Tree Identification Using K-Mean Clustering Algorithm
Abstract: Trees occupy an important place in the life of man. Tree plays an important role in purifying air around us. Trees are also very necessary for having good rainfall. So that to classify the tree type is very important for the forest maintenance. With the beginning of high spatial resolution remote sensing sensors; our capacity has greatly improved for tree type identification. Considering the amount of data in need of processing and the high computational costs required by image processing algorithms; predictable computing environments are simply not practical. Therefore; it is necessary to develop techniques and models for resourcefully processing large volume of remote sensing images. In this study; a cluster computing environment was adopted to speed up the calculation time. The test image was first partitioned into hundreds of manageable sub-images. Use of K-mean Clustering algorithm we identifying trees.
Keywords: Image Processing Algorithm, Computing environments, K-mean Clustering, Remote Sensing Sensors
How to Cite?: Archana Singh, Anuj Khuttan, "Tree Identification Using K-Mean Clustering Algorithm", Volume 3 Issue 6, June 2014, International Journal of Science and Research (IJSR), Pages: 460-462, https://www.ijsr.net/getabstract.php?paperid=20132250, DOI: https://dx.doi.org/10.21275/20132250