Pest Detection using Image Processing
Shilpa Itnal1, Mathena Akhila2, Syed Sha Noorulla Khadri3, Vanukuri Meher Sreemaiee4
1Shilpa Itnal*, Koneru Lakshmaiah Education Foundation, Guntur Vaddeswaram, India.
2Mathena Akhila, Koneru Lakshmaiah Education Foundation, Guntur Vaddeswaram, India.
3Syed Sha Noorulla Khadri, Koneru Lakshmaiah Education Foundation, Guntur, Vaddeswaram, India.
4Vanukuri Meher Sreemaiee, Koneru Lakshmaiah Education Foundation, Guntur Vaddeswaram, India.
Manuscript received on November 14, 2019. | Revised Manuscript received on 23 November, 2019. | Manuscript published on December 10, 2019. | PP: 1496-1498 | Volume-9 Issue-2, December 2019. | Retrieval Number: B6875129219/2019©BEIESP | DOI: 10.35940/ijitee.B6875.129219
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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 is one of the most significant economic activity. They are many ways that leads to the low productivity of agriculture, but the best method to protect the crop is by detecting the diseases in the early stage. In most of the cases diseases are caused by pest, insects, pathogens which reduce the productivity of the crop at the large scale. If pests are detected on the leaves then, precautions should be taken to avoid huge productivity loss at the end. The main objective of this paper is to identify the pests using image processing techniques like Gaussian blur, segmentation, watershed separation, morphological operations. These techniques are more efficient and less time consuming while identifying the pests over the leaf image with high intensity.
Keywords: Image processing, Gaussian blur, Segmentation, Morphological operations, Pest identification.
Scope of the Article: Signal and Image Processing