Segmentation of Arecanut Bunches: a Comparative Study of Different Color Models

Arecanut is one of the important commercial crop of Agriculture sector. Agriculture sector plays important role towards the economic development of India. The market price of arecanut is determined by it's maturity level of the ripeness . Farmers often incur loss in profit due to the lack of expertise in judging the ripeness maturity level of the arecanut bunches before the harvest. In the recent years, image processing and computer vision based precision agriculture techniques has helped the farmers in identifying the ripeness quality of the crops. So, accurate segmentation of the arecanut bunches plays vital role in the automated identification of the arecanut ripeness maturity level. In this proposed work YUV, YCbCr, YCgCr, YPbPr and HSV color models are used to segment arecanut bunches. Dataset with 1017 images of arecanut bunch are used to conduct experiment and segmentation result of the each color model is evaluated using different segmentation performance metrics. Results of experiment clarifies, segmentation of arecanut bunches were efficient using YCgCr and HSV color models.