A Novel Approach for Segmentation of Arecanut Bunches Using Active Contouring

  • R. DhaneshaEmail author
  • C. L. Shrinivasa Naika
Part of the Studies in Computational Intelligence book series (SCI, volume 771)


Arecanuts are among the main commercial crops of southern India. Identifying ripeness is important for harvesting arecanut bunches and directly affects the farmer’s profits. Manual identification and harvesting processes, however, are very tedious, requiring many workers for each task. Therefore, in recent years, image processing and computer vision-based techniques have been increasingly applied for fruit ripeness identification, which is important in optimizing business profits and ensuring readiness for harvesting. Thus, segmentation of arecanut bunches is required in order to determine ripeness. There are several techniques for segmenting fruits or vegetables after harvesting to identify ripeness, but there is no technique available for segmenting bunches before harvesting. In this chapter, we describe a computer vision-based approach for segmentation using active contouring, with the aim of identifying the ripeness of arecanut bunches. The experimental results confirm the effectiveness of the proposed method for future analysis.


Ripeness Harvesting Segmentation Erosion Closing Arecanut bunches Active contour 


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringU.B.D.T. College of EngineeringDavanagereIndia

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