Overlapped and Shadowed Tree Crown Segmentation based on HSI Color Model and Watershed Algorithm
Image provides valuable information to the human and this information could be used to take an effective
decision such as information that comes from satellite sensors. Satellite images let the human to gain the information from
the ground for a very wide area. The negative side of satellite images is the resolution still having low quality. Satellite
image plays a vital role in many areas of our live, especially agriculture, where the human can calculate the crown of the tree
for a very wide area in a very short time. The counting of the tree will not be accurate without getting good segmentation of
these crowns. This work has applied segmentation algorithm to separate crown of coconut palm tree from shadow and the
overlapped crown as well. The algorithm has exploited a HSI color model to differentiate the color of crown from the color
of shadow. The result of using HIS color feature gives an impressive outcome. After crown detection the algorithm used
morphological operation such as image filling to enhance the crown. The following step is removing noise or pixels which
considered unwanted objects. Finally, the image was segmented using watershed after applying distance transform on the
image. Since this research does not have ground information to measure the accuracy, the evaluation has been done
manually, where the crown has been counted manually and calculated the accuracy of this work which is 73%.
Keywords - Image Processing, Image Segmentation, Pattern Recognition, Computer Vision, Remote Sensing, Watershed
Algorithm, Satellite Images.