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ANIMAL DETECTION IN FIELDS USING IMAGE PROCESSING.

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Název: ANIMAL DETECTION IN FIELDS USING IMAGE PROCESSING.
Autoři: APPARI, JAY KUMAR, KAMBLE, MAAHI, CHOUDHARY, NUPUR, DEY, AMAR KUMAR
Zdroj: i-Manager's Journal on Image Processing; Mar2025, Vol. 12 Issue 1, p40-49, 10p
Témata: COMPUTER vision, IMAGE processing, AGRICULTURE, HUMAN settlements, IMAGE segmentation
Abstrakt: One of the primary requirements for sustaining a livelihood is agriculture. Low crop productivity is one of the issues facing farmers in the country. Crops destroyed by wild creatures is a major issue in low productivity. The agrarian fields must be defended from any undesirable interruption from creatures. In traditional styles, growers use crackers, electrical walls, direct observation, etc., to keep creatures away from their fields, but it is a threat factor that harms both humans and creatures. The presence of creatures is detected using Image Processing and Machine Learning in the proposed system. The damage to crops caused by wild creatures is dramatically increasing in India. It frequently poses pitfalls to humans and creatures. As wild creatures continue to cause increasing damage to human settlements, tolerance has become difficult. Therefore, an effective solution has been developed to address this situation. With that background, the ideal of this study is to descry wild creatures before entering into the crop fields and enforcing applicable dread- down mechanisms in real time. This paper presents an overview of the methodologies employed in this prototype model, including image segmentation, point birth, and bracket ways. Overall, this study highlights the significance of image processing technologies in advancing the understanding of these models and promoting sustainable relations between humans and wildlife. [ABSTRACT FROM AUTHOR]
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Databáze: Biomedical Index
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Abstrakt:One of the primary requirements for sustaining a livelihood is agriculture. Low crop productivity is one of the issues facing farmers in the country. Crops destroyed by wild creatures is a major issue in low productivity. The agrarian fields must be defended from any undesirable interruption from creatures. In traditional styles, growers use crackers, electrical walls, direct observation, etc., to keep creatures away from their fields, but it is a threat factor that harms both humans and creatures. The presence of creatures is detected using Image Processing and Machine Learning in the proposed system. The damage to crops caused by wild creatures is dramatically increasing in India. It frequently poses pitfalls to humans and creatures. As wild creatures continue to cause increasing damage to human settlements, tolerance has become difficult. Therefore, an effective solution has been developed to address this situation. With that background, the ideal of this study is to descry wild creatures before entering into the crop fields and enforcing applicable dread- down mechanisms in real time. This paper presents an overview of the methodologies employed in this prototype model, including image segmentation, point birth, and bracket ways. Overall, this study highlights the significance of image processing technologies in advancing the understanding of these models and promoting sustainable relations between humans and wildlife. [ABSTRACT FROM AUTHOR]
ISSN:23494530
DOI:10.26634/jip.12.1.21688