Abstract
The object-based image analysis (OBIA) is extensively used nowadays for classification of high-resolution satellite images (HRSI). In OBIA, the analysis is based on a group of pixels known as objects. It differs from the traditional pixels-based methodology, where individual pixels are analyzed. In OBIA, the image analysis consists of image segmentation, object attribution, and classification. The segmentation process thus identifies a group of pixels and are known as objects. These objects are taken for further analysis. Thus segmentation is an important step in OBIA. In order to find out the boundary of agriculture parcels, a two-step process is followed. First, the segmentation of the images is done using the statistical region merging (SRM) technique. Then the boundary information and center of the segmentation are found out using MATLAB. The best fit segment was found out using trial and errors. The extracted boundary information is very encouraging and it matches the parcel boundaries recorded in revenue registers. The completeness and precision analysis of the plots are also quite satisfactory.
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Khadanga, G., Jain, K. (2020). Agriculture Parcel Boundary Detection from Remotely Sensed Images. In: Chaudhuri, B., Nakagawa, M., Khanna, P., Kumar, S. (eds) Proceedings of 3rd International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 1022. Springer, Singapore. https://doi.org/10.1007/978-981-32-9088-4_26
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DOI: https://doi.org/10.1007/978-981-32-9088-4_26
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