture, although known as the backbone of the Indian economy, is facing crisis in terms of production. One of the major issues in the agriculture sector is the growth of weeds among the crops. They compete with the desired plants for various resources and hence their growth must be inhibited. At present weeds are removed either manually, which is a time consuming and labour intensive task, or herbicides are being sprayed uniformly all over the field to keep them under check. Spraying of herbicide is very inefficient as the chemical contributes less to weed control and cause contamination of the environment. The main objective of this work is a weed control system that differentiates the weed from crops and restricts weed growth alone by the precise removal of the weed. This is implemented by capturing the images of the field at regular intervals and processing them with a Raspberry Pi board by making use of an image processing algorithm to differentiate the desired plants from the weeds. This is based on various features like colour and size of the crop and weed. Once the weeds are identified and located correctly through image processing, a signal is transmitted from the Raspberry Pi board to turn on the weed cutting system. The selective activation of the weed removal system helps in the precise removal of the weeds and this provides a better environment for the desired plants to grow well.
Keywords: Agriculture, Crop, Image Processing, Raspberry Pi, Weed Detection, Weed Removal.
Scope of the Article: Signal and Image Processing.