A Study of Different Color Segmentation Techniques for Crop Bunch in Arecanut

Author:

S Siddesha1,Niranjan S K1,Manjunath Aradhya V N1

Affiliation:

1. Sri Jayachamarajendra College of Engineering, India

Abstract

Arecanut is an important cash crop of India and ranks first in the production. Arecanut crop bunch segmentation plays very vital role in the process of harvesting. Work on arecanut crop bunch segmentation is of first kind in the literature and this chapter mainly focuses on exploring different color segmentation techniques such as Thresholding, K-means clustering, Fuzzy C Means (FCM), Fast Fuzzy C Means clustering (FFCM), Watershed and Maximum Similarity based Region Merging (MSRM). The effectiveness of the segmentation methods are evaluated on our own collection of Arecanut image dataset of size 200.

Publisher

IGI Global

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Review of the Literature on Arecanut Sorting and Grading Using Computer Vision and Image Processing;International Journal of Applied Engineering and Management Letters;2023-04-29

2. Arecanut Bunch Segmentation Using Deep Learning Techniques;International Journal of Circuits, Systems and Signal Processing;2022-07-26

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