Journal Title : International Journal of Modern Trends in Engineering and Science
Paper Title : A NOVEL APPROACH TO DETECT THE WATER LEVEL IN PLANTS BY USING THERMAL IMAGE
Volume 04 Issue 06 2017
ISSN no: 2348-3121
Page no: 52-55
Abstract – Thermal imaging has shown potential to assist with many aspects of irrigation management that include scheduling application of water and detecting leaking irrigation canals and delivery systems. There are particular challenges for use of thermal imaging for scheduling irrigation in humid subtropical climates, which include the need for fine delineation of canopy temperatures under low vapor pressure deficits, proper accounting for micro meteorological conditions, and altitude effects on canopy temperature represented at the camera Identification of water level for plant from thermal images becomes more difficult since the water level become vary from each image to image. In order to perform this process, water level identification for plant images in initial stage the original image is converted into the LAB color space the red ,green and blue colors are converted into the LAB color space then converted color space grouped into the similar image based on the k-means clustering method . The k-means clustering methods group the similar image objects based on the converted color space, then water level threshold value are fixed to identify the water if the color of red is greater than the 30 % then the particular plant still required the water level from this way the water level identified. Performance analysis was charted for Bayesian classifier and k-means clustering method. K-means clustering shows better result compared with the fundamental classifier.
Keywords – Irrigation Canals; Canopy Temperature; LAB Color Space; K-means Clustering Method; Bayesian Classifier
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