Crop Monitoring Using Image Processing
Harvesting Readiness
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Crop cultivation plays an essential role in the agricultural field. Presently, the loss of food is mainly due to infected crops, which reflexively reduces the yield of the farm. The challenges have been to identify nature of soil and its fertile capacity, to reduce usage of pesticides and to monitor the quantity of agricultural produce. This book discusses the solution to this using image processing. This book has manifested enhanced clustering algorithm to not only predict the infected area of the leaves but also the soil fertility. A colour based segmentation model is defined to classify the...
Crop cultivation plays an essential role in the agricultural field. Presently, the loss of food is mainly due to infected crops, which reflexively reduces the yield of the farm. The challenges have been to identify nature of soil and its fertile capacity, to reduce usage of pesticides and to monitor the quantity of agricultural produce. This book discusses the solution to this using image processing. This book has manifested enhanced clustering algorithm to not only predict the infected area of the leaves but also the soil fertility. A colour based segmentation model is defined to classify the infected region and placing it to its relevant classes. Experimental analyses were done on samples images in terms of time complexity and the area of infected region. Plant diseases can be correlated to acquired images and processed for decision making. The pH value correlation is utilized to identify Fertility of soil. This book details the involved steps like image acquisition, image pre-processing, image segmentation, feature extraction and classification. This book also provides the sample coding on the developed algorithms for the reader's benefit.
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