Quantitative analysis of Mouza map image to estimate land area using zooming and Canny edge detection

Abstract

In Bangladesh, mouza map is used to maintain the record of land measurement, which is a form of interpreting land ownership as well as estimation. Unfortunately, the automatic determination of land is still under development. As a result, land administrators have to encounter multiple hurdles while evaluating any area by employing local civil engineers. Thus, our country needs an automated land estimation system so that it can reduce time, cost and other difficulties which inspired us to develop a system that requires only mouza map image. Once image acquisition is done, we applied the curvature interpolation technique to zoom the map that helps to select any area by the Area Selection Method. The selected area is then segmented by employing the Canny edge detection method. Finally, the area is calculated from the segmented image and extracted features of the selected location. Compared to the field measurement, the system gave the accuracy of 89.8%. Hence, the land administrators will be able to provide the land information to the landowners promptly.

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