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Pattern Recognition and Image Analysis

Erschienen in:

01.03.2023 | APPLIED PROBLEMS

Design and Implementation of Land Area Calculation for Maps Using Mask Region Based Convolutional Neural Networks Deep Neural Network

verfasst von: Akram A. Pathan, Nagaraj V. Dharwadkar

Erschienen in: Pattern Recognition and Image Analysis | Ausgabe 1/2023

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Abstract

Maps of the land are developed by the surveyor, map developer according to survey of land. In such maps land boundaries are shown using property lines. So the area of land is also mentioned in the maps to the valuation of the property. Area calculation is one of the main work of the surveyor so it is important for him to calculate it fast. So we have implemented a system which can help surveyor, land map developers to calculate the area. We implemented this using image processing and the deep learning model mask region based convolutional neural network (RCNN). For better results, we implemented this at a basic level. At base level synthetic dataset consists of 2 dimensional images of different geometry shapes (triangle, quadrilateral, pentagon, hexagon, octagon) and training our model to detect the shape in the image and based on this further process of area calculation of that shape takes place. This solution is unique for land developers because it uses deep learning and image processing to obtain results.

Vorheriger Artikel Fine-Grained Object Recognition Using a Combination Model of Navigator–Teacher–Scrutinizer and Spinal Networks

Nächster Artikel Enhancement of Brain Magnetic Resonance Images Using Cascade of Notch Filter and Linear Transformation Methods

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Titel: Design and Implementation of Land Area Calculation for Maps Using Mask Region Based Convolutional Neural Networks Deep Neural Network
verfasst von: Akram A. Pathan
Nagaraj V. Dharwadkar
Publikationsdatum: 01.03.2023
Verlag: Pleiades Publishing
Erschienen in: Pattern Recognition and Image Analysis / Ausgabe 1/2023
Print ISSN: 1054-6618
Elektronische ISSN: 1555-6212
DOI: https://doi.org/10.1134/S1054661822040095

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