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Published in:
2018 | OriginalPaper | Chapter
Thresholding Based Soil Feature Extraction from Digital Image Samples – A Vision Towards Smarter Agrology
Authors : M. Arunpandian, T. Arunprasath, G. Vishnuvarthanan, M. Pallikonda Rajasekaran
Published in: Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 1
Publisher: Springer International Publishing
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Abstract
Soil is one of the natural material, which has the different features for the particular characteristics. In digital image processing is the principle to simplify the identification of soil features. Soil consists of both physical and chemical characteristics. These characteristics are used to find the field of soil usage. Thresholding is the conversion of colour image into binary image and that is used for shape based identification. It applicable for feature extract from curvature, valleys, and non-smoothening surfaces and it enhances the feature and get more information. Fractal dimension is one of the soil feature. A new model is proposed to assign various threshold values apply to the same sample and to determine the range and also the best image model (Red-Green-Blue, Hue-Saturation-Value, Hue-Saturation-Luminance and Hue-Saturation-Intensity) of soil samples. The device can also be modelled as most powerful tool for prediction of land usage for various fields such as agriculture and construction.