International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 06 | Jun 2023
p-ISSN: 2395-0072
www.irjet.net
Automated Mechanism for Sugarcane Bud Detection & Cutting Azmatali Nadaf1, S. S. Sankpal2, D. B. Kadam3 Prathamesh Kumbhar4 Shreyas Patil5 Sejal Gaikwad6 1,4,5,6 B.Tech IV, E&TC, Padmabhooshan Vasantraodada Patil Institute of Technology, Budhgaon, Maharashtra,
India.
2Associate Professor, E&TC, Padmabhooshan Vasantraodada Patil Institute of Technology, Budhgaon,
Maharashtra, India.
3Professor, E&TC, Padmabhooshan Vasantraodada Patil Institute of Technology, Budhgaon, Maharashtra, India.
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Abstract – An automatic sugarcane bud detection and
The system's effectiveness was tested by conducting experiments on real sugarcane plants, and the results demonstrate promising accuracy levels.
cutting mechanism is an innovative technology that utilizes computer vision to accurately detect and send signal to the hardware module i.e. in our case an Arduino UNO which will then control the cutting mechanism and the sugarcane movement with the use of a conveyor belt. This machine offers a significant improvement over traditional manual method of sugarcane bud cutting, as it reduces labor cost, increase efficiency and improves the accuracy of the cutting process. One of the major advantages of this machine is its ability to accurately detect and cut sugarcane buds, which in turn reduce the time and effort required for manual cutting. Overall the automatic sugarcane bud detection and cutting mechanism is a promising innovation in the field of agriculture that has the potential to revolutionize how sugarcane is grown and harvested.
Figure 1 - Sugarcane Buds
Key Words: Image Processing, Computer Vision, Sugarcane Bud Cutting, Automatic Sugarcane Bud Cutting, Arduino UNO, Continuous Servo Motor, Camera, Cutter.
The proposed system has the potential to improve the efficiency and reduce the labor costs of sugarcane bud cutting, which could ultimately contribute to a sustainable and profitable sugarcane industry.
1. INTRODUCTION
2. IMAGE PROCESSING
Sugarcane cultivation is a vital component of the global economy and plays a crucial role in the food and beverage industry. The process of cultivating sugarcane involves various manual operations, such as bud cutting, which require significant time and labor investments. The existing bud cutting machines have limited capabilities and require constant supervision, which leads to increased labor costs and reduced efficiency. In this context, the development of automated sugarcane bud detection and cutting mechanism could bring substantial benefits to the industry.
Image processing is a method used to manipulate digital images through mathematical algorithms and techniques to enhance the image's quality, clarity, and interpretability. In our project, image processing is utilized to extract features from the images and classify them based on those features. There are several methods used in image processing, including:
This research project proposes a system for detecting and cutting sugarcane buds using computer vision and machine learning techniques. The proposed system utilizes the Hough Circle Transform algorithm to detect the circular shape of the sugarcane buds and an Arduino-based controller to control the cutting mechanism.
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Image filtering: This method is used to remove unwanted noise from the image or enhance specific features by applying a filter. Common filtering techniques include Gaussian filtering, Median filtering, and Sobel filtering.
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Image segmentation: This technique is used to partition an image into multiple regions or segments to extract meaningful information from
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