8 July 2011 Effect of water on neural-network-based soil image recognizer and classifier
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Proceedings Volume 8009, Third International Conference on Digital Image Processing (ICDIP 2011); 80092A (2011) https://doi.org/10.1117/12.896156
Event: 3rd International Conference on Digital Image Processing, 2011, Chengdu, China
Abstract
From the last few years, more attention has been directed towards the usage of information technology in agriculture. This new way of farming offers the promise of improving farm profitability. Using Internet the farmers can collect data like geographical- referred yield, weather, soil and other important data related to farming. The aim is to use these data to produce area-specific crop production decisions. For increasing the production quality of crop soil plays very important role. To help the farmer in deciding how to increase the crop quality based on soil. We have proposed, soil image recognizer and classifier, which classifies soil image samples based on their color and morphological features. Different types of soil image samples considered like red soil, black soil, black cotton soil. Using color and morphological features a Neural Network Based Classifier is designed. The effect of water on the soil image classifier is analyzed by adding the water into different portions of soil samples. The accuracy of the soil image classifier is improved by considering wet soil samples.
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Nagaraj V Dharwadkar, Nagaraj V Dharwadkar, D. G. Savakar, D. G. Savakar, S. S. Panchal, S. S. Panchal, A. A. Javaji, A. A. Javaji, S. R. Rathod, S. R. Rathod, } "Effect of water on neural-network-based soil image recognizer and classifier", Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80092A (8 July 2011); doi: 10.1117/12.896156; https://doi.org/10.1117/12.896156
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